anwar m. shaikh, e. ahmet tonak measuring the wealth of nations the political economy of national...

This book provides an alternate foundation for the measurementof the production of nations, and applies it to the U.S. economyfor the postwar period. The patterns that result are significantlydifferent from those derived within conventional systems of na-tional accounts.

Conventional national accounts seriously distort basic eco-nomic aggregates because they classify military, bureaucratic,and financial activities as creation of new wealth. In fact, theseauthors argue, such aggregates should be classified as forms ofsocial consumption which, like personal consumption, actuallyuse up social wealth in the performance of their functions.

The difference between the two approaches has an impact notonly on basic aggregate economic measures, but also on the veryunderstanding of the observed patterns of growth and stagna-tion. In a world of burgeoning militaries, bureaucracies, and salesforces, such matters can assume great significance at the levels ofboth theory and policy.

MEASURING THE WEALTH OF NATIONS

Measuring the wealth of nationsThe political economy of national accounts

ANWAR M. SHAIKHNew School for Social Research

E. AHMET TONAKSimon's Rock College of Bard

CAMBRIDGEUNIVERSITY PRESS

CAMBRIDGE UNIVERSITY PRESSCambridge, New York, Melbourne, Madrid, Cape Town, Singapore, Sao Paulo

Cambridge University Press

The Edinburgh Building, Cambridge CB2 8RU, UK

Published in the United States of America by Cambridge University Press, New York

www.cambridge.orgInformation on this title: www.cambridge.org/9780521414241© Cambridge University Press 1994

This publication is in copyright. Subject to statutory exceptionand to the provisions of relevant collective licensing agreements,no reproduction of any part may take place without the writtenpermission of Cambridge University Press.

First published 1994Reprinted 1996First paperback edition 1996

A catalogue record for this publication is available from the British Library

ISBN 978-0-521-41424-1 hardbackISBN 978-0-521-56479-3 paperback

Transferred to digital printing 2007

CONTENTS

List of figures page viiiList of tables xiPreface xv

1 Introduction 11.1 Approaches to the measurement of national product 11.2 Official national accounts 61.3 Extended national accounts for the United States 91.4 Toward an alternate approach to national accounts 17

2 Basic theoretical foundations 202.1 The distinction between production and nonproduction

activities 202.2 Productive labor under capitalism 292.3 Productive labor in orthodox economics 322.4 Production labor, surplus value, and profit 34

3 Marxian categories and national accounts: Money value flows 383.1 Primary flows: Production and trade 403.2 Secondary flows 52

A. Private secondary flo ws: Ground rent, finance,royalties 53

B. Public secondary flows: General government activities 593.3 Net transfers from wages, the social wage, and the

adjusted rate of surplus value 633.4 Foreign trade 653.5 Noncapitalist activities and illegal activities 713.6 Summary of the relation between Marxian and

conventional national accounts 72

Contents vi

4 Marxian categories and national accounts: Labor valuecalculations 784.1 Calculating labor value magnitudes 784.2 Rates of exploitation of productive and unproductive

workers 86

5 Empirical estimates of Marxian categories 895.1 Primary Marxian measures in benchmark years 895.2 Annual series for primary measures, based on NIPA

data 925.3 Employment, wages, and variable capital 1075.4 Surplus value and surplus product 1135.5 Marxian, average, and corporate rates of profit 1225.6 Rates of exploitation of productive and unproductive

workers 1295.7 Marxian and conventional measures of productivity 1315.8 Government absorption of surplus value 1375.9 Net tax on labor and adjusted rate of surplus value 1375.10 Empirical effects of price-value deviations 1415.11 Approximating the rate of surplus value 1445.12 Summary of empirical results 146

6 A critical analysis of previous empirical studies 1526.1 Studies that fail to distinguish between Marxian and

NIPA categories 1546.2 Studies that do distinguish between productive and

unproductive labor 1616.3 Studies based on the distinction between necessary and

unnecessary labor (economic "surplus") 202

7 Summary and conclusions 2107.1 Surplus value, profit, and growth 2117.2 Marxian and conventional national accounts 2167.3 Empirical results 2217.4 Comparison with previous studies 2247.5 Conclusions 228

Appendices 231A Methodology of the input-output database 233B Operations on the real estate and finance sectors 253C Summary input-output tables 274D Interpolation of key input-output variables 278E Annual estimates of primary variables 283F Productive and unproductive labor 295

Contents vii

G Wages and variable capital 304H Surplus value and profit 323I Rates of exploitation of productive and unproductive

workers 329J Measures of productivity 336K Government absorption of surplus value 344L Aglietta's index of the rate of surplus value 346M Mage and NIPA measures of the capitalist sector gross

product 351N The net transfer between workers and the state, and its

impact on the rate of surplus value 356

References 361Author index 369Subject index 371

FIGURES

1.1 Alternate measures of GFP 16

2.1 Production and nonproduction labor 222.2 Nonproduction labor and social consumption 292.3 Productive and unproductive labor under capital 30

3.1 Division of value: Production alone 433.2 Use of product: Production alone 443.3 IO accounts and Marxian categories: Production alone 443.4 Division of value: Production and trade 463.5 Use of product: Production and trade 473.6 IO accounts and Marxian categories: Production and

trade 483.7 IO accounts and Marxian categories: Primary flows 523.8 IO accounts and Marxian categories: Private royalties

payments 563.9 Production and royalties only 583.10 IO accounts and Marxian categories: General government 613.11 IO accounts and Marxian categories: Overall summary 74

4.1 IO accounts and Marxian categories: Condensed form 794.2 Production, trade, and royalties sectors 834.3 Input-output coefficients matrix and labor coefficients

vector 83

5.1 IO accounts and Marxian categories: Summary mapping 905.2 1972 IO table 915.3 Real total and final product, and real GNP 1065.4 Ratios of real product measures 106

vin

Figures ix

5.5 Components of total value 1075.6 Components of total product 1075.7 Total labor and productive labor 1115.8 Total real wage and variable capital 1185.9 Productive employment and wage shares 1185.10 Productive and unproductive employment compensation 1195.11 Relative rates of employment and compensation 1195.12 Real surplus value S* and profit-type income P+ 1225.13 Rate of surplus value SVV* and profit/wage ratio P+/EC 1235.14 Components of real total value 1235.15 Value composition and the input/wage ratio 1245.16 Aggregate rates of profit 1285.17 Rate of surplus value and composition of capital 1285.18 Rates of exploitation and related measures 1305.19 Productivity measures 1365.20 Productivity indexes 1365.21 Government absorption of surplus value (G^/SP*) 1405.22 Benefit and tax rates relative to total employee

compensation 1415.23 Net transfer rate 1425.24 Rate of surplus value adjusted for net taxes 1425.25 Value (S/V) and money (SVV*) rates of surplus value,

product side 1455.26 Approximation to the rate of surplus value 150

6.1 Theoretical bases for the type of empirical estimates 1546.2 Rate of surplus value SVV* and profit/wage ratio P+/EC 1556.3 Wage shares in advanced capitalist countries, 1950-70 1566.4 Estimates of the rate of surplus value: Manufacturing 1706.5 Aggregate and sectoral realized rates of surplus value 1726.6 Ratios of sectoral rates of surplus value to the aggregate

rate 1736.7 Rates of surplus value: Mage, Shaikh, Shaikh and Tonak 1816.8 Aglietta's real social wage cost versus the unit value of

labor power 1836.9 Rates of surplus value: Moseley, Shaikh, Tonak, Shaikh

and Tonak 1876.10 Real surplus value and economic surplus 2076.11 Real rates of surplus value and economic surplus 207

7.1 Social burden, consumption, and savings rates 2157.2 Profit and growth rates 215

Figures x

B. 1 Removing imputed rentals 254B.2 Rentals in input-output accounts 255B.3 Rentals adjusted for pass-through costs 256B.4 Rentals treated as a trading activity 257B.5 Division of value: Business royalties payments 259B.6 Use of product: Business royalties payments 260B.7 IO accounts and Marxian categories: Business royalties

payments as costs 260B. 8 Partial IO representation of business royalties payments

as disbursements from value added 261B.9 Revenue side: Business royalties payments to households 264B. 10 Use side: Business royalties payments to households 264B. 11 IO accounts and Marxian categories: Business royalties

payments to households 265B. 12 Revenue side: Household payments to royalties sector 265B. 13 Use side: Household payments to royalties sector 265B.14 IO accounts and Marxian categories: Household

payments to royalties sector 266

C. 1 IO accounts and Marxian categories: Summary mapping 274C.2 1947 IO table 275C.3 1958 IO table 275CA 1963 IO table 276C.5 1967 IO table 276C.6 1972 IO table 277C.I 1977 IO table 277

TABLES

3.1 Sectoral structure of reproduction 403.2 Production and trade sectors 413.3 Value and use of the product 423.4 Marxian and IO measures: Revenue side 423.5 Marxian and IO measures: Use side 433.6 Marxian and IO measures: Production and trade 503.7 Marxian and IO measures: Private royalties payments 573.8 Public secondary flows: General government activities 633.9 Domestically produced and used commodities 673.10 Exports 683.11 Imports 683.12 Marxian and IO measures: Overall summary 76

4.1 Labor value and money value measures 824.2 Calculations of labor value flows: Numerical example 844.3 An inconsistent (symmetric) mapping between Marxian

and IO categories: Use side 854.4 Calculating rates of exploitation 87

5.1 Primary Marxian and IO measures, 1972 935.2 Primary Marxian and IO measures, benchmark years 945.3 Primary and Marxian and NIPA measures, benchmark

years 985.4 Primary Marxian and NIPA measures, 1948-89 1005.5 Total labor and productive employment, 1948-89 1105.6 Total wages and variable capital, 1948-89 1155.7 Marxian variables and their orthodox counterparts,

1948-89 120

XI

Tables xii

5.8 Aggregate rates of profit and compositions of capital,1948-89 125

5.9 Changes in profit rates and basic components 1295.10 Marxian and conventional measures of productivity,

1948-89 1335.11 Government absorption of surplus value, 1948-89 1385.12 Labor value and money rates of surplus value 1445.13 Approximation to the rate of surplus value, 1948-89 1475.14 Comparison of key Marxian and orthodox measures 151

6.1 Wolff's estimates of the money and value rates of surplusvalue in Puerto Rico 158

6.2 Sectoral (manufacturing) estimates of the rate of surplusvalue, 1899-1984 168

6.3 Manufacturing sector, 1970 1716.4 Our basic mapping between Marxian and IO-NIPA

categories 1746.5 Comparison between our mapping and Mage's 1766.6 Rates of surplus value in Greece, selected years 1906.7 Money and labor value measure: Revenue side 1926.8 Estimates of the value rate of surplus value in Japan,

selected years 1956.9 Rates of surplus value, Izumi vs. Khanjian 1966.10 Rates of surplus value, Wolff vs. others 2026.11 Real surplus value and economic surplus 205

7.1 Profit, accumulation, social savings, and burden rates 217

A. 1 Mapping between sectors of the original 1972 85-ordertable and the final 82 x 88IO tables 235

A.2 Sectoral correspondence for the different IO tables 244A.3 Mapping of government sectors between the 87 x 94 and

87x9810 tables 249A.4 Sectoral list for the 82 x 88 IO table 250A. 5 Sectoral list for the 6 x 9 IO table 252

B. 1 Marxian and IO measures: Business royalties payments 262B.2 Marxian and IO measures: Household payments to the

royalties sector 268B.3 Calculation of the proportion of ground rent in real estate

(g), benchmark years 271B.4 Annual estimates of ABR, 1947-90 272

D. 1 Interpolation of M'p between 1963 and 1967 279D.2 NIPA-based interpolations of key IO variables 280

Tables xiii

E. 1 Annual estimates of TV*, 1948-89 284E.2 Procedure for calculating TP*, 1948-89 291

F. 1 Productive and unproductive labor, 1948-89 298

G.I Total wage (W), 1948-89 306G.2 Total variable capital and total wages of unproductive

workers, 1948-89 314

H. 1 Surplus value and profit, 1948-89 324

I.I Rates of exploitation of unproductive workers, 1948-89 330

J. 1 Productivity of labor, 1948-89 338

K. 1 Government absorption of surplus value, 1948-89 345

L. 1 Aglietta's index of SVV*, 1948-89 349

M. 1 NIPA-based GDP in production and trade sectors, 1958 352M.2 Components of Mage's gross product and NIPA GDP 352M.3 NIPA equivalent of Mage's nonfarm gross value added,

1958 353M.4 Components of NIPA-equivalent and Mage's capitalist

sector nonfarm gross product, 1958 354M.5 Relation between gross property-type income and Mage's

gross surplus value, 1958 355

N. 1 Estimation of the net transfer for the United States, 1964 358N.2 Benefit, tax, net transfer rates, and adjusted and

unadjusted rates of surplus value, 1952-89 359

PREFACE

This book has been a long time in the making. The interest in providingan empirical framework that would correspond to Marxian categoriesdates back to 1972-73, when Anwar Shaikh first discovered Shane Mage'spathbreaking work and developed an alternate schema and an alternateset of estimates based on Mage's own data.

In 1974 Shaikh came across Edward Wolff's working paper on input-output-based estimates of the rate of surplus value in Puerto Rico. Thisadded a new dimension to the problem. Mage's work emphasized the sig-nificance of the distinction between productive and unproductive labor,but it was restricted to only the value-added side of national income ac-counts. On the other hand, whereas Wolff's work was located within themore comprehensive double-entry framework of input-output accounts,it did not distinguish between productive and unproductive labor. Thisled Shaikh to attempt to develop a comprehensive framework for Marx-ian categories which made both distinctions simultaneously.

The procedure that emerged in 1975 was essentially the same one usedin this book: a mapping between Marxian and input-output categoriesillustrated by means of a continuing numerical example in which bothtotal price (the sum of purchasers' prices) and the magnitudes of the ag-gregate value flows (total value and its basic components) were held con-stant, while the associated money forms became ever more complex asmore concrete factors were considered. This allowed one to verify, at eachstage of the argument, that the overall mapping was correct.

For a short time in the mid-1970s Wolff and Shaikh joined forces, buttheir paths soon diverged. By 1978 Shaikh had produced a final draft of apaper that systematically built up a mapping between Marxian and na-tional income account categories, provided measures of the rate of sur-plus value in the United States, and made some preliminary estimates (for

xv

Preface xvi

three sample years) of the size and direction of the net transfer betweenworkers and the state (i.e., of the balance between taxes paid by workersand the social expenditures directed toward them). This paper circulatedwidely, but was never published (although an extended and somewhatdifferent version appeared in Shaikh 1980b). Instead, Shaikh turned hisattention to broadening the framework to encompass input-output ac-counts and data.

In the late 1970s, Ahmet Tonak also became interested in the estima-tion of Marxian categories. Using the schema of Shaikh's unpublishedpaper, he produced one of the first systematic estimates of the rate of sur-plus value in Turkey, published (in Turkish) in 1979. During the early1980s, Tonak focused on the United States, extending the sample esti-mates of the net tax on workers to the whole postwar period, providinghis own estimates of variable capital and surplus value, and tracing outthe general impact of the net tax on the rate of surplus value. This workbecame his Ph.D. dissertation in 1984, which was the basis for subsequentextensions by Tonak (1987) and Shaikh and Tonak (1987).

During the early 1980s, our attempts to utilize input-output data weregreatly hampered by a lack of computer facilities. Many people were in-strumental in helping to overcome these and other related barriers. MichelJuillard, who was at the time working on recasting U.S. input-outputand national income account data into a Marxian departmental schema,was of invaluable theoretical and empirical help. So too was KatherineKazanas, whose work focused on the impact of the distinction betweenproduction and nonproduction labor for the measurement of productiv-ity. Julie Graham and Don Shakow provided similarly crucial support inthe manipulation of the input-output tables. Ernest Mandel and DimitriPapadimitriou helped secure funding at various points. With the help ofEduardo Ochoa, Paul Cooney, and Michel Juillard, Ara Khanjian cre-ated an input-output database and used the basic framework to measureand compare money and labor value flows in the United States (Khanjian1989). All provided great moral and intellectual support throughout.

By the mid-1980s, the two of us had begun working together on turningthis project into the present book. A first draft was produced in 1985,thanks to a grant provided through the generous support of the HamburgInstitute for Social Studies, and the basic results were made available inthe same year at a conference supported by Bard College. A second, sub-stantially revised draft was produced in 1989, which was once again ex-tended and revised in 1992. During much of this period, Dimitri Papadi-mitriou of Bard College and Bernard Rodgers of Simon's Rock Collegeof Bard provided moral and material assistance for our efforts. We owethem a special debt.

Preface xvii

From the mid- to late 1970s onward, the various stages of this projecthave regularly appeared in Shaikh's lectures on advanced political econ-omy. Many graduate students who have been (willingly and unwillingly)exposed to this material over the years have provided both support andcriticism which has helped shape the final result.

In addition to those mentioned previously, we note our debts to PeterBrooks, Etelberto Ortiz, Hector Figueroa, Rebecca Kalmans, and NezihGiiner. Korkut Boratav, Nail Sathgan, and Sungur Savran provided criti-cal feedback on a version of the manuscript, as did an anonymous refereefor this press. Hakan Arslan, Matt Noyes, and Greg Bongen were vital tothe production of the many charts which adorn this book. We also thankRussell Miller for his contribution to the construction of the index. MattDarnell provided superb editorial assistance in rendering the final product.

Most of all, we wish to express our gratitude to our families for theirsupport and forbearance during this long and difficult task. It is to Fadimeand Ali, and to Diana, Kirsten and Lia, that we owe the greatest debt.

A. M.S.E.A.T.

Introduction

1.1 Approaches to the measurement of national productThis book aims to provide an alternate foundation for the mea-

surement of the production of nations. The framework developed here isapplied to the U.S. economy for the postwar period. The patterns thatresult are significantly different from those derived within conventionalsystems of national accounts.

National accounts give systematic empirical form to the structure, pat-terns, and performance of an economy (Young and Tice 1985). In themodern world, they provide the objective basis for judging the level andprogress of the wealth of nations and for identifying the causes of successand failure.

Conventional systems of national accounts include the United NationsSystem of National Accounts, the United States National Income andProduct Accounts, and various forms of input-output accounts. It is ourcontention that these types of accounts seriously distort the levels andtrends of the national product, the surplus product, productivity, andother major aggregate economic variables. Because measurement andanalysis are inextricably intertwined, our understanding of intertemporaland international economic development is correspondingly affected.

Criticisms of official national accounts are not new. Debates about theirpurpose and structure have gone on from the very start (Eisner 1988,p. 1611). In recent times, there has been a renewed flurry of questionsabout their adequacy. Such criticisms come from a variety of quarters,ranging from official agencies such as the United Nations to a variety ofprestigious economists. In Section 2 we address the issues involved.

The measurement of national product lies at the core of all systems ofnational accounts (Carson and Honsa 1990, pp. 28-9). In this regard, it is

1

Measuring the wealth of nations 2

interesting to note that most critics of official accounts accept the basicdefinitions of production embodied in the official accounts, and seek in-stead to extend and improve their coverage. Issues of coverage are evi-dently important. But the definition of production is clearly prior, andthis is precisely where we differ from orthodox economists. Thus, whileour own criticism is part of the general chorus, it is quite different in char-acter from most of the others, and has different implications.

The basic problem arises from the fact that conventional accounts clas-sify many activities as "production," when in fact they should be classifiedas forms of social consumption. For example, the military, the police,and private guards protect property and social structure. Civil servantsand lawyers administer rules and laws. Traders in commodities and papercirculate wealth or titles to it. It is our contention that such activities areactually forms of social consumption, not production.

Consider the basic difference between production and consumption.Production activity uses up wealth to create new wealth (i.e., to achieve aproduction outcome). Personal consumption uses up wealth to maintainand reproduce the individual (a nonproduction outcome). In like manner,military, police, administrative, and trading activities use up wealth inthe pursuit of protection, distribution, and administration (also nonpro-duction outcomes). The issue is not one of necessity, because all theseactivities are necessary, in some form or the other, for social reproduction(Beckerman 1968, pp. 27-8). Rather, the issue concerns the nature of theoutcome; protection, distribution, and administration are really formsof social consumption, not production.

At the heart of this discussion is a distinction between outcome andoutput. Not all outcomes are outputs. This is evidently the case with per-sonal consumption, whose outcome is the maintenance of the individual,not the production of new wealth. It is our contention that the samereasoning applies to the other social activities listed.

It should be emphasized that the distinction being made is between pro-duction and nonproduction activities, not between goods and services.We shall see that a substantial portion of service activities (transporta-tion, lodging, entertainment, repairs, etc.) will be classified under produc-tion, whereas others (wholesale/retail, financial services, legal services,advertising, military, civil service, etc.) will be classified as nonproductionactivities. The real distinction is between outcomes and output. All activityresults in outcomes. Some outcomes are also outputs, directly adding tosocial wealth. But others preserve or circulate this wealth, or help main-tain and administer the social structure in which it is embedded. One wayto formalize these distinctions is to imagine a list (a vector) of propertiesassociated with every commodity. Some of these characteristics, to use

Introduction 3

Lancaster's (1968, pp. 113-18) terminology, would be relevant to the com-modity as an object of social use, while others would be relevant to itas an object of ownership. Production would enhance one set, distribu-tion another, and so forth. Needless to say, this extension of Lancaster's"characteristics" approach is different from the conventional neoclassicalone.

Our general approach is rooted in the classical tradition, parts of whichcan be found in Smith, Ricardo, Malthus, Mill, Marx, Sismondi, Bau-drillart, and Chalmers, among others (Studenski 1958, p. 20). Althoughits presentation was incomplete and occasionally inconsistent, it was none-theless part of "the mainstream of economic thought for almost a cen-tury" (Kendrick 1968, p. 20). Only when neoclassical economics rose tothe fore was the classical distinction between production and nonproduc-tion activities displaced by the notion that all socially necessary activities,other than personal consumption, resulted in a product (Bach 1966, p. 45).With this change, lawyers, private guards, and traders of all sorts cameto be counted as adding to national wealth. So too did armies, police,and civil servants.

In his monumental work on the history of national accounts, Studenskihas labeled the above transition as the switch from the "restricted pro-duction" definition of the classicals to the "comprehensive production"definition of the neoclassicals (Studenski 1958, p. 12).1 But from our pointof view, this change is really a retreat from the "comprehensive consump-tion" approach of the classicals (who treat many activities as forms ofsocial consumption, not production) to the "restricted consumption" def-initions of the neoclassicals (who restrict the definition of social consump-tion to personal consumption alone). Under the neoclassical definition,an activity is considered a production activity if it is deemed socially nec-essary. This in turn rests on the conclusion that (at least some) peoplewould be willing to pay for it directly (Bach 1966, p. 45). It follows that,within neoclassical economics, all potentially marketable activities areconsidered to be production activities.2 The ideological convenience of a

1 Studenski's treatment of the classical and Marxian traditions is quite superficial.He is so attached to the neoclassical "utility based" concepts of production thathe is unable to see the fundamental issue at stake in the distinction betweenproduction and nonproduction activities: namely, the difference between totalproduction and total (private and social) consumption (Studenski 1958, pp. 18-22, 24-5).

2 According to the Bureau of Economic Analysis (BEA), "the basic criterion usedfor distinguishing an activity as economic production is whether it is reflected inthe sales and purchase transactions of a market economy" (cited in Eisner 1988,p. 1612). Eisner (pp. 1616-17) proposes to extend this definition of production toencompass all activities that contribute to economic welfare. Of course, within


definition of production which treats all market activities as productive isobvious.

In spite of its other breaks with neoclassical theory, Keynesian eco-nomics did little to change the neoclassical conventions. As a result theyare now embodied in all official national accounts of the Western world(although not without challenge, as we shall see).3

Although the neoclassical concept of production has dominated theofficial accounts of the Western world in the twentieth century, until re-cently quite another concept ruled in (what used to be called) the socialistworld: that of the National Material Product. At the heart of this latterapproach is the idea that production consists of physical goods alone.From this point of view, the value of the total product consists of whatis essentially the final cost of the total physical product: that is, the pricecharged by the producer plus the costs of repair, transportation, and dis-tribution (UN 1991, p. xxii). The originators of this concept claim to de-rive it from Marx, but this physicalist notion of the total product is ac-tually rooted in Smith. It is quite explicitly rejected by Marx, as evenStudenski concedes (Studenski 1958, p. 22).

The undifFerentiated production categories of the neoclassicals and theoverly restricted production concept of the modern physicalists form thetwo poles of official accounting systems (UN 1990, p. vi). But betweenthis Scylla and Charybdis lies another path, one which it is our purposeto develop and apply.

Independent from theoretical and academic discourse is the languageand understanding of practical experience. In this regard, it is quite strik-ing that even though the very concept of nonproduction market activitieshas been abolished from the theoretical lexicon of orthodox economics,the notion continues to thrive in practical discourse. The Prime Ministerof Japan was recently quoted as arguing that American resources were"squandered" on financial and trading activities in the 1980s (Sanger 1992).Fortune magazine reports that "representatives of the manufacturing sec-tor indict the legal and financial sectors as highly unproductive" (Farn-ham 1989, pp. 16, 65; cited by Chernomas 1991, p. 1; emphasis added).Business economists Summers and Summers (1989, p. 270) report that

neoclassical economics, the fundamental test of this status is that someone wouldbe willing to pay for the activity - i.e., that the activity is marketable (Bach 1966,p. 45). Hence only those nonmarket activities that are judged to fail this potentialmarketability test, such as perhaps some portion of government activity, couldbe deemed unnecessary and hence by definition unproductive. Official accountsdo not make such distinctions.

3 Extended accounts that fall within the orthodox economics tradition are dis-cussed in Section 1.3. Those falling within the tradition of Marxian economicsare discussed in Chapter 6.

Introduction 5

"the most frequent complaint about current trends in financial markets isthat so much talented human capital is devoted to trading paper assetsrather than to actually creating wealth'9 (cited in Chernomas 1991, p. 2;emphasis added).

In like vein, Thurow (1980, p. 88) has argued that while "security guardsprotect old goods, [they] do not produce new goods since they add noth-ing to output" (emphasis added), and that military activities are "a formof public consumption" which "use up a lot of human and economic re-sources" (Thurow 1992, p. 20). The New York Times has expressed thesame sentiment, noting that "[s]ecurity people - or guard labor, as someeconomists call them - are proliferating... [in] a nation trying to protectitself from crime and violence." It goes on to quote Harvard Universityeconomist Richard Freeman to the effect that if " 'you go to a sneakeroutlet in a not-so-poor neighborhood in Boston, there will be three pri-vate guards. . . . We are employing many people who are essentially notproducing anything'" (Uchitelle 1989, emphasis added).

The growth of the military and the bureaucracy is endemic in the post-war world, in developed and developing countries alike. Within manyparts of the capitalist world in the 1970s and 1980s, the same was trueof financial and trading activities. At present in the American economy,guard labor is one of the most rapidly growing forms of employment.Within an orthodox national accounts framework, all such activities areviewed as resulting in additional output. But within a classical frame-work, because these same activities are viewed as forms of social con-sumption, their relative growth is seen as serving to absorb an increasedportion of the national product and hence lower the share available forinvestment and accumulation. The difference between the two approacheshas an impact not only on the measures of national production, but alsoon the very understanding of the observed patterns of growth and stag-nation. In a world full of burgeoning militaries, bureaucracies, and salesforces, such matters can assume great significance at the most practicallevel.

As noted previously, conventional national accounts have been criti-cized from a variety of viewpoints in recent years. We share many of theexpressed concerns about the desirability of extending and improving thecoverage of such accounts. But our primary concern is with the very defi-nition of production itself, since this lies at the heart of all systems ofaccounts. In the next two sections, we will briefly trace the history ofnational accounts and outline the basic structure of various alternativesystems of accounts currently under discussion. Section 4 will summarizethe essential differences between our approach and those which fall withinthe tradition of orthodox economics.


1.2 Official national accountsModern systems of national accounts are actually a set of inter-

related accounts that attempt to cover different aspects of the function-ings of market economies. The most fundamental of these are the produc-tion accounts (national-income-and-product and input-output accounts),which attempt to measure the creation and use of new national wealth.These in turn may be supplemented by ones that track financial flows inthe economy (capital and flow-of-funds accounts) or ones that link pro-duction and financial flows to the corresponding stocks (national balancesheets).

At the heart of any set of national accounts lies some common defini-tion of production activities. To construct production accounts, one mustfirst distinguish between production and nonproduction activities, andhence between their corresponding actual or imputed transaction flows.4

All transactions not associated with production activities are excludedfrom the measure of national product. Because orthodox economics de-fines production activities very broadly, its definition of nonproductionactivities is correspondingly narrow - limited to transfer payments (suchas social security, unemployment payments, etc.) and any nonmarket ac-tivities deemed to be socially unnecessary.

Given the actual and imputed transactions that are deemed to corre-spond to some definition of production activities, the next step is to choosea particular measure of production. At the most general level is the totalproduct, which is the sum of all output produced in a given year. Thisis the basic measure used in input-output accounts. It can in turn bedecomposed into two elementary components: the portion which is theequivalent of the inputs used (materials and capital depreciation) in pro-ducing the total product; and the remainder, which is the net product.It is this latter component which is the focus of national-income-and-product accounts.

Since for every receipt there corresponds a payment by someone, thereare two sets of actual or imputed money flows associated with any givenmeasure of national product: production-related receipts of the produc-ers, which are used to measure the money value of output; and associated(nontransfer) payments representing purchases of the product by its var-ious users.5 These are the basic elements of a double-entry production

4 Because national accounts are built around transactions, it is necessary to imputea money value transaction to any production activity (e.g., production in thehome or payments in kind) which is not mediated by actual money flows (Beck-erman 1968, p. 9).

5 Since the object is to measure production, not merely sales, the money revenuesof a unit are supplemented by adding to it the excess of production over sales

Introduction 1

account. Further detail can then be added by subdividing the output sideinto different types of producing sectors and by subdividing the use sideinto different types of users. Individual accounts can then be constructedfor business, household, government, and foreign sectors.

Conventional production accounts come in two basic forms: national-income-and-product accounts (NIPA) and input-output (IO) accounts.Since the former are only concerned with the final use of the product,6

they focus solely on the net product.7 This is split into personal consump-tion, government purchases, private investment, and net exports on theuse side; and wages, profits, and taxes on the revenue side. Input-outputaccounts go one step further, in that they keep track of the whole prod-uct.8 By including the portions of the product used as inputs by variousindustries, they are able to illuminate the structure of interindustrial pro-duction relations in addition to capturing the main aggregates of NIPA.It is because of their greater coverage that we use them as our theoreticalfoil in the development of our own accounting framework.

Both NIPA and IO accounts focus solely on production-related flows.As such, they leave out two important aspects of the overall economicpicture: transactions that are not directly related to production; and stocksof real and financial wealth.

Financial accounts attempt to correct for the first limitation by expand-ing the coverage of financial flows beyond those directly tied to production.

(this item can be negative, of course). To balance the accounts, the same amountis treated as a (positive or negative) payment by the unit to itself, for "unin-tended inventory investment." This is typically merged into gross investmentexpenditures.

6 Because the goal of NIPA is to measure the net product, they must exclude theportion of total product which is the equivalent of inputs used up in the year's pro-duction. To do otherwise would be double counting. But if the goal is to measurethe total product, as is the case with input-output accounts, then obviously itwould be undercounting to ignore input use. There is nothing sacrosanct aboutthe net product as a measure.

7 The proper measure of net product within conventional accounts is net nationalproduct (NNP). But since depreciation measures are frequently unreliable, pro-duction accounts commonly leave depreciation (capital consumption) in the mea-sure of net product (in value added on the revenue side, and in investment on theuse side). This gross-of-depreciation measure of net product is called gross na-tional product (GNP) if it refers to the net production of the nationals of acountry (including those who live abroad), and is called gross domestic product(GDP) if it refers to net production within a nation.

8 It is useful to note that the total product is a more general and useful measurethan the net product. Two nations with the same net product per unit labor canhave different input requirements. Focusing on the net product alone would thenbe quite misleading when considering national productivity, employment andresource use, etc.


Capital finance accounts such as those associated with the United Na-tions System of National Accounts (described hereunder) focus on thesources and uses of funds for capital transactions (transactions whichaffect stocks of financial and real assets). Flow-of-funds (FOF) accounts,which are associated with the U.S. NIPA, track the sources and uses offunds for both capital transactions and current transactions (production-related flows as well as transfer payments) (Ruggles 1987, p. 380). Theyshow the financial interrelationships among economic units, and can beviewed "as a direct extension of [NIPA] . . . into the financial markets"(Ruggles and Ruggles 1982, p. 10).

National balance sheets address the second limitation of productionaccounts by linking flows to changes in stocks.9 This allows one to builda comprehensive picture of national wealth encompassing nonreproduc-ible assets (land, natural resources), reproducible assets (business fixedcapital and inventory stocks, stocks of consumer durables, stocks of mone-tary metals), and net external claims on foreign tangible and financialassets (Goldsmith 1968, p. 52).

To be fully useful, the production, financial, and balance sheet accountsshould be integrated into one another. Although this has not yet beendone for official U.S. accounts, it has been more or less accomplished inthe United Nations System of National Accounts (UN/SNA). For thisreason, and for the sake of comparability with other nations (almost allof whom use the UN/SNA), the United States is expected to change overto the UN/SNA by the mid-1990s (Carson and Honsa 1990, p. 20).

The UN/SNA are more comprehensive than the U.S. accounts, becausethey constitute an integrated system that uses consistent definitions andclassifications to link together NIP and IO national production accounts,financial accounts, and balance sheets. There are also some notable dif-ferences between the classification systems of the two sets of accounts.The UN/SNA focuses on gross domestic product (GDP), not gross na-tional product (GNP). GDP measures net production within a nationwhile GNP measures net production by nationals of a country (includingthose who live abroad), and the differences can be significant for somecountries. The UN/SNA also distinguishes between government consump-tion and investment (the latter being the change in nonmilitary govern-ment equipment and structures). Under discussion are issues concerningthe treatment of research-and-development expenditures and of naturalresources and the environment (see the remarks on Eisner and Repetto inSection 1.3). Revisions of the UN/SNA are currently under way, but sub-stantial changes are not expected (Carson and Honsa 1990, pp. 21-30).

9 For instance, positive net investment adds to the stock of fixed capital, and posi-tive household savings adds to the stock of household financial assets.

Introduction 9

1.3 Extended national accounts for the United StatesAlthough the various official U.S. accounts are not integrated,

much work has been done by individual researchers on linking productionflows with balance-sheet stocks, and on expanding the coverage of pro-duction accounts themselves to encompass both nonmarket and nonlegalactivities. In addition, there has been considerable discussion of a moreadequate treatment of natural resources and environmental issues.

Ruggles and Ruggles (1982, pp. 1, 17) attempt to extend U.S. NIPAby improving their treatment of various individual items and by linkingstocks and flows. In the former domain, they split both household andgovernment expenditures into current and capital components (capitalexpenditures being defined as the net acquisition of durable equipmentand structures), list imputed values in separate accounts, and attempt toallocate transactions in a more accurate way (e.g., owner-occupied hous-ing expenses are allocated to the household sector rather than to unincor-porated business enterprises).10 But their main concern is to integrate stockand flow accounts in such a way as to link up with already existing capitalstock estimates of the Bureau of Economic Analysis (BEA), which arenow broadened to include stocks of household and government durables,and the financial flow-of-funds accounts of the Federal Reserve Board.They end up with larger measures of NNP (net national product) andGNP, because they add in "net imputed income from consumer durables"(which increases both NNP and GNP) and imputed "depreciation allow-ances" on consumer and government durables (which increases GNP).They also obtain a much larger estimate of national savings and invest-ment, because they count changes in the stocks of consumer and gov-ernment durables as part of savings and investment. This is a commonfeature of all extended accounts, as we shall see. Denison (1982, pp. 60,62-3) argues against such procedures, on the grounds that the resultingadjusted measures of GNP, NNP, and national savings are less mean-ingful than the conventional NIPA measures.

There are several other sets of alternate accounts, the most importantof which is from Eisner (1985,1988). In an important article, Eisner (1988)surveys six proposed extensions of NIPA, including his own and that ofRuggles and Ruggles.

Eisner begins by noting how crucial it is to have adequate definitionsof production, primary incomes, intermediate and final output, and in-vestment and consumption. On the issue of production, he proposes ex-tending the definition to cover nonmarket production (e.g. in households)

10 Carson and Jaszi (1982, p. 58) note that Ruggles and Ruggles's definition of thehousehold sector includes soldiers, prisoners, people in sanitariums, etc.


and illegal production (drugs, gambling, prostitution), pointing out thatit would make international comparisons much more meaningful (Eisner1988, pp. 1613-14). On the other hand, he rejects the notion that "leisuretime" be counted as a production activity, even though most other ex-tended accounts do add a very large imputation for the value of leisuretime to their measures of national output. Finally, he points out (p. 1622)that since extensions of the production measure to nonmarket activitiesrequire corresponding imputations on the income side (as the two sidesmust balance), extended accounts tend to give a radically different pic-ture of the distribution of income (real and imputed) between capital andlabor, employed and unemployed, and so forth. For instance, in officialGNP accounts for 1966, the share of labor income is 82.6% and of capi-tal income 24.3%. In the extended accounts of Jorgenson and Fraumeni(1987), because of imputations for the "services" of household durablegoods and for the value of household production and leisure time, thetotal (real and imputed) income of households is raised over fivefold!Thus in the Jorgenson-Fraumeni accounts the labor share appears as 93%and the property share as a mere 7% (Eisner 1988, p. 1672, table S.4).

On the question of investment, Eisner argues in favor of counting thenet changes in consumer and government durables as part of aggregate in-vestment (as do Ruggles and Ruggles). He notes that various researchersalso include in investment one or more of the following: changes in thevalue of land; expenditures for the development and discovery of naturalresources; research and development (R&D) expenditures; and expendi-tures on health, education, training, and information (human capital).As he shows, such adjustments cause enormous changes in the measure ofgross investment and national product. Finally, if one accepts the Haig-Simon-Hicks definition of income as that which can be consumed with-out changing real wealth, then real income, savings, and investment mustall include an adjustment for the net monetary revaluations in stocks.This can add a sharply fluctuating component to the measure of nationalproduct (Eisner 1988, pp. 1622-5).

From our point of view, one of the most intriguing aspects of Eisner'ssurvey is his discussion of the treatment of police, fire protection, guard,and national defense activities. Recall that we classify all such activitiesas nonproduction activities. As such, we would exclude them from thetotal product and hence also from the net product. Eisner argues thatthey should be treated as intermediate inputs rather than final product,citing Kuznets to the effect that such activities constitute "the mere costof maintaining the social fabric, a precondition for net product ratherthan the net product itself" (cited in Eisner 1988, p. 1617; see also Becker-man 1968, pp. 11-12, 23-4, 27-8). This means that they would be countedas production activities and would add to the total product, but would

Introduction 11

not enter into the net product. It is interesting to note that Mage (1963;p. 66) adopts a similar approach.11

We would also view these activities as costs of maintaining the socialfabric. But we treat them as nonproduction activities instead of as inter-mediate inputs into production. How then would one decide between thetwo approaches? To begin with, we note that the normal definition of aninput into production is something that enters directly into the produc-tion process, such as steel into the production of an automobile. In thissense, an activity such as national defense would surely not qualify as aproduction input.

The other possibility is to view national defense as an indirect inputinto the total product, on the grounds that it serves to maintain the socialfabric. But to say that something is an indirect input is only to claim thatit is a necessary part of the overall process of social reproduction: byserving to maintain the social fabric, national defense constitutes whatKuznets calls a "precondition" for other social activities. This does notimply, we would argue, that it is thereby an input into production. First ofall, national defense is just as much a precondition for personal consump-tion as it is for production. To put it the other way, it is just as little aninput into production as it is into personal consumption. Second, oncewe introduce the notion of preconditions, personal consumption is evenmore important than national defense as a precondition of production.12

Is personal consumption then also to be treated as an intermediate inputinto production?13 To answer in the affirmative would vitiate the very dis-tinction between consumption and production. Conversely, if we are tomaintain this distinction then we must be able to say that production andconsumption have different (albeit necessary) outcomes, and that the out-come of consumption is not an output. In this same sense, the outcomeof national defense is not an output either. This is why we argue thatnational defense, like personal consumption, is a nonproduction activ-ity.14 And since, like consumption, it uses up resources in pursuit of anonproduction goal, we label it as a form of social consumption.

In his survey of conventional extended national accounts,15 Eisner exam-ines six alternative systems: those of Nordhaus and Tobin (NT), Zolotas

11 Mage (1963, pp. 61-8) argues that nonproduction activities in general should betreated as part of intermediate input (constant capital in the sense of Marx).

12 Indeed, production is a precondition for personal consumption and nationaldefense.

13 Eisner (1988, p. 1617) expresses uncertainty on just this issue when he asks "Is eat-ing itself intermediate to the creation and maintenance of human capital?"

14 It is worth noting that this debate is not new; Marx (1963, pp. 161,172) remarkson exactly this point.

15 Eisner makes no mention of the national and international Marxian literaturethat we survey in Chapter 6.


(Z), Jorgenson and Fraumeni (JF), Kendricks (K), Ruggles and Ruggles(R), and Eisner (E). The latter two have already been discussed in somedetail. In what follows, we will focus on the major characteristics of thesetypes of accounts.

In principle, orthodox economics defines production activities as allthose that affect the welfare (welfare as utility) of individuals in a na-tion (Kendrick 1968, p. 24).16 In practice, however, official accounts arebuilt largely around market activities, supplemented by imputations forthe "services" furnished by owner-occupied buildings, services furnishedwithout payment by financial intermediaries, and some small imputa-tions for farm products consumed on farms and food furnished to em-ployees, et cetera (Eisner 1988, p. 1620).17 Thus one of the central tasksof conventional extended accounts is to revise and expand the measureof production in a manner consistent with the underlying core of eco-nomic theory (p. 1616).

The differences among the various accounts arise solely from the spe-cifics of this process. In particular, whereas most authors seek to measureproduction in terms of activities that contribute to economic welfare,a few "seek explicitly to measure" welfare itself (Eisner 1988, p. 1627,n. 15). Thus Nordhaus and Tobin, as well as Zolotas, reduce the measureof national product by their estimates of "regrettables and disamenities"(Eisner 1988, p. 1670, table 1).

Certain themes are common to almost all accounts. Most would addthe imputed value of household activities and of illegal market produc-tion to their estimates of the national product, if good data were avail-able (Eisner 1988, p. 1670, table I).18 Our own approach would be similar,

16 Eisner (1988, p. 1617) states that "we are looking for all economic activity relatedto welfare." Tobin remarks that "we do have to admit that there are lots of prob-lems in the utility criterion of welfare that we economists love so well" (cited inEisner 1988, p. 1619, n. 8).

17 Orthodox accounts treat owner-occupied housing as a source of utility-generating"services" whose value is estimated by imputing a rental value to such housing.In 1986, this (fictitious) imputed value is listed as $305 billion. In addition, inorder to treat financial firms in exactly the same way as other "producers" (asopposed to admitting that they are nonproduction firms), it is necessary to createan imputed flow of "services furnished without payment" by them. This amountsto $71 billion in 1986. The implications and alternate treatments of such issuesare discussed in Chapter 3.

18 Ruggles and Ruggles (1982, p. 5) exclude "housewive's services and do-it-yourselfactivities" on the grounds of the difficulty of obtaining "accurate and valid mea-surements." Illegal activities suffer from this problem to an even greater extent.As Carson (1984, p. 33) notes, the relative size of the underground economyvaries considerably across countries, and even within any one country. For theUnited States, for instance, the estimates range from a low of 4% of GNP to ahigh of 34%.

Introduction 13

except that we would distinguish between production and nonproductionactivities, and also between capitalist and noncapitalist activities - just aswe do in the case of legal market activities (see Chapter 2).

A second common characteristic of extended accounts is that they striveto integrate the treatment of sectoral wealth stocks with correspondingproduction-flow accounts. However, in attempting to do this, conventionalaccounts adopt the business sector as their basic model. In business, pur-chases of plant and equipment are capital investments that yield returns(profits) in subsequent years. On the (false) premise that the salient char-acteristic of business fixed capital is its durability,19 extended accountstreat stocks of consumer durables (houses, cars, shoes, clothing, equip-ment, and furnishings) and government durables (building and equip-ment) as household and government "capital," respectively (Eisner 1988,p. 1653). Of course, unlike business capital, there is no actual profit -indeed, no revenue at all - attached. It therefore becomes necessary toimpute a stream of "services" to household and government durables,and add these imputed amounts to the measure of national product.20

Official accounts already carry out such imputations for owner-occupiedhousing, in which private homeowners are treated as unincorporated busi-nesses renting out their homes to themselves for fictitious sums of money(BEA 1980, p. 47). Most extended accounts follow a similar procedurefor so-called intangible capital, cumulating health and education expen-ditures to derive a stock of "human capital" and cumulating business re-search and development to get a stock of business "intangible" capital(Eisner 1988, p. 1670, table S.I). As a corollary, it becomes necessary toshift all household and government expenditures on durables, health, andeducation from the category of current expenditures to a newly createdcategory of capital "investment" expenditures.

As far as we are concerned, the conventional treatment conflates twodistinct issues. On one hand, they are quite right to stress the importanceof keeping track of the stocks of household and consumer wealth, andof integrating the formation of these stocks into corresponding flows ofrevenue. On the other hand, we would argue that it is wrong to treatmere durable goods as if they were equivalent to business capital, andeven worse to impute fictitious profits to such goods. The capital stockof a business is part of a profit-making venture, and comprises not only

19 The reduction of the concept of capital to a merely durable good obscures the dif-ference between a capital good and a consumption good. It is also inadequate asa description of capital itself, since profit in no way depends on the durability ofan investment (huge profits are routinely made on short-term financial capital).

20 Gross imputed services of household and government durable goods are calcu-lated as imputed depreciation on the stock of these goods, plus a gross imputedreturn on these same stocks (Eisner 1988, p. 1626).


durable items (plant, equipment, and durable financial assets) but alsonondurable items (inventories of materials and work in progress as wellas short-term financial assets). It is because money is tied up as capital -be it in the form of durable goods or short-term financial assets - thatthe possibility of profit arises. The substantial profits made in speculationand trade make it clear that the durability of the investment is a com-pletely secondary matter.

The goods of a household, both durable and nondurable, are part ofthe consumption circuit; those of the government are part of social ad-ministration. To reduce business, household, and government stocks tomere durable goods is to negate the differences between capitalist enter-prise, personal consumption, and social administration.21 To impute fic-titious gross profits to the latter two only compounds the problem. In asimilar vein, while it is perfectly proper to assess the skill and knowledgeof the population, and perhaps even to cumulate the total cost of acquir-ing these attributes, it is not appropriate to treat the resulting measure ofimbedded cost as yet another stock of "capital."

Business R&D expenses and exploration costs are a different matter;they are a part of the circuit of capital. The question here is whether theyshould be reclassified as fixed investment expenditures (rather than currentcosts or circulating investment), and then cumulated to form some stockof intangible business capital. In this regard, it is useful to note that R&Dand similar expenses are, after all, exploratory expenditures which may ormay not bear fruit. By treating them as current costs, businesses alreadytake account of the expense when it is incurred. And if they do bear fruitat some time in the future, the resulting capital investment is counted whenit is made, as are any associated profits if they in turn appear. An artifi-cially constructed stock of intangible R&D capital is therefore redundant.

Eisner lists several other major modifications specific to particular au-thors. A significant number (NT, Z, JF, K) expand their measures of totaloutput by a large amount representing the estimated output of leisuretime; since leisure contributes to utility, it is appropriate within neoclassi-cal economics to view it as a production activity (Eisner 1988, p. 1626).22

21 It is interesting to note that even though many other countries count some partof government durables as a stock of capital, military durables are specificallyexcluded (Ruggles and Ruggles 1982, p. 12). Thus durability per se is evidentlynot sufficient as a definition of capital.

22 Relative to the official BE A measure of GNP, the estimated additional productattributed to leisure time is very large: 48.7% for Z in 1965 (Eisner 1988, p. 1636,table Z.I), 96.6% for K in 1984 (p. 1646, table K.6), 101.5% for NT (p. 1632,table NT.2), and 115.5% for JF in 1982 (p. 1638, table JF.l, which shows $4,200.7billion for the JF estimate of the 1982 value of total time spent in household pro-duction and leisure, from which the leisure component can be estimated usingthe Kendrick estimates of the two components in Eisner 1988, p. 1646, table K.6).

Introduction 15

A number of authors (JF, R, E) also add a large and volatile componentrepresenting the effects of price changes on the value of household, govern-ment, and business stocks of wealth, on the grounds that the appropriate"Haig-Hicks-Simon concept of income [is] that which can be consumedwhile keeping real wealth intact" (p. 1624). Eisner argues in favor of thisprocedure, even though it entails "a significant conceptual departure fromconventional accounts, which focus on the direct output of current pro-ductive activity," and even though it creates a large component that ex-hibits "some sharp year-to-year variations" (p. 1625). Scott (1990, p. 1175)argues against this procedure on both theoretical and practical grounds,noting in passing that if revaluations were counted as part of income andoutput flows then one would have to conclude "that the U.S. nationalincome was negative during October 1987" (the month of the stock mar-ket crash). Finally, as we have already noted, some authors (NT, Z, E)shift police, fire protection, defense, and guard activities from the finalproduct to intermediate input; NT directly subtract other "regrettablesand disamenities."23 Both procedures serve to lower the measure of finalproduct.

Figure 1.1 presents the various estimates of gross final product whichflow from the six conventional extended accounts, relative to the officialBEA measure of GNP, as summarized by Eisner (1988, p. 1673, tableS.5) for the mid-1960s. Also included are our own estimates, as developedin subsequent chapters of this book.

Two things are notable in Figure 1.1. First, all the estimates, includingour own (ST), are larger than the official measure of GNP. In the case ofthe six conventional extended accounts, this is due to the fact that virtu-ally all authors include estimates of the value of housework and of the"services" of household and government durable goods, and that mostalso include quite large estimates for the value of leisure. As for our ownestimates, we find that our basic estimate of market production is smallerthan GNP. But when we supplement this with Eisner's estimate of house-work, in order to make the coverage somewhat similar to that of otherextended accounts,24 the resulting figure is about 21% larger than GNP.

The second striking feature of the estimates in Figure 1.1 is their greatrange of variation: from a low of 112% of the official measure of GNP(Ruggles and Ruggles) to a high of 468% (Jorgenson and Fraumeni). In

23 Regrettables include the previously discussed items of national defense, police,etc., as well as costs of commuting to work and road maintenance, all on thegrounds that these are instrumental expenditures that do not directly enter util-ity but are (regrettably) necessary for activities which do. Disamenities representcosts of pollution, litter, congestion, noise, etc. (Eisner 1988, pp. 1627-8).

24 We have already argued against the notion of adding the "services" of durablesor the value of leisure time to the measure of the product.


Figure 1.1. Alternate measures of GFP. Key: NT = Nordhaus and Tobinfor 1965; Z = Zolotas for 1965; JF = Jorgenson and Fraumeni for 1966;K = Kendrick for 1966; R = Ruggles and Ruggles for 1969; E = Eisner for1966; ST = Shaikh and Tonak for 1966. The ST estimate is from Table5.4, supplemented by the addition of Eisner's (1985, p. 36) estimate ofthe value of housework ($267.9 billion in 1966). Source: Eisner (1988,p. 1638, table S.5).

the JF case, this is almost entirely due to a particularly large estimate ofthe value of leisure, and to a huge addition for investment in human capi-tal (Eisner 1988, p. 1638, table JF.l).25

Many of these account extensions involve significant changes in the com-ponents of the production accounts (Eisner 1988, p. 1626). For instance,the treatment of expenditures on household durables as investment in-volves shifting their purchases from consumption to (household) invest-ment. Similar effects obtain for government purchases on durables, andfor expenditures on health and education (investment in human capital).The net result is to radically alter the size, ratios, and even the meaningsof categories such as consumption and investment.

Environmental and resource issues are much less discussed in these ex-tended accounts (Ruggles and Ruggles 1982, p. 5; Eisner 1988, pp. 1622-

25 JF's estimate of the value of housework and leisure is itself almost V/i timesas large as official GNP, while their measure of investment in human capital isalmost 3 times as large as GNP and almost WA times as large as the official mea-sure of gross private domestic investment (Eisner 1988, pp. 1637-8, table JF.l).

Introduction 17

3). It is well known that official conventions can lead to very inconsistentresults. The degradation of the environment is not counted as reductionin income or wealth. If industry cleans up its own mess, the expenditure iscounted as an intermediate input and hence output is not affected. But ifgovernment cleans it up, this expands the measure of net output becausegovernment expenditures are considered to be purchases of final goodsand services. Finally, if households incur medical expenses as a conse-quence of environmental problems, their expenditures raise the measureof consumption and hence of the final product (Repetto et al. 1989, p. 16).

Although such issues are beyond the scope of the present book, it isinteresting to note that within our accounting schema the above anomalieswould not appear. Neither the cleanup expenditures by industry or gov-ernment, nor the medical expenditures by consumers, would be countedas production activities. Indeed, like all nonproduction activities, theywould use up resources in responding to the environmental problem. Asfor the environmental degradation itself, this could be counted as a re-duction in the stock of (environmental) wealth.

In any case, there exists no consensus on the appropriate treatment ofenvironmental issues within any system of accounts.26 But it is possibleto address the somewhat more manageable issue of resource depletion.Eisner (1988, pp. 1622-3) suggests that the improvement or exhaustion ofnatural resources be treated on a par with any other investment. Economicactivity that increases the value of land or natural resources would becounted as investment, and activity that exhausts them would be countedas depreciation. Repetto et al. (1989, pp. 22-4) propose a similar scheme,in which the change in the physical stock of resources, valued at averageprices over the period, is added to net national product (as net investmentor disinvestment). Such a procedure would reduce the measured net na-tional product when income is derived essentially from the depletion ofresources.27

1.4 Toward an alternate approach to national accountsIn spite of the complexity and sophistication of the various ex-

tended accounts surveyed here, it is important to note that they all share

26 Of the six extended accounts surveyed, only Nordhaus and Tobin attempt toaddress this issue directly, in the form of their deduction for "regrettables anddisamenities." But this is a rather ad hoc treatment, and as Eisner (1988, p. 1627,n. 15) points out, it crosses over the line between the measurement of production(creation of objects of utility) and utility or disutility itself.

27 Unlike Eisner, Repetto et al. (1989, pp. 23-4) would not count the monetary reval-uation (the change in the monetary value of a given physical stock) in the measureof income and product.


certain critical characteristics. First, they are intended to be extensions,not alternatives, to the conventional accounts that form their core (Eisner1988, p. 1616). Second, like the conventional accounts around which theyare built, the "theoretical constructs they are presumed to serve" (p. 1612;Repetto 1989, p. v) are those of neoclassical economics. Third, at thecore of all national accounts lie the production accounts (Carson andHonsa 1990, pp. 28-9). Fourth, the neoclassical concept of productionembodied in conventional production accounts is a very elastic one, en-compassing not only all results of potentially marketable human labor,but also the "services" of durable goods and even the "benefits" of leisuretime. At the other extreme we find the restricted concept of productionembodied in the National Material Product system of the formerly so-cialist bloc. Here, the core accounts are focused on the production anddistribution of physical goods.

The system we develop falls between these two polar extremes. On onehand, our production encompasses both goods and services. Indeed, thevast bulk of the traditionally defined service sector falls within our defini-tion of production activities. On the other hand, we do not identify allactivities as production: trading, military, police, and administrative ac-tivities are treated as forms of social consumption, not production. Atthe heart of the matter is a distinction between outcomes and outputs.The outcomes of nonproduction activities may be socially desirable re-sults, but they are not outputs.

Our system has its roots in the classical tradition. The classical econo-mists were deeply concerned with the factors that regulate the growth ofthe wealth of nations. Once it was recognized that some activities wereactually forms of social consumption, not production, two crucial impli-cations followed. First, an increase in employment need not signal anincrease in production; on the contrary, it might signify an increase insocial consumption. Second, an increase in the share of social consump-tion in net output is a decrease in the social savings rate, and this tends toreduce the rate of growth of the system (see Chapter I).7*

28 If we write net output as Y = C'+1, where C'= personal and social consumptionand I = net investment, then the social savings rate is s'= ( Y - C ' ) / Y = 1 -C' /Y.An increase in the relative share of social consumption is then a decrease in thesocial savings rate, and hence a direct reduction in the Harrodian warranted rateof growth g* = sVv, where v = the ratio of capital to normal capacity output. Ina depressive situation in which the actual growth rate is below the warrantedrate, the two might move in opposite directions. In normal growth, however, theactual growth rate will fluctuate around the warranted rate (i.e., capacity utiliza-tion will fluctuate around normal levels), so that a decrease in the social savingsrate will lower the latter by lowering the former. See Chapter 7 for further analy-sis and data.

Introduction 19

From this perspective, a deficit-financed increase in (say) military ex-penditures may indeed stimulate an increase in aggregate demand, out-put, and employment in the short run. But, insofar as it expands the shareof social consumption, it will tend to reduce the rate of growth of thesystem. The short-run gain will therefore be achieved at the expense of along-run loss that will eventually outweigh it.29

The location of the dividing line between production and nonproductionactivities has other implications as well. We will find that it changes thevery measures of net product, surplus product, consumption, investment,and productivity. The observed trends of these and many other criticalvariables are also quite different from those in conventional accounts.As a result, one may achieve a very different understanding about theprogress of the U. S. economy and the determinants of its postwar growth.

29 The short-run stimulatory effect may, in the Keynesian sense, raise the level ofoutput. But the decline in the propensity to save will reduce the rate of growth,and eventually the new level of output will be lower than what it would havebeen at the old rate of growth. See Chapter 7 for further details.

Basic theoretical foundations

2.1 The distinction between production andnonproduction activitiesMarxist national accounts depend crucially on the distinction be-

tween labor which is productive of capital and that which is not. Becausethis distinction is so often presented in a confused and contradictory man-ner, we will not begin from it. Instead, this section will focus on the priorand more general distinction between production and nonproduction ac-tivities. The next section will then develop this into more concrete distinc-tions between labors which are and are not productive of capital. As weshall see, our derivation will enable us to arrive at a definition that corre-sponds exactly to the one Marx uses. Deriving the definition from firstprinciples, rather than simply beginning with it, allows us to endow itwith considerably greater depth.

2.1.1 Mistaken conceptions of the distinctionIt is useful to begin by emphasizing what the distinction between

production and nonproduction labor does not refer to. In the first place, itis not a distinction between necessary and unnecessary activities. We intendno connotation that production activities are either more (or less) necessarythan nonproduction activities. The dividing line does not rest on eithertechnical or social standards of efficiency, though of course such stan-dards may well be applied to either set of activities. Baran and Sweezy'sargument that some labor under capitalism would be unnecessary in a"rationally ordered" (i.e. socialist) economy (Baran 1957, p. 32) is onesuch efficiency approach. But it is easy to show that they draw the dis-tinction between "productive" and "unproductive" labor in ways that arequite different from those in Marx (Hunt 1979, pp. 304-8), and certainlyfrom those which we will develop.

20

Basic theoretical foundations 21

Second, we are not attempting to demarcate between "good" and "bad"activities. One might well argue that certain activities (e.g. nuclear weaponsproduction) are dangerous and destructive and thus bad, or that muchof advertising is manipulative and dishonest. These would be moral cri-tiques. But such labels are clearly applicable to both production activi-ties (nuclear weapons) and nonproduction activities (advertising). Theproduction-nonproduction distinction is independent of our evaluationof their social merit.

Third, we are not attempting to construct a political distinction, becauseproduction labor is not a designation for the working class, nor nonpro-duction labor one for the petty bourgeoisie, as Poulantzsas (1975) wouldhave it.1 Finally, we will not equate production activities with "physicalgoods" nor nonproduction activities with "services." Such a conflationhas its origins in the fact that the classical economists adopt it on practicalgrounds.2 Marx certainly rejects any such association at the theoreticallevel, and explicitly criticizes Adam Smith for confusing the "material-ization" of labor in a use value with its embodiment in a physical good(Marx 1963, pp. 171-2).

In sum, the distinction we seek has nothing to do with the efficiency,morality, physicality, or politics of the activities involved. With this inmind, we can turn to the argument itself.

2.1.2 Basic activities of social reproductionIn analyzing the overall process of social reproduction, we can

distinguish four major types of social activities:production, in which the various objects of social use (use val-

ues) are utilized in the process of the creation of new suchobjects;

distribution, in which various objects of social use are utilized inorder to transfer such objects from their immediate possessorsto those who intend to use them;

social maintenance and reproduction, in v/hich use values areused up in the private and public administration, maintenance,

1 According to Poulantzas (1975, pp. 20, 212, 216, 221), not only all unproductivelaborers but also some productive laborers are new petty bourgeois. Wright(1978) provides an effective critique of this position.

2 Smith associates productive labor with a physical "vendible commodity." Ri-cardo (1951, p. 13) refers to Malthus's argument that the most practical distinc-tion is the one that "separates material from immaterial objects," which in turnimplies that productive labor - i.e., labor productive of wealth - is that laborwhich produces material objects (p. 23). Malthus feels this to be the most useful,if not most subtle, classification (Ricardo 1951, p. 23), and Ricardo concurs(p. 15).


Figure 2.1. Production and nonproduction labor.

and reproduction of the social order by the government, thelegal system, the military, corporate security personnel, etc.;and

personal consumption, in which the objects of social use areconsumed directly by individual consumers.

Of these types of activities, only the first three qualify as labor (sincepersonal consumption is not labor). But since only the first activity consti-tutes production, it follows that labor is not synonymous with production.We must distinguish, in other words, between production labor and non-production (distribution and social maintenance) labor. See Figure 2.1.

2.1.3 Production, distribution, and social maintenanceFrom the most general point of view, the process of production

involves the creation or transformation of objects of social use by meansof purposeful human activity (Marx 1977, p. 183). This definition is de-ceptively simple; it appears easy to grasp when we conceive of a usefulobject as a physical object. But in fact the definition of an object of socialuse is more general than that. Broadly speaking, it is a material thing oreffect, some of whose properties satisfy human wants.3 It makes no dif-ference, as Marx puts it, whether these wants "spring from stomach orfancy" (Marx 1967a, p. 35), or whether they are satisfied directly by theconsumption of this object or indirectly through its use in social repro-duction (e.g., distribution or maintenance of the social order).

What we have been calling an object of social use is what Marx calls ause value: a material thing or effect, some of whose objective (i.e. space-

3 The concrete expressions of human wants are, of course, largely socially de-termined.


time) properties make it an object of social use. As such, these usefulobjective material properties are quite distinct from the satisfaction wemay or may not derive from its actual use.

Let us consider various such objects. In a factory, a set of workers pro-duces a car. This car has objective material properties - shape, color,engine displacement, etc. - which make it an object of our consumption.These properties are the car's useful objective characteristics and serveas the material basis for the subjective satisfaction we may derive fromthe car, but they are clearly distinct from this satisfaction itself.

Now consider the case of so-called services. A barber uses scissors totransform the shape of someone's hair, thus producing a material effectwhich is the object of the customer's personal consumption, an effectwhose useful objective properties are evident in the mirror, to the touch,and even in a photograph. Similarly, a singer who projects a song intothe air produces an object of consumption so material that it can be cap-tured on a record and reproduced electronically. In both cases, the usefulobjective material properties of this song are very different from the satis-faction one may or may not derive from them (Marx 1963, p. 157).

Even transportation can result in the creation of a use value. Broadlyspeaking, transportation consists of passenger transport and commoditytransport. Each of these encompasses both production and nonproduc-tion activities, depending on more specific considerations. For instance,planes or trains taken as part of vacations and visits bring about a desiredchange of location which is a direct element of overall consumption. Thusconsumption-related passenger transport is part of the production ser-vices that enter directly into consumption. Similarly, by shipping orangesfrom their point of production to their point of consumption, a truckertransforms a useful objective property of these oranges (their location inspace) which is crucial to them as objects of consumption. To be con-sumed, an orange must not merely be an orange somewhere, it must bean orange where the consumer is. Transportation from the orange groveto the consumption region is therefore productive transportation, a com-pletion of the process of the creation of an object of consumption - thatis, a completion of the process of production. It is internal to the processof production.4

It is important to understand that not all transportation constitutesproduction activity. Some part of commodity transport may be internalto the distribution process itself. Suppose our oranges are produced inCalifornia to be sold in New York, but are stored in New Jersey becauseof cheaper warehouse facilities. As already noted, the transport from

4 This is precisely why Marx counts transportation as part of the production pro-cess (Marx 1%3, pp. 152, 412).


California to New York is the productive leg of the journey, because itchanges the objective useful properties of the orange. The loop throughNew Jersey has no (positive) effect on the useful properties of the orangeas an object of consumption,5 but it does improve those properties whichaffect the orange as an object of distribution. As such, this loop is internalto the distribution system. It therefore constitutes distributive transportof commodities, a nonproduction activity. A similar argument can bemade for business-related transport of salespeople, which would be dis-tributive transport of passengers.

In the case of production activities, the labor involved is productionlabor, which utilizes certain use values in the creation of new use values.As products of this labor, these new use values are quite distinct fromeither the labor or the materials that went into their own production: asong is not the singer, nor merely the medium of air; cut and shaped hairis neither barber nor scissors, nor uncut hair; an orange in New York isobjectively different, as a New Yorker's object of consumption, from theorange that began its journey in California.

It should be evident that the definition of a use value has nothing to dowith the conventional distinction between goods and services. Indeed, aswe shall see, the very term "services" conflates a vital distinction betweenproduction and nonproduction labor. The preceding discussion also allowsus to clarify a point of confusion in the literature concerning the differ-ence between the production of a use value and its subsequent use. Webegin by considering the various alternative uses of some given set of usevalues which have just emerged from a production process.

In the first place, use values may re-enter into another production pro-cess as material inputs. A truck may be used in transportation, an orangemay be used in making food, a coiffure may be part of the performanceof a song. In all these cases, they are used up as part of a new productionprocess involving fresh production labor and resulting in new use values.The original use values are destroyed (they are productively consumed,in Marx's terminology), but in the process new wealth is created. At theother extreme, the original use values may enter directly into personalconsumption, in which case they are used up in the process of reproduc-ing the consumers themselves; they are individually consumed.

Whether an orange is re-used in the further production of food or con-sumed directly, it must first be produced as an orange. This means that,regardless of the further use to which the orange is put, the labor whichoriginally produced it remains production labor. If it is re-used in further

5 To the extent that oranges deteriorate over time, the additional time involved ina distribution loop may actually degrade their useful characteristics.


production, then new production labor must be performed to transformit into a new use value (such as orange juice). On the other hand, if it isconsumed then consumption activity (though not labor) is required. Ineither case, the original labor remains what it was, since its status is notdetermined by the use to which the fruits of this labor, so to speak, areput.6

A second important point can be made even at this level. All economictheory distinguishes between production and consumption, and recog-nizes that only production results in the creation of new use values or (asclassical economists put it) in the creation of new wealth of nations. Evenneoclassical economics distinguishes between the production that createsobjects of utility (the arguments of utility functions) and the personalconsumption that realizes the potential utility of these objects. Thus alleconomic theory contains an elementary distinction between productionand nonproduction activities. What distinguishes the classical/Marxiantradition from the neoclassical/Keynesian one is the location of the di-viding line. The former places distribution and social maintenance activ-ities in the sphere of nonproduction activities, whereas the latter placesthem in production.7

The dividing line between production and personal consumption ac-tivities is at the same time a dividing line between labor and nonlaboractivities. But it was precisely this latter division which the classical econ-omists felt to be inadequate, because it was their contention that not alllabor resulted in the creation of new wealth. It was therefore necessaryfor them to distinguish not merely between production and nonproduc-tion activity, but also between production and nonproduction labor - inother words, between what they called "productive" and "unproductive"labor.

It must be emphasized once again that the classical distinction betweenproduction and nonproduction labor is essentially analytical. It is foundedon the insight that certain types of labor share a common property withthe activity of consumption - namely, that in their performance they useup a portion of existing wealth without directly resulting in the creationof new wealth. To say that these labors indirectly result in the creationof this wealth is only another way of saying that they are necessary. Con-sumption also indirectly results in production, as production indirectlyresults in consumption. But this hardly obviates the need for distinguish-ing between the two.

6 This speaks to a certain strand in the literature which conflates the production ofa use value with its subsequent use. See, for example, O'Connor (1975).

7 Neoclassical and Keynesian approaches will be discussed in Section 2.3.


We have already seen that, at one extreme, use values emerging from aprocess of production may be productively consumed (re-entering intoanother production process as its material inputs); at the other extreme,they may be personally consumed. What we need to examine now is theiruse in distribution or in maintenance of the social order.

In order to forestall any possible confusion, we should note that weuse the term "distribution" to cover only those activities (not necessarilyfirms) which transfer the use values, titles, or money from one set of indi-viduals to another. We have already argued, for instance, that transpor-tation can be either productive or distributive, depending on its context.8

By the same token, a particular firm may encompass both distributionactivities and production activities (as in the example of advertising thatfollows).

Generally speaking, distribution involves the utilization of some usevalues as material inputs in a process that transfers the ownership of(other) use values from their immediate possessors to those who finallyintend to use them. As such, the labor involved in this process bringsabout the circulation or distribution of pre-existing use values by chang-ing their possession. Thus, although distribution activity does transformthe use values it circulates, this transformation relates to their propertiesas objects of possession and appropriation, not to the properties whichdefine them as objects of social use. A cashier who charges you money isperforming a very different activity from the singer who sings the song.The latter activity results in the use value itself, while the former circulatestitles to it. A song heard for free is all the more sweet to the listener. Butthen, of course, the seller hears a different tune altogether.

Advertising and sales activities have the same character, because theiraim is to change not the use value itself but rather the knowledge of, anddesire for, this use value. They therefore attempt to locate, enhance, andcreate the effective demand for this use value so as to transfer title to(sell) it on as profitable terms as they can.9 This in no way precludes

8 Insofar as transportation completes the creation of a use value, such as in thecase of the shipping of fruit from its place of production to where the consumeris, then it is productive transportation. But transportation can also be whollyinternal to the distributive process, when for example supplies are shipped backand forth between warehouses and retail outlets. In this case, the transportationinvolved is distributive transportation.

9 Advertising and sales activity should not be confused with television or radio,which are the media for these activities, just as they function as media for theproduction of use values in the form of the TV or radio shows themselves. Thelabor that produces such media is production labor. The labor that uses mediais production labor (e.g. entertainment) or distribution labor (e.g. advertising),depending on the type of activity in which the labor is involved.


an advertising firm from encompassing production activities such as theproduction of a commercial. Similarly, since money is the means of cir-culation, all money-dealing activities also fall into the category of distri-bution labor. As we have already noted, none of this implies that distri-bution labor is in any way inferior (or superior) to production labor; itonly implies that the two are distinct.10

Finally, we have all those activities that revolve around the mainte-nance and reproduction of the social order. Police, fire departments,courts, and prisons involve the protection of persons, property, and thesocial relations that surround them. National defense and internationalaffairs do much the same, only on a world scale. General government activ-ities (such as those involving administration, public assistance, pensions,social security, etc.) fall into the same category. But not all such activitiesare performed in the public sphere. Corporate security personnel and pri-vate guards protect persons and their private property. In each case, usevalues enter as material inputs into activities designed to protect, main-tain, administer, and reproduce the social order, and as such they arequite distinct from production labor.

The fact that most of the activities just mentioned are performed bythe state should not mislead us into conflating social maintenance andreproduction activities with state activities. Corporate security is a privateactivity. On the other hand, government-owned electric power plants arepart of production, while government agencies that buy and sell grain areengaging in distribution activities. All labor activities can have privateand public components.

In the same way, individual people or firms can also encompass morethan one type of activity. A manufacturing firm, for instance, will encom-pass both production and distribution (sales, credit, advertising) activi-ties. Similarly, a given person such as a butcher may both cut meat to acustomer's specification and also ring up the purchase. The boundarybetween production and distribution is in this case crossed by the sameperson. Nonetheless, the boundary remains a very real one. Should thebutcher be so fortunate as to expand into a capitalist enterprise of sufficientscale, then butchers and cashiers will perform different tasks altogether.11

10 As noted in Chapter 1, one could formalize this argument in terms of Lancas-ter's notion of commodities as characteristics (Lancaster 1968, pp. 113-8). Ofcourse, our treatment would nonetheless differ from a neoclassical one (see Sec-tion 2.3).

11 Because all circuits of capital begin and end with money, every firm must engagein at least some distribution activity. We are of course unable to separate em-pirically the production and distribution components of any single person's ac-tivities. But we can (approximately) separate out production and nonproduc-tion workers within each firm or industry. This latter division is by far the most


2.1.4 Personal and social consumptionWe have emphasized that production, distribution, maintenance

of the social order, and personal consumption are all part and parcel ofthe process of social reproduction. The distinctions between them havenothing to do with one being intrinsically more necessary than the others.12

Each type of activity uses up use values as material inputs in order toarrive at its own distinctive outcomes. But only the first activity directlyresults in the creation of new wealth and hence in a net product over andabove what it uses up. The other three facilitate, respectively, the socialtransfer of this new wealth, the maintenance and reproduction of thesocial conditions of existence, and the maintenance and reproduction ofindividuals in the society.13

Of the three nonproduction activities, the first two (distribution andsocial maintenance) involve the performance of labor, while the third(personal consumption) does not.14 Nonetheless, they have in commonthe property that they all use up use values in their performance with-out themselves directly resulting in the creation of new wealth. As such,they must necessarily be supported by existing physical or nonphysicalwealth. They are, in other words, similar to personal consumption itselfin that their net effect is to consume a portion of the net social product:nonproduction labor is a form of social consumption. This is preciselywhy classical economists insisted on distinguishing between production("productive") labor and nonproduction ("unproductive") labor. See Fig-ure 2.2.

important, precisely because capitalist production tends to confine individualworkers to distinct activities.

12 The fact that social reproduction requires all four activities in one form or an-other need not prevent us from arguing that one existing form is wasteful, dan-gerous, etc. Thus one could argue, as many radicals do, that some productionactivities (nuclear weapons), some distribution activities (false and misleadingadvertising) and some social maintenance activities (subsidies to corporate agri-business) are undesirable. This superimposes the distinction between desirableand undesirable upon the four analytical categories we have defined, therebyadding another dimension to the analysis.

13 To say that the latter three "indirectly" result in production is only to say thatthey are necessary for social reproduction. Thus, consumption indirectly resultsin production because it reproduces the producers themselves. Conversely, pro-duction indirectly results in consumption insofar as it produces the articles ofpresent consumption or the means of future consumption. The concept of indi-rect production therefore tells us nothing new.

14 Household labor should not be confused with consumption activity. Activitiessuch as cooking and cleaning are production labor. Consumption activity is quitedistinct from this.


Production Labor -* Nonproduction Labor

i Total Labor — — — — —

Figure 2.2. Nonproduction labor and social consumption.

2.2 Productive labor under capitalismThe preceding definitions of production and nonproduction labor

are perfectly general. However, they take on additional content when theyare considered in relation to specific social relations under which theymight be conducted. Broadly speaking, labor might be conducted fordirect use, for sale for income, and for sale for profit. Each of these repre-sents a distinct social relation under which any given labor process is or-ganized and developed. Only the last represents capitalistically employedlabor, in which capitalists advance capital value as wages in order to pur-chase and utilize labor power for a specified period. It follows from thisthat capitalistically employed labor is not only wage labor but also wagelabor whose labor-power is first exchanged against capital (Marx 1977,p. 477). This covers not only production labor but also distribution andsocial maintenance labors, insofar as they are capitalistically organized.

Now consider each of these activities in turn. All types of productioncreate use values. Insofar as production is organized for direct use, as inhousehold or community production, it produces use values alone. Onthe other hand, insofar as it is organized for sale for revenue (income),as in petty commodity production, it produces use values that are simul-taneously values (materializations of abstract labor time). Finally, insofaras production is for sale for profit, it represents capitalist commodityproduction that produces not only use values and values but also surplusvalue. This last category is represented by the unshaded sections in Figure2.3. It represents capitalistically employed labor which is also produc-tion labor.


Production Distribution Social Maintenance

Figure 2.3. Productive and unproductive labor under capital.

The identification of that labor which produces surplus value - in otherwords, that labor which is productive of capital - immediately allows usto specify its two salient properties:

(a) it is wage labor which is first exchanged against capital (i.e., it iscapitalistically employed);

(b) it is labor which creates or transforms use values (i.e., it is pro-duction labor).

The definition derived here is identical to the one Marx (1977, p. 644)uses to characterize productive labor. All other labor is thereby unpro-ductive of capital, either because it is production labor that producesdirect use values or commodities but not capital, or because it is non-production labor. Thus even capitalistically employed wage labor can beunproductive of capital if it is distribution or social maintenance labor(Marx 1977, p. 1042). It is surprising how often this basic point has beenmisunderstood in the literature.15

The fact that all labor other than capitalistically employed productionlabor is unproductive of capital does not in any way negate the specificityof the individual components of this labor. Petty commodity productionand household labors have very different effects on capitalist reproduction,even though they both produce use values. For instance, suppose that -at a particular stage in economic development - half of the standard ofliving of the working class is supported out of the use values produced by(unpaid) household labor, and the other half by commodities purchasedwith the wages of employed workers. If over time the directly produceduse values were gradually replaced by the products of petty commodityproduction, then in order to maintain the same standard of living the pur-chasing power of workers would have to rise to double its initial level,other things being equal. Thus a given standard of living could correspond

15 See Gough (1972). Even Hunt's careful tracing of Marx's argument stumbles overthis issue (Hunt 1979, pp. 313-15).


to very different values of labor power, and hence rates of surplus value,depending on the proportion in which the products of the two types ofunproductive labors enter the standard of living. The rate of surplus valuedepends only on the length of the working day and the unit value of laborpower in either case, other things being equal. But this unit value of laborpower is not independent of the conditions under which noncapitalist (i.e.unproductive) production labors are performed. These considerations areespecially important in the context of the Third World.

In a similar way, even though both salespeople and (say) military peo-ple are primarily nonproduction personnel, they do not have the sameimpact on reproduction. Suppose that the amount of value and surplusvalue is given, that new sales employment is financed out of current profits,and that new military expenditures are financed directly out of taxes onwages. An increase in sales employment diminishes the amount of surplusvalue left for aggregate profit (though it may well transfer more surplusvalue to the firms that increase their sales force). Aggregate profits there-fore decline, other things being equal. On the other hand, an increasedmilitary employment financed out of taxes on wages need not alter aggre-gate profit.16 In both cases, the mass and rate of surplus value are un-altered, but aggregate profit is altered in one case and not the other - eventhough both types of labor involved are unproductive labor from thestandpoint of capital.

It is important to note that all capitalistically employed labor is ex-ploited by capital, whether it is productive labor or unproductive labor.The rate of exploitation of each is their respective ratio of surplus labortime to necessary labor time. Necessary labor time is simply the value ofthe labor power involved, that is, the labor value of the average annualconsumption per worker in the activities in question. Surplus labor timeis excess of working time over necessary labor time. In the case of pro-ductive workers, their rate of exploitation is also the rate of surplus value,since their surplus labor time results in surplus value. This concept is sopractical that we can use it to calculate the separate rates of exploitationof productive and unproductive workers (see Sections 4.2 and 5.6).

The illustrations in this section were designed to emphasize the point thatthe distinction between productive and unproductive labor is necessary, butnot sufficient, for the analysis of reproduction. We need also to know thespecific components of unproductive labor and their interaction with thecircuits of capital and revenue. This is precisely why we began our analy-sis with the general distinction between production, distribution, social

16 The decreased consumption of taxed workers is assumed to be compensated forby the increased consumption of military employees, so that aggregate demandis unchanged.


maintenance, and personal consumption activities, rather than merelybeginning with Marx's definition of productive labor.

2.3 Productive labor in orthodox economicsProduction, distribution, social maintenance, and personal con-

sumption are all necessary links in the social reproductive process. Buttheir common necessity does not imply similar effects. Indeed, all eco-nomic theories recognize that production and personal consumption havepolar effects, in that the former creates wealth and the latter uses it upto reproduce individuals. The question is, where do the middle two activ-ities fit?

Both classical and Marxian economics view distribution and socialmaintenance activities as forms of consumption - they are part of so-cial consumption, as opposed to personal consumption. Orthodox eco-nomics takes exactly the opposite tack. It argues that distribution andsocial maintenance are forms of production. Is not distribution (for in-stance) just as necessary as production? In fact, is this necessity not man-ifested precisely in the fact that distribution "transforms" a commodityinto a different commodity, and that people are willing to pay for thistransformation?

As we have seen, distribution does indeed transform a commodity, byaltering its ownership. In doing so it completely transforms the commod-ity from the point of view of the seller, changing it from a commoditywith a price tag to one that has been successfully sold. Thus, if we wereto enumerate the vector of "characteristics of the commodity" a la Lan-caster (1968), some of these characteristics would now be changed. Butfrom the point of view of the user, the characteristics that define its usevalue remain just as they were: they are not altered merely because it hasbeen sold. As far as the user is concerned, the sale is only one of manyways of achieving access to the pre-existing use value. This becomes evi-dent when it is "accessed" by being stolen instead of being purchased.

In the eyes of orthodox theory, however, it is sufficient that the usevalue be somehow transformed, and that someone be willing to pay forit. The former establishes that some change is brought about, the latterthat someone finds this change to be necessary. Taken together, they es-tablish that distribution activities produce services - that is, useful effectsfor which someone is willing to pay. From this point of view, distributionactivity is identical to production activity, since both are necessary. Thesole distinction then resides in the (unimportant) fact that whereas theformer consists entirely of services, only part of the latter does, the restbeing made up of (physical) goods. And so, in the end, the orthodoxdefinition of production reduces to that of labor which is deemed to besocially necessary:


To the economist, production is the creation of any good or service thatpeople are willing to pay f o r . . . . The agricultural, manufacturing, andmarketing services all satisfy human wants; and people are willing to payfor them. . . . Half of what you pay for many products goes for middle-men's services - the retailer, the wholesaler, the banker, the trucker, andmany others. Lots of people object violently to this situation. "Thereare too many middlemen!" they say. Maybe there are. B u t . . . the realtest for all producers is whether they satisfy a consumer demand - nothow many pounds of physical stuff they produce. (Bach 1966, p. 45)

The thrust of this logic is clear. Either the definition of productionis confined to "physical stuff" (goods), or else it must be broadened toinclude all "services," the latter being defined to encompass all market-able activity. To the practical economist, one who gathers the actual dataand renders these definitions concrete, this leads to the following opera-tional criterion: If it is sold, or could be sold, then it is defined as produc-tion.17 Thus - within orthodox accounts - commodity traders, privateguards, and even private armies are all deemed to be producers of socialoutput, because someone is paying for their services. So too are all gov-ernment employees and military personnel, in this case because their em-ployment by the state is usually taken to mean that the society deemsthem necessary.18

When we consider only production and personal consumption, the dis-tinction between them is also a distinction between labor and nonlaboractivity. But once we introduce distribution and social maintenance ac-tivities, labor need no longer be an undifFerentiated category. Since clas-sical and Marxian economics view distribution and social maintenanceas nonproduction activities, the corresponding portion of labor becomesnonproduction labor. Orthodox economists view these same activities asproduction. For them, all labor is production labor, and the distinctionbetween production and consumption becomes synonymous with the dis-tinction between labor and leisure.

At an abstract level, the orthodox argument turns on the notion that mar-ketability is equivalent to production. But at a more concrete level, mar-ketability is only a measure of the ability to attract money, and it rapidlybecomes evident that money flows are not synonymous with counterflows

17 It need not actually be paid for; it is sufficient that it could fetch a price. Manycomponents of actual national income accounts depend heavily on imputedmoney values.

18 The application of operation criteria is always circumscribed by social practice.Thus nonmarket government labor has long been included, and its "product"estimated by imputing some money value to it, even when it has been what wedesignate as nonproduction labor. On the other hand, production labor per-formed in the household has almost always been ignored in official accounts.Only recently has this latter issue begun to be addressed, albeit unofficially (seeRuggles and Ruggles 1982 and Eisner 1988).


of new wealth. Even orthodox economics then admits that some mon-etary transactions correspond to transfer payments, which "are simplymeans of redistributing, among the members of the community, the goodsand services produced in the economy" (Beckerman 1968, p. 7). As apractical measure, the theoretical notion of marketability must then beapplied in such a way as to exclude transactions involving transfer pay-ments from those involving production, on the grounds that the personsreceiving the former do not "render current services" (BEA 1986, p. xi).Yet at the same time, those who administer such payments are countedas producing wealth. Thus, in orthodox economics, the flow of unem-ployment benefits is excluded from the measure of production becauseit does not correspond to any service rendered by those who receive it.Unemployment benefits are a transfer of wealth. But the civil servantswho administer these large and growing transfers of wealth are countedas producing new wealth in the form of administrative services. In Marx-ian economics, both would be excluded from production.

2.4 Production labor, surplus value, and profitAny concrete capitalist social formation is a mixture of capitalist

and noncapitalist relations of production in which the former dominates.But the dominance of capital should not obscure the fact that all spheresparticipate in the reproduction of the social formation, and that the capi-talist sphere is not independent of the others. This gives rise to severalnew considerations.

The first issue concerns the difference between capitalistically producedwealth and total new wealth. We have already noted that all types of pro-duction labor create new wealth. Thus, household and commodity pro-duction labor create use values that are bearers of value aimed at earninga revenue; they create simple commodities. Capitalist commodity pro-duction labor creates use values that also are bearers of both value andsurplus value, and are aimed at making a profit; such labor creates com-modity capital (Marx 1963, pp. 156-7). The wealth of capitalist nationsgenerally encompasses all three forms, in proportions that vary over time,space, and stage of capitalist development. But not all are captured inconventional accounts. Commodity production and capitalist commodityproduction are generally well covered (subject to the usual difficulties ofestimating hidden transactions) because the product is sold for money,and much of the nonmarketed product (such as directly consumed farmproduction, repairs to owner-occupied houses, etc.) is captured by im-puting a money value to it. But official national accounts still leave outthe imputed value of household production, although all extended ac-counts now correct for this (see Chapter 1). Because our concern is with


an alternative to the official accounts for market activities, we will notdeal with nonmarket and illegal activities in this particular work. Suchmatters are, however, important in any extension of the basic accountsdeveloped here.

The next issue regards the relations between profit and surplus value.It is well known that, at the most abstract level of Marxist theory, aggre-gate profit is simply the monetary expression of aggregate surplus value.But it is often forgotten that profit can also arise from transfers betweenthe circuit of capital and other spheres of social life. Marx calls this latterform of profit profit on alienation, which - unlike profit on surplus value -is fundamentally dependent on some sort of unequal exchange. Its ex-istence enables us to solve the famous puzzle of the difference betweenthe sum of profits and the sum of surplus values brought about by thetransformation from values to prices of production (Shaikh 1984,1992a).More importantly, it allows us to explain how capitalism can derive aprofit from noncapitalist spheres without any creation of surplus value.In what follows, we will focus on the latter aspect alone, since the formerhas been treated in detail elsewhere (Shaikh 1984).

Consider a barter between a noncapitalist tribe and a merchant capi-talist. The merchant purchases guns worth £100 in London, barters themfor furs from the tribe, and sells the furs back in London for £250. Themerchant thus gains £150, which covers both trading costs and merchantprofit. Yet there has been no corresponding increase in surplus value.Nor has there been an offsetting loss to the members of the tribe, since(under this idealized version of trade) they have traded one set of goods(furs) for a more desirable set (guns). Aggregate profits have risen by£150, apparently out of thin air. How is that possible?

The answer lies in the fact that different measures of gain have beenapplied across the two poles of the above transaction. The tribe is oper-ating within the simple commodity circuit C-C9 in which one set C ofuse values is bartered for another useful set C . The comparison here isin terms of social usefulness. At the other pole, the merchants operatewithin the capital circuit M-C-C'-M', in which one sum of money (M =£100) is transformed into a larger sum (M'= £250), through the exchangeof one set C of use values for a more valuable set C . Because only one ofthe poles is assessed in monetary terms, any monetary gain recorded therehas no counterpart at the other pole, so that a net monetary gain appearsfor the system as a whole. If both poles were treated in the same way,then it would be obvious that one side's monetary gain was another side'smonetary loss: the tribe would have exchanged assets valued at £250 (furs)for those valued at £100 (guns), for a net change of asset value of -£150;the merchants would correspondingly have recorded a net change in asset


value of +£150, which they would then realize as profits of £150 throughthe sale of the furs.

Similar results can be derived for transfers between capitalist and pettycommodity spheres. For example, suppose a petty commodity producersells a product for $50 to a merchant who then sells it on the open marketfor $250 (handicrafts are an obvious example). For simplicity of exposi-tion, assume that the final selling price is merely the money equivalent ofthe commodity's (labor) value.19 Then, from a global point of view, themerchant has merely succeeded in transferring four-fifths ($200/$250)of the total value of the product to himself, leaving only one-fifth inthe hands of the original producers. But whereas a portion of the valuetransferred in to the merchant will show up as part of aggregate capi-talist profit (in the wholesale-retail sector), there will be no correspond-ing transfer out listed in the petty commodity sector because its productwill be valued only at its immediate selling price (producer's price) of$50, rather than its final selling price (purchaser's price) of $250. A por-tion of the transfer in of value will therefore show up as a net additionto aggregate profit.

Finally, consider transfers within the capitalist sector itself, betweenthe circuit of capital and the circuit of revenue. Suppose an (uninsured)object such as a television set is stolen from a house, sold to an unscrupu-lous merchant for $50, and then resold on the open market for $250.From the point of view of the society as a whole, the original owner haslost an asset worth $250, a new owner has gained an asset worth $250 buthas given up a money sum of exactly the same amount, and the merchantand thief have shared out a net gain of $250. The merchant's profit isthen clearly the counterpart of a portion of the original owner's loss. Butif we disregard this latter loss, or record it only at partial value, then ofcourse the merchant's profit will seem to spring out of thin air. Section3.2.2 provides a particularly striking example of this effect.

The preceding examples should make it clear that, even at the mostabstract level, aggregate profit encompasses both profit on surplus valueand profit on alienation. At a more concrete level, we must also allow forsome profit on alienation derived from various transfers between nationalcapitals and other foreign capitals and noncapitals. The issue here is not

19 Thus, if the labor value of the commodity is 125 hours and the value of money ishalf an hour per dollar, then the commodity's direct money equivalent (directprice) would be $250. If the commodity were to be sold for more or less than$250, then value would be transferred in or out of the combined petty commod-ity and merchant capital circuit. This additional transfer could then be treatedseparately, and poses no new problems except those involved in the so-calledtransformation problem. See Shaikh (1984,1986,1992a) for further discussion.


one of money flows of profits, dividends, and interest, but rather of thedifference between the sum of such flows and the surplus value that sup-ports them in modern capitalism. Since it is our object to measure themoney equivalent of this surplus value, we must be mindful of the factthat our measure will pick up some part of profit on alienation. For theUnited States, with its highly developed capitalist sphere and its relativelysmall foreign trade sector, the error in associating aggregate profit withaggregate surplus value appears to be small.20 But in earlier times, or inless developed capitalist nations, no such a priori identification can bemade. It would then be necessary to explicitly separate profit on surplusvalue from profit on alienation.

2 0 Khanjian (1989, pp. 108-13) finds that value measures of surplus value differ fromcorresponding money measures by 6%-9%. He attributes this to transfers ofvalue brought about by price-value deviations within the U.S. economy. Ourown estimates of foreign transfers of value indicate that they are quite small(Section 3.4.2).

Marxian categories and national accounts:Money value flows

The purpose of this chapter is to develop a mapping between Marxiancategories and those of conventional national accounts. The essentialpoints of the argument will be presented here, with all further detail re-served for Appendix A.

National income and product accounts (NIPA) are the traditional basefor national accounting. But input-output (IO) tables provide a moregeneral framework in that they encompass both interindustrial flows andnational income-product flows. We will therefore use IO tables as ourbasic theoretical and empirical foils.

Although IO accounts provide a superior description of the economyfor our purposes, they suffer from the drawback of being available onlyfor benchmark years (1947, 1958, 1963, 1967, 1972, 1977) for the UnitedStates. We will therefore use these tables only to provide comprehen-sive benchmark estimates, which will then be expanded into annual seriesusing NIPA data.

Our project requires distinguishing between three different sets of mea-sures, for which we adopt different notation: Marxian labor value measuressuch as constant capital, variable capital, and surplus value (C, V, S);their money forms (C*, V*, S*); and corresponding IO-NIPA aggregatessuch as intermediate inputs, wages, and profit-type (unearned) income(M, W, P). Since all accounts in question will be double-entry accounts,each of the revenue-side flows will have use-side counterparts (such, as Ufor the Marxian labor value of the inputs used in production, U* for thecorresponding Marxian money value, and M for the orthodox measure ofintermediate inputs on both revenue and use sides). The letter P taken byitself will refer to profit-type income, but when preceded by another letteror when appearing as a subscript it will refer to production. Thus TPstands for total product, and Pp refers to profits in the production sector.

38

Money value flows 39

All results will be summarized both graphically and algebraically. Inaddition, we illustrate what will become an increasingly complex mappingbetween Marxian and IO categories by means of a continuing numericalexample in which the magnitude of the total product, of the correspond-ing total (labor) value, and of their respective components are held con-stant throughout. Thus a given quantity of total value TV* will alwaysbe divided into the same amount of constant capital C*, variable capitalV*, and surplus value S*. Similarly, total product TP* will always bedivided into the same amounts of inputs used up in production U*, nec-essary product NP* (consumption of production workers), and surplusproduct SP* (used for capitalist consumption, investment, nonproduc-tion, and state activities). As we move beyond production alone to con-sider wholesale and retail trade, finance, government, and the externalsector, these given amounts of value and product will be subject to pro-gressively more complicated modes of circulation and distribution, andtheir corresponding forms of appearance within IO tables will becomemore complex. Nonetheless, precisely because we have the original nu-merical quantities already in hand, we can immediately verify that ourmeasures of the aggregates are correct.

Sectors (such as production and wholesale /retail trade) which are di-rectly involved in the production and domestic realization of the totalcommodity product will be called primary sectors. Those (such as finance,land rental and sales, and general government) involved in the subsequentrecirculation of the value and money streams originating in the primarysectors will be called secondary sectors.1 Such a distinction is rooted inthe Marxian approach to capitalist reproduction, and its rationale willbecome evident as we proceed with the argument. In what follows, wewill begin with the analysis of the primary sectors and then move on tothe various components of the secondary sectors. The sections on foreigntrade and noncapitalist labor activities sectors will round out the argu-ment, to be followed by an overall summary of the relations betweenMarxian and orthodox national measures. Table 3.1 illustrates the sec-toral divisions just outlined; further detail will be developed in the sec-tions that follow.

Finally, it should be noted that we will conduct our argument as if ac-tual input-output tables included fixed capital used up in intermediateinputs (as depreciation) and in intermediate demand (as replacement in-vestment), so that value added and final demand are net measures. Wewill also proceed as if value added were explicitly divided between wages

1 It should be obvious that primary and secondary, as used here, do not at allmean the same thing as "primary products" (extracted products), etc.


Table 3.1. Sectoral structure of reproduction

Primary sectorsProduction (goods/services, private/public)Trade (wholesale/retail, building/equipment rentals)

Secondary sectorsFinance, ground rent, royalties (private)General government (public)

Foreign trade sectors

Noncapitalist labor activities

and profits, and consumption demand were explicitly divided betweenworkers' consumption and capitalist consumption. Conventional tableslack this level of detail, but could be modified to incorporate it. Themapping between Marxian and IO categories is greatly enhanced by theseadjustments. As noted earlier, Appendix A provides further detail on thematerial developed in this chapter.

3.1 Primary flows: Production and tradeThis section will deal with primary flows only. We will begin with

a consideration of production activities alone, and then move on to ana-lyze production and trade taken together. Before we proceed, it is usefulto recall some critical points concerning the definitions of production andtrading activities.

Briefly, "production" encompasses those activities that create or trans-form material objects of social use (use values). As derived in Chapter 2,this definition covers not only goods but also many so-called servicessuch as transportation, entertainment, lodging, cooking, and so forth.Moreover, since the definition depends on the character of the process,not on its formal ownership, it also covers government enterprises insofaras they produce use values (such as electricity).

The definition of "trade," on the other hand, encompasses not onlywholesale /retail trade but also the rental of produced commodities suchas cars and buildings (since this is merely the piecemeal sale of the prod-uct's use value over its functioning lifetime), the activities of governmenttrading enterprises, and any transportation involved in conjunction withthese realization activities. Table 3.2 outlines the basic components ofthe primary (production and trade) sectors. Further detail will be reservedfor the empirical analysis in Chapter 5.


Table 3.2. Production and trade sectors

Production Trade

Goods Wholesale/retailProductive services Building, equipment, and car rentalsGovernment production Government tradingProductive transportation Distributive transportation

3.1.1 National accounts with production sectors aloneConsider production alone. Suppose that the total product con-

sists of 2000 hours of (labor) value, whose aggregate selling price is anymoney sum, say 4000 "currency units" (CU). The total labor value of2000 hours is expressed in 4000 CU of money. But we can always redefinethe unit of money to be equal to 2 CUs, name this new unit a "dollar,"and say that the total selling price of 2000 hours of value is $2000. Whilethis is merely a notational device, it simplifies our exposition by allowingone magnitude (with differing units) to represent total labor value andalso its monetary expression, the total selling price of the product. Theterm "value" will therefore be used for both labor value and its monetaryexpression, unless we wish to explicitly distinguish them.

Once we introduce trading activities, we need to distinguish betweenthe producer's price (the price at which the product is sold by the pro-ducer to the wholesaler/retailer), and the final selling price charged by thewholesaler/retailer (which includes their markup). As long as the markupis positive, there will be a transfer of value from the producing sector tothe trading sector. This was discussed in Section 2.4.

None of the results we derive depend significantly on whether or notproducer prices or final selling prices of individual commodities deviatefrom their corresponding labor values. Regardless of any such deviations,the sum of individual producer prices defines an aggregate producer price,and the sum of individual final selling prices defines an aggregate finalselling price of the total product; this is all we need to know at present.The issue of individual price-value deviations and their impact is takenup in Sections 4.1 and 5.10.

Throughout this chapter, we will assume that the $2000 selling price ofthe total product is composed of $400 in production costs, $200 in pro-duction worker wages, and $1400 in profits (profit-type income) and otherexpenses. In order to track the use of this same aggregate product, wewill assume that production costs represent the costs of inputs used in


Table 3.3. Value and use of the product

Value of product Use of product Amount

Production costs = Inputs used = $ 400Worker wages = Workers' consumption = $ 200

Profits - (Capitalist consumption ($700)] _Fronts - ^ T o t a l i n v e s t m e n t ( $ 7 0 0 ) ) -

Total price = Total use = $2000

Table 3.4f Marxian and IO measures: Revenue side

Marxian name IO name Amount

Constant capital C* = Intermediate input M = $ 400Variable capital V* = Wages W = $ 200Surplus value S* = Profits P = $1400

Total value TV* = Gross output GO = $2000C* + V* + S* = M + W + P =$2000

production, that workers' consumption is equal to their wages, that capi-talist consumption is equal in magnitude to one half of profits, and thatthe sum of (intended) business investment in plant, equipment, inven-tories, and "unintended inventory investment" (i.e. unsold or oversoldgoods) will be equal to the other half of profits. This latter assumptiondoes not imply that sectoral or aggregate supply and demand balance.Rather, it is simply a standard accounting device in which the differencebetween supply and demand is added to the "total investment" on theuse side as "unintended inventory change" so as to make the revenue anduse sides balance ex post. Table 3.3 provides a numerical illustration ofthese basic principles.

Table 3.4 compares the Marxian and IO representations of the flowsportrayed in Table 3.3. Precisely because we are considering productionalone, the correspondence is straightforward: Constant capital C* is thesame as intermediate input M, variable capital V* the same as wages W,surplus value S* the same as profits (profit-type income), and total valueTV* the same as gross output GO. The relation between Marxian and IOmeasures of the use side is equally transparent, at this level of abstraction.The Marxian measure of the amount of product used as inputs U* willbe the same as the corresponding IO measure of intermediate demand M;


Table 3.5. Marxian and IO measures: Use side

Marxian name IO name Amount

Production input U* = Intermediate demand M = $ 400Necessary product NP* = Workers* consumption CONW = $ 200

c . . . CT5sic f Capitalist consumption CONC ($700)) -,, A^Surplus product SP* = [ ^ i n v e s t m e n t {{Sm) >\ = $1400

Total product TP*U* + NP* + SP*

= Gross product GP= M + CONW + (CONC +1)

= $2000= $2000

TC*

4///////A

Figure 3.1. Division of value: Production alone.

the Marxian measure of necessary product (the consumption of produc-tion workers) NP* the same as the IO measure of workers' consumptionCONW; and the surplus product SP* the same as the sum of capitalistconsumption CONC and total investment I. See Table 3.5.

The numerical outcomes in Tables 3.4 and 3.5 are illustrated graphicallyin Figures 3.1 and 3.2. Within their respective figures, Marxian total valueTV* and total product TP* are enclosed in solid and dashed lines respec-tively, Marxian value added (VA* = V* + S* = 1600) and final product(FP* = NP* -I- SP* = 1600) in hatched areas, and surplus value and surplus


Total Product =2000

Figure 3.2. Use of product: Production alone.

Production

Gross Final Demand

CONW CONC I

Total Producfc:TP*=2000(Within Dashed lines)

Total Valuc=TV*=2000(Within Solid Unes)

Gross OutputGO

Figure 3.3. IO accounts and Marxian categories: Production alone.

product in shaded hatched areas. We will use these conventions in allsubsequent figures.

Finally, we can map the relations expressed in Figures 3.1 and 3.2 ontothe (rudimentary) input-output table in Figure 3.3. At this level of ab-straction, the input-output table is merely a concatenation of the twosides depicted in Figures 3.1 and 3.2. In the resulting table, Marxian totalvalue TV* and total product TP* are enclosed within the solid and dashedareas, respectively, while the various hatched areas within each representMarxian value added VA* and final product FP*, respectively.

Figures 3.1-3.3 establish that when all activities are assumed to beproduction activities, Marxian measures are identical to their orthodox


counterparts, at least at this level of abstraction.2 But this direct andsimple correspondence is quite deceptive. It disappears as soon as weconsider nonproduction activities.

3.1.2 National accounts with production and trade sectorsWe now broaden our inquiry to include wholesale/retail trade

(other trading activities will be considered later). Production and its ele-ments are the same as before, but the circulation of this given total valueand product is now explicitly mediated by trading activities.

Suppose that the previously considered output worth $2000 is now real-ized in two distinct steps. First, it is sold by the producing sector p to thetrading sector t, for a producer's price of $1000.3 Second, this very sameproduct is then sold by the trading sector to individuals for use in per-sonal consumption, to firms for use as materials and fixed capital, or isretained as unsold goods in inventories.4 The sum of these dispositions,which equals the final selling price of the product, is called the purchaser'sprice of the product. The $1000 difference between the producer's priceand purchaser's price is known as the trading margin TM of the tradesector.5 The trading sector thereby converts an aggregate product worth$2000 into money and unsold goods totaling $2000, keeping $1000 of theproceeds for itself.

The present two-stage realization process distributes the previouslygiven total value of $2000 in a new manner. The intermediate input andwage bill of the production sector are unchanged (Mp 4- Wp = 400 + 200 =600), but since its total revenue is now only $1000, its profit Pp is re-duced to $400 (from $1400). At the same time, the $1000 which is lostto the producing sector is captured by the trading sector in the formof its trading margin, which in turn is allocated among its own inputsMt, wages Wt, and profits Pt. From the Marxian point of view, noth-ing has changed in the production process, so that constant capital C*,variable capital V*, and surplus value S* are unchanged. But whereasthe total surplus value S* = $1400 previously accrued entirely to the pro-duction sector as profits, it is now divided between the profits of the

2 This assumes that profits are measured accurately - i.e., that allowance is madefor the extent to which profits may be disguised as fictitious costs and expenses.

3 We may think of the producing and trading sectors as production and sales di-visions of the same company.

4 National accounts trace the disposition of the'actual product. Thus if some of itis unsold, the unsold portion is counted as a (positive) "investment" in inven-tories. If more is sold than is produced, then the excess of sales over productionis treated as a negative investment (a "disinvestment") in inventories. Either way,the sum total in question is made equal to the current annual product.

5 Since we have assumed that depreciation is listed as part of the input costs in ourexamples, the trading margin is net of depreciation.


Total Value=2000

Figure 3.4. Division of value: Production and trade.

production sector (Pp = $400) and the trading margin of the trade sector(TM = Mt + Wt + Pt = $1000).

To derive the use-value side, we follow our previous conventions: Foreach sector, intermediate use of the product is the same as its materialsinputs on the revenue side (Mp = $400, Mt = $200); workers' consump-tion is equal to their wages (CONWp = Wp = $200, CONWt = Wt = $400);capitalist consumption is one half of sectoral profits (CONCP = $200,CONCt = $200); and total investment (including unintended inventorychange) is equal in magnitude to the other half of profits (Ip = $200, It =$200).

From a Marxian point of view, the productive input use U*, the neces-sary product NP*, and the surplus product SP* are unchanged by theirmore complex mode of circulation. This means that U* = Mp = $400,NP* = CONWp = $200, and SP* = $1400, as before. But the dispositionof the surplus product is now different, since it is absorbed not only bycapitalist consumption and investment in the production sectors but alsoby all uses of the trading sector. Thus


TotalProduct

2000

M t

200

C0NWt

400

CONC

400

Ui SP*=Suiplus Product= 1400

Figure 3.5. Use of product: Production and trade.

SP* = (CONCP + Ip) + (Mt + CONWt + CONCt + It)

= ($200 + $200) + ($200 + $400 + $200 + $200) = $1400.

Figures 3.4 and 3.5 depict these new divisions of value and use value.The last step is to assemble all the preceding information into a map-

ping between input-output and Marxian accounts. To accomplish this,we need to delve further into the conventions of IO tables.

We begin by noting that whereas commodities are sold to their final usersat purchasers' prices, most input-output tables are cast in terms of pro-ducers' prices. Thus the total revenue listed for any given activity (grossoutput and gross product, in IO terminology) is its estimated producer'sprice, not its actual s^les revenue (purchaser's price). By the same token,the total revenue of the trading sector (its "producers' price") is the sum ofthe trading margins on all activities that pass through this sector.6 But sucha procedure immediately creates a problem in the valuation of purchasesof inputs and of elements of final demand, since these items are acquired atpurchasers' prices. Conventional IO tables get around this by treating anysingle commodity purchase as two separate but simultaneous transactions,one from the producing sector in an amount equal to the producer's priceof the commodity input, and one from the trading sector in an amountequal to the trading margin on the same bundle of commodities. In this way

6 In this context, the term "producers' price" means the total revenue generatedfrom the activity minus any wholesale/retail margins. Since all revenue-generat-ing activities are treated as production activities in orthodox economics, eventhe trading sector has a producers' price.


Production

GO

2000

Total Product=TP*=2000(Within Dashed Lines)

Total Value=TV*=2000(Within Solid Lines)

Figure 3.6. IO accounts and Marxian categories: Production and trade.

the final purchaser's price of any input is decomposed into its producer'sprice and its trading margin, and the two components are recorded sep-arately as "goods" purchased from the producing sector and "tradingservices" purchased from the trading sector (BEA 1980, pp. 19-20).

In our numerical example, the total value of the aggregate product issplit between producer's price and gross trading margin in the propor-tions 1000:1000 = 1:1. For simplicity in constructing our IO table, wewill assume that the same split holds for each individual component ofthe total product. On this assumption, each commodity purchase (M,CONW, CONC, and I) appearing in Figures 3.4 and 3.5 will be recordedas two equal "purchases" from the production and trade sectors, respec-tively. The row sum of all these commodity trade margins is the "grossproduct" of the trade sector in input-output terminology, and this ofcourse is the same as the corresponding column sum of its input costs,wages, and profits (its total revenue or "gross output"). The resulting IOtable is depicted in Figure 3.6, with our usual conventions for represent-ing the various Marxian measures.

The translation from the Marxian value and use-value flows depictedin Figures 3.4 and 3.5 to the conventional input-output mappings in Fig-ure 3.6 brings out the difference between the two theoretical bases. Aglossary of terms is provided next, and Table 3.6 summarizes the alge-braic and numerical relations between the two sets of measures as derivedfrom Figure 3.6.


Marxian measures Input-output measures

GO = M + W + P=total value = gross output

VA* = V* + S* VA = W + P= value added = final demand

TP* = U* + FP* GP = M + FD= total product = gross product

FP* = NP* + SP* FD = CON + I = CONW+CONC + I= final product = final demand

Lp = productive employment (no direct counterpart)

Lu = unproductive employment (no direct counterpart)L=total employment L=total employment

Table 3.6 (p. 50) makes it clear that once we distinguish between pro-ductive and unproductive activities, Marxian and IO-NIPA categories nolonger correspond directly. Since the revenue sides are more similar acrossframeworks than are the use-value sides (there being no input-outputequivalents of necessary and surplus product), we will focus our explana-tion on the former. Even at this level of abstraction we can identify sev-eral general patterns.

Production and trade are the sectors through which the commodityproduct is produced and realized. Their combined total revenue thereforerepresents the total price of the product TV*. In input-output tables, thiscombined total revenue will show up as the sum of the gross outputs ofthe production and trade sectors GOP and GOt. It will not include therevenues ("gross output") of any secondary sectors (GOS) because suchrevenues originate in transfers of portions of the value flows of the pri-mary sectors, and all such source flows have already been counted in thesector of their origin. Thus we will always find that total value TV* =GOp + GOt, constant capital C* = MP, variable capital V* = WP, andproductive employment equals the employment of capitalistically em-ployed production workers Lp alone. For this same reason, in generaleach of these Marxian categories will always be less than their orthodoxcounterparts GO, M, W, and L, respectively, precisely because these lat-ter measures count trade, ground rent, finance, and a host of other non-production activities as forms of production.7

Other patterns in Table 3.6 will not necessarily carry over to the generalcase. For instance, the present equality of Marxian total value TV* and

7 If we use the subscript s to denote secondary sector variables, then conventionalgross output GO = GOP+GO, + GOS, intermediate input M = Mp + M, + Ms, totalwages W = Wp + W, + Ws, and total employment L = LP + Lt + Ls, respectively.


Table 3.6. Marxian and IO measures: Production and trade

Marxian Input-output

A. Revenue sideTV* = GOp + GOt = 2000

= 1000+1000C*=Mp = 400

VA*=TV*-C* = 1600= VAp + GOt = 600+1000

V* = Wp = 200

S*=VA*-V* = 1400= PP + GOt

= Pp + Pt + (Wt + Mt)= 400+ 400+ (400+ 200)

S*/V* = rate of surplus value= 1400/200 = 700%= [Pp + Pt + (Wt + Mt)]/Wp

B. Use sideTP* = GPp + GPt = 2000

U* = Mp = 400

FP* = T P * - U * = 1600= Mt + CON + I= 200+1000 + 400

NP* = CONWp = 200

SP* = FP*-NP* = 1400= Mt + CON + I-CONWp

= Mt + CONWt + CONC +1= 200 + 400 + 400 + 400

SPVNP* = rate of exploitation= 1400/200 = 700%

GO = GOp + GOt = 2000= 1000+1000

M = Mp + Mt = 400 + 200 = 600VA = G O - M = 1400

= VAp + VAt = 600 + 800

W = Wp + Wt = 200 + 400 = 600

P = Pp + Pt = 400 + 400 = 800

» P/W = profit/wage ratio= 800/600=133%= (Pp + Pt)/(Wp + Wt)

GP = GPp + GPt = 2000

< M = Mp + Mt = 400 + 200 = 600

> FD = G P - M = 1400=CON+I= 1000 + 400

(no direct counterpart)



= (Mt + CONWt + CONC + I)/CONWp

input-output gross output GO does not hold in general, for the reasonsdiscussed previously. More importantly, although we will be able to de-rive the precise relations between Marxian value added VA* and orthodoxvalue added VA, and between Marxian surplus value S* and aggregateprofits P (which at this level of abstraction is the same as "profit-typeincome" P + in Section 3.2.2, i.e. the sum of profits, rents, and interest),at a more general level the relative magnitudes of the two sets cannot bedetermined a priori. Indeed, the empirical evidence in Chapter 5 indicates


that whereas S* continues to be greater than P + and P, the present findingthat VA* > VA (see Table 3.5) is actually reversed at a more concrete level.Table 3.12 will summarize these and other general patterns in our findings.

3.1.3 Further types of trading activitiesWe indicated in Table 3.1 that the definition of trading activities

encompasses not only private wholesale/retail trade but also any trad-ing done by government enterprises, as well as distributive transport andthe rental of buildings and equipment. Because input-output accountsplace specific government enterprises in the same industries as their pri-vate counterparts (BEA 1980, p. 45), we can assume that governmenttrading enterprises are already part of the overall trade sector.

The treatment of transportation is similar to that of trade in IO ac-counts (see Section 3.1.2). That is to say, only transportation marginsenter into the transportation sector's gross output and product, and theindividual margins are all "unbundled and shifted forward" (BEA 1980,p. 20). Thus, if we were able to estimate the portion of transportationwhich qualifies as distributive transport, we could in principle merge thisdirectly into the trade sector. But in practice the necessary information islacking, so that our empirical estimates are based on the assumption thatall transportation is productive transport.

The identification of building and equipment rentals is more complex.To begin with, the overall real estate and rental sector in conventionalaccounts is comprised of three disparate activities. The first is a fictitious(imputed) component known as "owner-occupied rentals," arising fromthe fact that IO-NIPA accounts treat homeowners who live in their ownhouses as if they were businesses renting out their homes to themselves.This must be discarded altogether. Second is the rental and sale of land,which we will shift to the secondary sector (along with finance) since suchactivities really amount to the recirculation of revenues, titles, and claimsto revenues. The third activity is the sale and rental of buildings, whichinvolves either the direct or piecemeal sale of a produced commodity andmust therefore be merged into the overall trade sector.

Furthermore, IO accounts treat building and equipment rentals as pro-duction activities, whereas we need to treat them as trading activities;this means that when we merge building /equipment rentals (br) into thetotal trade sector (tt), we must ensure that only the rental margins enterinto gross output and product and that the individual rental margins (thelow elements of the sector) are unbundled and shifted forward. Figure 3.7summarizes the overall treatment of the primary flows. All further detailis reserved for Appendix A.


P r o d u c t i o n

! i: 1

Total Trade Final Demand GrossProduct

GP

Agriculture

Manufacturing

ProductiveServices

Wholesale &Retail

Real Estate &Rental

Wages

Value Added

GPa

v_;•:..-. A

Mp

- , " • • * • ,

VAt

Gross Output GOa GOt

90/

GOp . GOtt_

Figure 3.7. IO accounts and Marxian categories: Primary flows.

3.2 Secondary flowsProduction and trade activities derive their revenues directly from

the sale of the commodity product. These primary flows in turn give riseto a series of secondary flows, such as payments for ground rent,8 financecharges, fees, royalties, and taxes.

Secondary sectors are therefore defined by the fact that they derivetheir revenues from the recirculation of the money flows generated by theprimary sectors, or from the circulation of socially validated claims uponportions of these primary flows, or both. Thus, (pure) ground rent9 (asopposed to building and equipment rental, which we have already ana-lyzed) is a royalty paid for access to land, interest a royalty paid foraccess to money and credit, and a patent or other fee a royalty paid foraccess to a particular process of some sort. The sale of land, of financialinstruments, and of patent rights then circulates the claims to these royal-ties. A similar conclusion applies to taxes, which are (quite literally) roy-alty payments made to a sovereign social power.

8 The term "ground rent" refers to the rental of land, mines, etc.9 Capitalist ground rent, as Marx notes, is part of surplus value that accrues to

landowners because of their "ownership of certain portions of our planet" (Marx1967b, p. 634).


The transfers between the primary and secondary sectors can take placedirectly when the former pay royalties (ground rent, interest, etc.) to thelatter. Or they can take place indirectly, when (say) the households whoderive their revenues from the primary sectors (as wages, dividends, in-terest payments, etc.) in turn pay over some portion of these revenuesto the royalties sector. In either case, since the original sources of thesesecondary-sector revenues are already captured in the accounts of the pri-mary sectors, we cannot count them again in the measure of total value.By the same token, since the total product is produced and realized in theprimary sector, we cannot count the revenues received by secondary sec-tors as measures of some additional production emanating from thesesectors. Thus we cannot count them in the measure of total product. Sec-ondary flows are part of total transactions, but not part of total value ortotal product.

Note that this does not mean that we ignore the actual use of the prod-uct by the secondary sector or by households whose incomes derive fromit. Royalty payments are deductions from the purchasing power of theprimary sector and its associated households. Their receipt by the secon-dary sector enhances that sector's purchasing power and that of its asso-ciated households. What the former sector loses, the latter gains. In thisway the redistribution of value brought about through transfers betweenthe primary and secondary sectors leads to a changed use of the product.

A. PRIVATE SECONDARY FLOWS: GROUND RENT, FINANCE, ROYALTIES

3.2.1 General implications of royalty paymentsIn what follows, we will use the term "royalty payments" to des-

ignate secondary flows in general. As we have already noted, transfersbetween the primary and secondary sectors do not generally change thebasic Marxian measures.10 But because IO-NIPA accounts treat thesetransfers as purchases of the royalties-sector "product," they do changethe corresponding orthodox measures. Hence the consideration of royaltypayments adds a new element to the mapping between the Marxian and or-thodox accounts. We next analyze the cumulative effects of these changeson measures of total output and product, on value added and net product,and on total profit-type income.

Since orthodox accounts treat the receipts of the royalties sector as ameasure of its so-called product, they increase the measures of economy-wide gross output GO by adding a column for royalties-sector revenues,

10 Royalty payments that come out of the wage of productive workers can lowertheir true wage and hence raise surplus value. We address this issue in Section 3.3.


and increase the measure of total gross product GP by adding a row ofdisbursements to the royalties sector from all other sectors. From ourpoint of view, these are merely records of transfers, and must be left outof our measures of total value TV* and total product TP*. Thus, as be-fore, TV* = GOp + GOt and TP* = GPp + GPt. We will see shortly thatthe same principles apply to the general government sector.

The effects on orthodox measures of value added and profit are a bitmore complex. There are three possibilities, depending on whether roy-alty payments are treated as costs or disbursements.

First, primary sectors' accounts treat some particular type of royalties(RYP + RYt) paid to the secondary sectors as costs and hence record themamong intermediate inputs (by adding them to intermediate inputs andthen subtracting them from value added by creating a matching negativeentry for "imputed interest received"). This is the case with ground rentpaid to the real estate sector and net interest paid to the financial sector,11

so that the measured level of the value added of the primary sectors isreduced by this amount. At the same time, the receipt of these paymentsshows up as the total revenue (GOry = RYp + RYt) of the royalties sector.But since some of this is absorbed by the intermediate inputs (Mry) of theroyalties sector, the amount that re-appears as the value added of theroyalties sector is less than the amount that was lost to the value addedof the primary sectors on the original transfer. Thus the IO-NIPA mea-sure of aggregate value added VA falls below its Marxian counterpartVA* (see Section B.2.2). The reduction in the orthodox measure of aggre-gate profit-type income (profits, rents, and interest) relative to aggregatesurplus value is even greater, because a portion of the value added of thesecondary sector is also absorbed in its wage bill. Finally, to the extentthat rents and (some) interest payments are treated as costs, aggregateprofit will be even smaller.

Second, some types of royalties are treated as disbursements from valueadded (RYp-f RYt'). These comprise net interest and dividends paid tohouseholds, foreigners, and the government, as well as indirect businesstaxes.12 Such payments leave the conventional measure of the primarysectors' total value added unchanged (although they may change the di-vision between profits and royalties). Since these disbursements are notmade directly to the secondary sectors, total business revenues are also

11 Businesses actually list net interest paid as part of disbursements from valueadded, but IO-NIPA accounts treat the interest paid to the finance sector as acost and shift it to intermediate inputs. However, interest paid to consumers,government, and foreigners is left in value added. See Section B.2.

12 As noted previously, orthodox accounts treat net Interest paid by business tothe finance sector as business costs, and record them in intermediate input.


unchanged. Thus transfers of this sort leave unchanged the relation be-tween Marxian value added VA* and orthodox value added VA. The samecan be said for disbursements from profit-type income (the sum of profits,rents, interest, and taxes), though obviously aggregate profits themselvesmay be reduced by the amount of royalties paid out as net interest andindirect taxes.

Finally, the households, government, and foreigners supported out ofprimary-sector revenues may pay a portion (RYC + RYg + RYx_m) of theirincomes over to the secondary sectors as ground rent, net interest, and soforth. Because such transfers take place "downstream" of the primarysectors' gross output, value added, and profits, the originating flows willnot be affected. Of course, the receipt of these payments will increaserevenues of the secondary sector, and orthodox accounts will register thisincreased revenue as an increase in gross output. On the use side, ortho-dox accounts record the transfers in question as purchases of secondarysector output, to be listed in the household-, government-, and foreign-sector columns of final demand; this raises the aggregate measure of finaldemand. Since none of the primary-sector measures are affected, and allof the secondary-sector measures are raised, the aggregate orthodox mea-sures are all raised relative to the corresponding Marxian measures. Thesame argument applies to profit-type income relative to surplus value.This latter result gives rise to the possibility that profit can actually begreater than surplus value, owing solely to the manner of circulation ofthe product. We will examine this new and striking result in more detailin Section 3.2.2.

In summary, royalty flows increase the orthodox measures of grossoutput GO and gross product GP relative to their Marxian counterpartstotal value TV* and total product TP*. But the effect on the magnitudeof conventional value added VA and final demand FD relative to Marx-ian value added VA* and final product FP* is not similarly determinate.Royalty payments by primary sectors to the secondary sectors decreaseorthodox measures relative to Marxian ones, but royalty payments fromthe primary sectors to households, government, and foreigners have noeffect on the relative positions of Marxian and orthodox measure. Androyalty payments made by households, government, and foreigners to thesecondary sectors increase orthodox measures relative to their Marxiancounterparts. The same can be said for measures of aggregate profit-typeincome (the sum of profits and royalties) relative to aggregate surplusvalue. Thus the overall effect of royalty flows on orthodox measures ofvalue added, final demand, and aggregate profit, relative to their Marxiancounterparts, is indeterminate. A more detailed derivation of these resultsis provided in Appendix B.


Final Demand

CON I

GO

Figure 3.8. IO accounts and Marxian categories: Private royaltiespayments.

Figure 3.8 depicts the overall effects of royalty flows on the mappingbetween Marxian and IO categories. Some royalty payments (RYp + RYt)made by the primary sectors (production and trade) are listed as costsand hence recorded in the intermediate inputs of these sectors. Others(RYp + RY/) are shown as disbursement from the value added in thesesectors. Finally, transfers out of household income and other final ex-penditures are listed as purchases (RYC, RY^ in the final demand column.

Table 3.7 provides the corresponding algebraic summary. Note that inlight of the discussion concerning the effects of transfers of value, nogeneral pattern between VA* and VA, or between S* and P, has been pre-sumed to hold. But the rate of surplus value SVV* is shown as beinglarger than the measure of the profit/wage ratio because this general em-pirical pattern is rooted in the fact that V* < W.

3.2.2 Profit-type income can exceed surplus valueWe have seen that whereas royalty payments by primary sectors

to secondary sectors tend to reduce the measure of profit-type incomerelative to surplus value, similar transfers originating in household, gov-ernment, or foreign sectors (i.e., in nonbusiness sectors) tend to makeprofit-type income larger relative to surplus value. At an empirical level,the profit-reducing effect of transfers of value swamps the profit-increasingeffect. But the very fact that two such opposing effects exist implies thatwe cannot say a priori whether or not surplus value will be greater thantotal profit. This only serves to emphasize the theoretical point that aggre-gate profit is the sum of realized surplus value and the net transfer ofvalue between circuits of capital and circuits of revenue (see Section 2.4).


Table 3.7. Marxian and IO measures: Private royalties payments


A, Revenue sideTV* = GOp + GOt

VA* = TV*-C*= RYp + VAp + (GOt)

VA VA

v=wpS* = VA*-V*

-wp

+ RYt)

+ RYp>RYt + RYt')]/Wp'

B. Use sideTP*=GPp + GPt

FP* = TP*-U*= Mt + Mry + (CON-RYc)

NP* = CONWp

SP* = FP*-NP*

= GOp + GOt + GOry

+ (Mry + RYry)VA = G O - M

= VAp + VAt + VAry

W = Wp + Wt + Wry

P = Pn + Pt + Prv

Pt + Pry)/(Wp

GP = GPp -f GPt + GPry

M = Mp + Mt + Mry

FD = G P - U=CON+I

(no corresponding category)(no corresponding category)

y + CON* +1* - CONWp

Note: CON* = CON-RYC and I* = I-RY, (see Figure 3.8).

To obtain an insight into the profit-enhancing effect of transfers ofvalue, it is useful to consider the simple case of household royalty pay-ments in conjunction with the production sector alone. With productionalone and no household royalty payments, aggregate profit is equal toaggregate surplus value ($1400 as in Section 3.1.1). According to our con-vention, this aggregate profit is also the income of the capitalist class.Suppose that the capitalists in turn pay $450 of this personal revenue overto the royalties sector as net interest and ground rent. The royalties sectorwill then have a total business revenue of $450, split into (say) $300 incosts and $100 in profits. Aggregate business profits will now equal theprofits of the production sector ($1400) plus the profits of the royalties


Total Profits= 1500

Figure 3.9. Production and royalties only.

sector ($100), for a total of $1500. Yet aggregate surplus value is $1400.Total profit exceeds total surplus value. Figure 3.9 illustrates these flows,with total profits and total surplus value explicitly mapped out.13

This result is a variant of the one that has always bedeviled the discus-sion of the transformation problem. In both cases, the mystery is solvedonce we recall that monetary profit is the sum of surplus value and any

13 The upper limit to this effect is when all profits of the production sector flow backto the royalties sector (profits are used solely to pay royalties) and all of this flowshows up as royalties-sector profits (there being no input or wage costs in theroyalties sector). In this case, aggregate profits would be twice as large as surplusvalue!


(positive or negative) transfers of value between the (flow) circuit of capitaland all other circuits (see Section 2.4). In the present case, the disburse-ment of dividends out of the profits of the production sector is recordedas a sharing out of profits, not as a deduction from it (unlike payments ofground rent or net interest, which are recorded as costs of business andhence as deductions from production profits). Because dividend paymentsare not treated as deductions from profits, there is no recorded transfer-out of value from the circuit of capital. But when capitalists in turn pay aportion of this dividend income back to the business sector, the correspond-ing business receipt constitutes a recorded transfer-in of value into thecircuit of capital, a portion of which then shows up as additional recordedprofit. It is the particularity of profit-loss accounting that gives rise to thiseffect, not some mysterious creation or negation of value in circulation.

Another way to look at this outcome is to recognize that although sur-plus value is the foundation of modern capitalist profit, some componentsof total profit-type income are not derived from surplus value. The profit-type income of the primary sector is always part of aggregate surplusvalue (see Figure 3.7 and Table 3.6); however, the profit-type income ofthe secondary sector is not included in surplus value, precisely because itssources are already contained within other parts of total value (capturedin the accounts of primary sectors). This is clearest in the simple casein which there are only production and royalties sectors (Figure 3.9).Here, while the profit-type income of the production sector is equal tosurplus value, total profit-type income is greater because of secondary-sector profits.

In actual empirical estimates for the United States, the abstract possi-bility pictured here does not predominate. Indeed, aggregate profit-typeincome P + is roughly 60% of total surplus value, and aggregate profitP is 40%. Moreover, since variable capital V * s W p is roughly 40% oftotal wages W, the rate of surplus value SVV* is generally five timesgreater than the profit/wage ratio P/W (see Section 5.4).

B. PUBLIC SECONDARY FLOWS: GENERAL GOVERNMENT ACTIVITIES

The state sector as a whole encompasses two types of activities. First,there are government enterprises. Depending on the particular type ofactivity in which they engage, such enterprises appear in IO-NIPA ac-counts as part of the production, trade, or private royalties sectors (BEA1980, pp. 27-8), and are treated in the same way as are private enterprisesin those sectors.14 Second, government agencies oversee the maintenance

14 We treat government enterprises in the United States as essentially capitalistenterprises. This need not be the case in other countries.


and reproduction of the social order: police, fire departments, courts andprisons, defense and international affairs, and general administration.All of these are nonproduction activities.

Within conventional national accounts, government receipts consist oftaxes (business and personal, net of subsidies and transfers), fees andfines, rents and royalties, and personal and employer contributions forsocial insurance. Government disbursements consist of the purchases ofgoods and services (including payments to unproductive sectors and gov-ernment employees), transfer payments to persons, net interest paid topersons and foreigners,15 and net subsidies to government enterprises,minus dividends received by government. The government surplus or def-icit is the difference between receipts and disbursements (BEA 1986, pp.ix-xii).

Input-output accounts only partially capture the flows associated withgeneral government. On the revenue side, they only pick up business pay-ments (taxes, fees, net interest paid) to government. Household paymentsto government, like those to the royalties sector, do not explicitly show uphere. On the use side, transfer payments to persons and business are ex-cluded (having been netted out of taxes and fees received by government).

This leaves only two major elements: government purchases of goodsand services G' (which include royalty payments such as ground rent andfinance charges); and purchases of labor power, the wages WG paid togovernment employees. Total government expenditures G = G' + WG. In-put-output accounts treat these two components in quite different ways.Government purchases G' are treated as part of the final use of the prod-uct, and therefore appear under final demand. In keeping with the ortho-dox treatment of royalties, expenditures on net interest and ground rentare treated as purchases of the output of the royalties sector.

Treating G' as part of final use, rather than as an intermediate inputinto some government production activity, is an implicit admission thatgeneral government activities are nonproduction activities. To be consis-tent, one would also have to similarly treat the government purchase oflabor power WG as part of the same nonproduction activity - but this isnot done. On the contrary, IO-NIPA accounts treat government pur-chases of labor power as purchases of a service which is the sole con-stituent of a government net product (and hence of government valueadded). Since these wages do not appear anywhere in the accounts, adummy "government industry" is added to the IO table: its row contains

15 In keeping with the treatment of net interest in IO-NIPA accounts, the net inter-est paid to businesses is redefined as a purchase of a financial service. It is there-fore part of the government disbursements on goods and services.


Production

Trade

GO

Figure 3.10. IO accounts and Marxian categories: General government.

only one entry (WG) under the government column (representing the gov-ernment's purchase of the government industry's net product), and itscolumn contains only one element (WG) in its value-added row (repre-senting the value added of the government industry). Through this device,orthodox measures of gross and net product are each expanded by WG.

From our point of view, the payments made by businesses and house-holds to general government are simply a form of royalty payments. Assuch, the basic principles governing the treatment of royalties also applyhere. Thus, since the accounts of primary sectors already include the orig-inal sources of government receipts, we cannot now count them twice.In our view, neither government commodity purchases G' nor purchasesof labor power WG enter into a production activity; we must exclude notonly the former (as IO-NIPA accounts do) but also the latter (which theydo not). As indicated in Figure 3.10, this means excluding the dummygovernment industry from aggregate measures of output and product.As before, the basic Marxian measures are contained within the primary-sector blocks.

Note that exclusion of the government dummy industry does not implythat we ignore either the government use of actual product (which showsup in the government final-demand column of the production row) orthe personal consumption of government workers (which shows up inthe consumption column of the production row). Both of these items


are genuine uses of the existing total product. By excluding the dummygovernment industry, we simply exclude any expansion of the measureof this product.

Because business payments to government (net interest paid and taxesnet of subsidies) are recorded in value added, their introduction changesthe distribution but not the magnitude of business value added. But sincethe subsequent payment of government wages out of these same revenuesis recorded as the creation of a government net product, the conventionalaggregate measures of gross and net product are expanded by WG.

Business payments to government leave the measure of business valueadded unchanged, so they also leave the measure of business profit-typeincome unchanged (where profit-type income is defined as value addedplus royalties paid minus wages). There being no profit-type income forgovernment, it follows that aggregate profit-type income is unchanged bythe inclusion of general government. On the other hand, since net inter-est paid and indirect business taxes reduce the portion of business valueadded which goes to profit, and since profit taxes reduce the portion ofprofit which firms get to keep, the inclusion of general government re-duces the aggregate measures of pre- and post-tax profit.

Finally, to the extent that the government transfers some of its revenuesback to the royalties sector as (say) ground rent or finance charges, thiswould expand the revenues of the royalties sector. Measured gross output,value added, and even profits of the royalties sector would rise, and withthis so too would the corresponding aggregate measures (since, as we havealready seen, the payment of taxes etc. does not reduce the measuredgross or net output of the business sector). This result is the same as theone derived earlier from household payments to the royalties sector, andincludes the possibility that measured profit-type income could exceedsurplus value.

In summary, royalty payments by primary sectors to the governmentalready show up in the value added of the originating sectors and can-not therefore be counted again if they happen to be transferred to someother sector or group. But orthodox accounts do count (a portion of)such transfers, precisely because they view them as measures of the gov-ernment's output; thus they inflate the measures of total value and totalproduct by the sum of these transfers. Specifically, they count any wagespaid by government to its nonproduction employees as a measure of addi-tional government product (recorded through the creation of a dummygovernment industry), and count any transfer from the government tothe royalties sector as a measure of the additional product created by theroyalties sector. By restricting ourselves to the sum of the gross output


Table 3.8. Public secondary flows: General governmentactivities


A. Revenue sideTV* = GOp + GOt

C* = Mp

VA* = TV*-C*= VAp + GOt

v*=wpS* = VA*-V*

= P + IBT + (Wt + Mt)

S*/V* = [P + IBT + (Wt + Mt)]/Wp

B. Use sideTP* = GPp + GPt

FP* = T P * - U *

= CON + I + G'+Mt

NP*=CONWp

SP* = FP*-NP*= I + G+(CONWt

GO = GOp + GOt + GOry + WG

M = Mp + Mt

VA = G O - M= VAp+VAt + WG

W = Wp + Wt + WG

• P/W = P/(Wp + Wt)

GP = GPp + GPt + GPry + WG

U = Mp + Mt

FD = G P - M

(no corresponding category)


Notes:IBT = indirect business taxes;

P = profit-type income, net of indirect business taxes;P + = profit-type income, gross of indirect business taxes.

and gross product of the primary sectors, we avoid these spurious over-statements of total measured product.

Table 3.8 summarizes the treatment of public secondary flows (exceptfor the issue of net taxes on productive worker wages, which is addressedin Section 3.3). We abstract from private royalty flows here.

3.3 Net transfers from wages, the social wage, and the adjustedrate of surplus valueWhereas royalty payments from primary to secondary sectors do

not change the basic Marxian measures, those which come out of the


wage of productive workers are different. The true measure of variablecapital is the nominal wage of productive workers minus any net royaltypayments made by them. Thus, in order to estimate true variable capital,we should deduct net interest, net ground rent, and net taxes (net of socialbenefit expenditures received) paid by production workers from our ap-parent measure of variable capital.

At a conceptual level, the calculation of net interest and net ground-rent payments is relatively straightforward. But the estimation of net taxespaid requires a comparison between the gross taxes paid by productionworkers and the corresponding transfers and other social welfare expen-ditures (for health, education, roads, parks, etc.) directed back towardthem. These further details are taken up in Section 5.9 and Appendix N.

Once the sum of net royalty paid by production workers NRYwp hasbeen estimated, it must be subtracted from production worker wages andadded to surplus value in order to obtain the true measures of each. Themeasure of surplus value will then be correspondingly larger, as will theadjusted rate of surplus value. Using primes to denote these adjustedmeasures, we have on the revenue side:

V*'=V*-NRYwp = Wp-NRYwp;

S*'=S* + NRYwp;

adjusted rate of surplus value= S*7 V*' = (S* + NRYwp)/( V* - NRYwp)> apparent rate of surplus value = S*/V*.

On the use side, the corresponding adjustment comes in the measure ofthe necessary and surplus products, as follows:

NP*'= CONWp-NRYwp = NP* -NRYwp

SP*'=FP*-NP*'

= Mt + CON* +1* + NRYwp - CONWp;= SP* + NRYwp

adjusted rate of exploitation= SP*'/NP*'= (SP* + NRYwp)/(NP* -NRYwp)> apparent rate exploitation = SPVNP*

All actual calculations appear in Section 5.9 and Appendix N. There, weconfine ourselves to the net tax on variable capital. The estimation of thisnet tax (which may be negative, insofar as social expenditures on work-ers exceed the taxes they pay) is part of a much larger issue involving the


debate that concerns the welfare state and the so-called social wage orcitizen wage (Bowles and Gintis 1982; Shaikh and Tonak 1987). It shouldbe noted that our analysis of state-induced transfers deals with actualempirical flows - that is, with the observed incidence of taxes - corre-sponding to what Ursula Hicks (1946) has called the "social accountingapproach." The further analysis of tax incidence based on some assumedpattern of tax shifting, which would involve a comparison between the ac-tual flows and some hypothetical alternative set of flows deemed to holdin the imagined absence of some taxes, is beyond the scope of this book.

3.4 Foreign tradeWe have tracked down the various forms taken by produced value

as it is absorbed by the trade, royalties, and state sectors by means of acomplex series of value transfers. But this was for a closed economy. Thequestion now is: How are these results modified for an open economy?

In the case of an open economy, our object is to distinguish betweendomestically produced value and domestically realized value. The dif-ference between the two arises from transfers of value which cut acrossnational boundaries. There are three basic causes of these internationaltransfers: foreign trading margins on exports and imports, which transfervalue between nations; deviations between purchasers' prices and values,which do the same thing; and international flows of wages and salaries,dividends, interest, et cetera, which transfer value directly in the form ofmoney. The first two issues will be addressed in the treatment of inter-national commodity trade (merchandise trade accounts) and the thirdin that of international payments for "factor services" (rest-of-world ac-counts). Before we proceed, however, we need to specify what we meanby national economic boundaries.

The precise distinction between domestic and foreign economic activ-ities depends on the purpose of the analysis. For instance, we can define"domestic" in two basic ways: in terms of the national boundaries of thecountry involved; or in terms of the nationality of the person or orga-nization in question. We will adopt the former, because our purpose is tomeasure the production of value within a given nation. This use of na-tional boundaries to define domestic activities implies that location takesprecedence over nationality. Thus foreign workers or corporations locatedwithin the United States are counted as part of the domestic sector.

Transportation activity involves a further consideration. A cargo loadedonto a domestic carrier can cross over to foreign territory before it isunloaded at its foreign destination. Along the way, it may cut across theterritory of some third nation, or cross neutral space such as the ocean.Alternately, the domestic carrier may hand over its cargo to a foreign


carrier at some point before the foreign port of call. The complicationsarising from all of these instances can be handled by extending the defini-tion of the national economic boundary to encompass domestic carriers.On this basis, we will count an import as entering the United States eitherwhen it is unloaded at a U.S. port or when it is transferred onto a U.S.carrier. Similarly, an export will be counted as leaving the United Stateseither when it is loaded onto a foreign carrier or when it is unloaded at aforeign port of call.

3.4.1 GDP, GNP, and the rest-of-world (ROW) accountsOrthodox national accounts distinguish between gross domestic

product (GDP), which seeks to measure "the output of goods and ser-vices produced by labor and property located in the United States," andgross national product (GNP), which corresponds to "the goods and ser-vices produced by U.S. residents" (Tice and Moczar 1986, p. 28). Thefirst measure is based on the location, the second on the nationality, ofthe corporations or persons involved.

The GNP measure of national product is derived from the GDP mea-sure by adding the rest-of-world (ROW) accounts, because ROW flowsare designed to represent the difference between the two concepts of na-tional product. GDP counts the wages and salaries, dividend and interestearnings, and retained earnings of foreign persons and corporations lo-cated in the United States. On the other hand, it excludes the same earn-ings of U.S. nationals and U.S. corporations located abroad. GNP, whichis structured according to nationality, excludes the first set and includesthe second. The ROW accounts are simply the difference between thesecond and first sets, so that adding them to GDP produces GNP (BEA1980, pp. 29-32).

For our purposes, it is the GDP concept which is the relevant startingpoint. Since sectoral accounts in both NIPA and IO tables are structuredaccording to the GDP concept, we can work directly with them and ig-nore the ROW accounts altogether. With this out of the way, we proceedto the analysis of transfers of value brought about by foreign tradingmargins on exports and imports, even when commodities sell at final(purchasers') prices proportional to values. We then extend the analysisto cover purchaser price-value deviations, ending up with a general sum-mary of the transfers of value induced by international trade. This willhelp us separate out domestically produced value from the realized valuesthat are recorded in conventional accounts.

3.4.2 Transfers of value in international tradeWithin one nation, the production sector transfers a portion of

the value of its product to the trading sector by selling it at a (producer's)


Table 3.9. Domestically produced and usedcommodities

Producer's price: $ 80Manufacturer's price: $70Transport margin: $10

Trade margin: $ 20Purchaser's price: $100

price below its value. The difference between the two sets of sales is therevenue of the domestic trade sector (the total trading margin on all goodssold). This holds even when commodities are sold to their final users at(purchasers') prices proportional to their values.

Exactly the same thing occurs when a domestic producer exports acommodity. In this case, however, the value transferred to the trade sec-tor may be split up between domestic and foreign trading capitals, so thatonly a portion of the total value is retained within the country. Exportstherefore transfer value out of a nation, ceteris paribus, in an amountequal to the trade margin of the foreign trading capital. The oppositeholds for imports. The domestic trading capital captures a portion offoreign value by acquiring a commodity below its final selling price (whichby assumption is equal to its value). Imports transfer value into a coun-try, other things being equal.

Tables 3.9-3.11 illustrate these arguments. In Table 3.9, we see thatin the case of a domestically produced and used commodity (say steel),the total value of the product (equal to its purchaser's price of $100) issplit up between the production sector ($70), the domestic transportationsector ($10), and the domestic trade sector ($20). On the assumption thatthe transportation in question is productive transport, a total value of$100 is created by the production sectors (steel producers and transport-ers), of which $20 is transferred to the domestic trade sector by virtue ofthe fact that the total producers' price ($80 = $70+$10) is less than thetotal value.

The same basic principle applies to exports and imports, with the dif-ference that the connection between producers, transporters, and tradersnow cuts across national boundaries and thus gives rise to internationaltransfers of value. Keep in mind that our definition of a nation's eco-nomic boundary encompasses any transport by national carriers.

Table 3.10 applies this rule to the case of an export. The domestic ex-port price - the price received by domestic producers, transporters, andtraders - is defined as the domestic port price plus any cost of international


Table 3.10. Exports

X* = domestic export price=value retained: $ 70

=domestic port price ($55)+ international transport by domestic carriers ($15)

Foreign margins = value transferred abroad: $ 30= international transport by foreign carriers ($5)

+ foreign importer's duties ($3)+ foreign importer's insurance ($2)+ transport within foreign country ($13)+ trade within foreign country ($7)

X+ = foreign purchaser's price: $ 100

Table 3.11. Imports

IM* = domestic import price = value paid for: $ 60= foreign port price ($50)

+ international transport by foreign carriers ($10)

Domestic margins = value transferred in= value received—value paid= $100-$60: $ 40

= international transport by domestic carriers ($5)+ domestic import duties ($7)+ domestic importer's insurance ($3)+ domestic transport of imported goods ($15)+ domestic trade in imported goods ($10)

IM + = domestic purchaser's price: $ 100

transport by domestic carriers.16 This represents that portion of the totalvalue of the commodity which is retained within the country. The re-mainder of the export's final selling price (its foreign purchaser's price),which for the moment is assumed to be equal to the commodity's value,represents the value which is transferred abroad.

Table 3.11 examines the case of imports. Here, the outcome is reversedsince it is the foreigners who retain only a portion of the value produced intheir country, with the rest being captured by domestic importers, trans-porters, and traders. The domestic import price is therefore the foreign

16 The structure of merchandise trade accounts is described in BEA (1980, pp. 4,20, 22-4).


port price plus any costs of international transport by foreign carriers.This total is, of course, the same as the value retained by the foreigncountry.

It follows that value can be transferred between nations - even whenall final selling prices are equal to values - depending on the balance be-tween the value transferred in through imports and the value transferredout through exports. This is a systematic effect whose direction is tied tothe location of the commodity within foreign trade (as export or import),quite different from the indeterminate direction of transfers associatedwith purchaser price-value deviations. Relative producer prices, includ-ing domestic export and import prices, are relative prices of productionwhose deviation from relative values depends on the relative organic cap-itals of the sectors and the relative efficiency of the capitals within a givensector (Shaikh 1980a). But all producer prices are less than purchaserprices because of the intervening domestic and foreign trading margins.Thus the transfers of value due to trading margins are unidirectional,from producers to traders. On the other hand, purchaser price-value de-viations are the synthesis of factors causing relative producer prices todeviate from relative values and factors causing absolute producer pricesto be less than purchaser prices.

For the analysis of international transfers of value, the trading-margintransfers are clearly more fundamental than those arising from purchaserprice-value deviations. The latter are easily introduced into the analysis.Any (positive or negative) deviation between purchaser prices and directprices (prices proportional to values) must be added to the previouslyanalyzed deviations between domestic import and export prices and thecorresponding purchaser prices. As shown in what follows, the overalltransfer can be derived directly by substituting direct prices for purchaserprices in Tables 3.10 and 3.11. But it is more useful to show the two setsof deviations separately, since they are determined differently. The mea-sures Tx, Tim, and T are constructed so that a transfer in is positive and atransfer out is negative:

X*, IM* = domestic prices of total exports and imports;

X"1", IM+ = purchaser prices of total exports and imports;

Xv, IMV = direct prices (values) of total exports and imports.

Tx = transfer of value on exports

= transfer out on foreign margins

+transfer on price-value deviations of exports

= (domestic export price - foreign purchaser price)

+ (foreign purchaser price — direct price)


= domestic export price - direct price of exports

Tim = transfer of value on imports

= transfer in on domestic margins on imported goods

+ transfer on price-value deviations of imports

= (domestic import price — domestic purchaser price)

+ (domestic purchaser price - direct price of imports)

= domestic import price — direct price of imports

T = Net transfer of value through foreign trade = Tx - Tim

= (X*-IM*)- (X V -IM V ) .

The net transfer of value T (expressed in its money equivalent) is there-fore the difference between the conventional realized-value measure ofthe balance of trade (X* — IM*)17 and the corresponding labor value mea-sure (Xv —IMV). This means that adding T to the revenue and use sidesof conventional accounts will replace the realized values recorded therewith the corresponding produced values. The resulting total value andtotal product will then correctly measure produced, rather than realized,magnitudes.

In estimating the net international transfer of value T, it is useful toexpress it in a somewhat different form. Let

d,, s (X* - X v ) / X * = the percentage deviation of basic exportprices from direct export prices (values),and let

dim B (IM* - IMV)/IM* = the percentage deviation of basicimport prices from direct importprices (values); then

T = dx.X*-di m.IM*.The last expression is the most convenient one for the empirical estima-tion of net transfers. Note that if trade is balanced (X* = IM*) then the

17 In actual practice, NIPA measures differ slightly from the domestic export andimport prices defined here. Exports are valued in orthodox accounts at theirdomestic port price alone, which makes their valuation smaller than our defini-tion of the domestic export price by the cost of their shipping on domestic car-riers. On the other hand, noncomparable imports are similarly undervalued rela-tive to our measure, since orthodox accounts leave out the cost of shipping byforeign carriers. The net difference between the orthodox trade balance measure(X - IM) and our measure of net realized trade balance (X* - IM*) is quite small;we therefore ignore it in what follows.


transfer of value depends solely on the difference in export and importprice-value deviations and on the level of trade: T = (dx - dim) • X*. Con-versely, if the price-value deviations are the same for exports and imports(dx = djm = d) then the net transfer depends solely on the level of thisaverage deviation and on the balance of trade: T = d-(X* -IM*). If weestimate d at 12% (see Section 5.10) then T is quite small relative to S*and can safely be neglected.

In summary, the production accounts within any one country will re-cord only domestically realized values. To correct for this, it is necessaryto adjust surplus value on the revenue side, and the recorded trade bal-ance X* — IM* on the use side, by subtracting the amount of the net trans-fer of value T. This replaces realized surplus value and the realized tradebalance X* - IM* with produced surplus value and the produced tradebalance Xv - IMv. The resultant measures of total value and total productwill then reflect domestic production alone.

3.5 Noncapitalist activities and illegal activitiesIn principle, noncapitalist activities should be distinguished from

capitalist ones. But in the official accounts of an advanced capitalist econ-omy such as the United States, such activities are either merged into thecorresponding capitalist sectors (e.g., self-employed mechanics are treatedas unincorporated enterprises within the automobile repair industry) orthey are left out altogether (most notably in the case of the householdsector). We are unable to transcend these limitations in the data, althoughwe do provide estimates of the impact of unpaid household activities. Aswe saw in Chapter 1, unofficial extended accounts do address such issues.

The one case in which noncapitalist activities are explicitly treated is adummy industry designed to capture the output of paid household laborsuch as that of "maids, chauffeurs, and baby sitters" (BEA 1980, p. 28).As in the case of the government industry sector, the household industrydummy sector has only one entry in each row and column, in each caserepresenting the estimated wages of the workers involved. Even assumingthat such labor is mostly production labor, it is generally not capitalistproduction labor.18 The cost of this labor power therefore cannot be in-cluded in variable capital. The household industry sector, like the gov-ernment industry sector, must be excluded from our measures of totalvalue and total capitalistic product. Both are unproductive of capital,

18 To the extent that the household workers in question are employed by a capitalistenterprise (e.g., a capitalist housecleaning service), their labor in the householdis simply the application of labor power that has first been exchanged againstcapital (when they were hired by the housecleaning firm). It is therefore produc-tive labor, not merely production labor; but then it shows up under productiveservices.


albeit for different reasons: the government industry is a nonproductionsector, and the household industry is a noncapitalist production sector.

3.6 Summary of the relation between Marxian and conventionalnational accounts

3.6.1 Overall summaryIn a closed economy, the total value produced within a country

is realized in the sales of the primary (i.e., production and trade) sectors,whose combined revenue represents the total price (money equivalent)of the output created in the production sector. Production involves thecreation or transformation of the useful properties of material objects ofsocial use (use values). It includes goods created in agriculture, mining,construction, public utilities, manufacturing, and government productionenterprises, in addition to services such as productive transport and ahost of other productive services (e.g., hotels, haircutting salons, repairservices, entertainment, health and educational services, and householdproduction labor).

Trade circulates use values, redistributing them from seller to buyer inreturn for a counterflow of money. Trade encompasses wholesale/retailtrade, building and equipment rentals (piecemeal sales), distributive trans-portation, and government trading enterprises. Two steps are required toderive an estimate of the building and equipment rental sector. First, thefictitious components of the real estate and rental sector, which consistof imputed wages and profits of private homeowners (who are treated asbusinesses renting their own homes to themselves), must be excised fromthe accounts on both revenue and use sides (Section 3.1.3 and Figure 3.7).Second, the remaining nonimputed real estate and rental flows must besplit into building and equipment rental (which is included in total trade)and land rental and sales (which becomes a part of the royalties sector).

The value which is realized in the primary sectors can be further recir-culated through a series of transfers (which we call royalty payments)between the primary sector and various secondary sectors. These secon-dary flows involve the payment of net interest, finance charges, groundrent, fees, royalties, and taxes. The sectors receiving these can be groupedinto the (private) royalties sector (finance, insurance, ground rent, etc.)and the general government sector. The two are treated as separate partsof the royalties sector.

Because the original sources of the revenues of the secondary sectors arealready counted in the revenues of the primary sectors, we cannot countthem again in the measure of the total product and its total value. Secon-dary flows are part of total transactions, but not part of total product. In


the case of the royalties sector, this means leaving out the royalties-sectorcolumn on the revenue side; and leaving out royalty payments from the con-sumption, investment, government, and net-trade columns on the use side,since these are transfer payments, not purchases of use values (Figure 3.8).

The same principle applies to the general government sector (govern-ment enterprises are treated as part of other sectors, according to theactivity in which they engage). As a royalties-receiving sector, its revenues(taxes and fees) derive from the already counted flows in the primary sec-tor, and thus cannot be counted again in the measure of the total product(although these revenues may add powerfully to total transactions). InIO tables, this means excluding the government industry dummy sectorfrom the revenue side, as well as the corresponding row entry in the final-demand government column on the use side (Figure 3.10).

The next step is to extend the analysis to the case of an open economy.Since our purpose is to measure domestically produced value and surplusvalue, the GDP concept (which measures output produced within the na-tion) is preferable to the GNP concept (which measures output producedby U.S. persons or corporations anywhere in the world). We thereforeexclude the rest-of-world industry column and row from our coverage ofproduction and trade, because this is merely the balancing item betweenthe GDP and the GNP concepts. In addition, since foreign trade inducestransfers of value, the value realized within the primary sectors reflectsnot only the value produced within the country but also any (negative orpositive) international transfers of value. We would therefore have toadjust for these transfers in order to recover the magnitude of producedvalue. This could be done by adding the net international transfer ofvalue T to realized surplus value on the revenue side, and to the realizedtrade balance X* — IM* on the use side, once the basic Marxian totalshave been derived.

Finally, input-output tables list a dummy industry called the householdindustry; it is designed to represent the output of the domestic services ofmaids, chauffeurs, and baby-sitters. The money value of this output istaken to be equal to wages alone, since the activities in question are non-capitalist. The only entries associated with this dummy industry appear inthe value-added row of the household column and in the household rowof the consumption column, both equal to the wages of domestic workers.We exclude this sector from our coverage of total value and product, onthe grounds that paid domestic labor is largely noncapitalist activity.

Adjusting conventional IO tables in the ways just indicated (except forthe transfer of value T), we can map out the overall relation between IOaccounts and Marxian categories as depicted in Figure 3.11. A dash in acell indicates that it is empty by construction (as in the case of most of

f 3 I I

VA If!

Dum

my

Sect

ors

Roy

. 8.

To

tal

Tr

ad

ew f

Pro

du

ctio

n

Agr

ic.

Man

uf.

c n

Prod

.Se

rvic

,

Whs

le.

&R

et.

Bld

g.R

enta

l

Gov

t.Tr

adin

g

H o ET H

11

Gro

und

Ren

tal

Fina

nce

Aln

s.

fG

ovt

Ind.

Hsh

ld.

Ind.

2R

OW

Ind.

ro

3 s o-

ia


those associated with dummy sectors). Blank cells, or those with xx inthem, contain (or could contain) entries; dots in cells indicate continua-tion of the existing pattern. The Marxian revenue-side flows are indicatedby the area within the bold rectangle, and the corresponding use flows bythat within the dotted rectangle. Value added is broken down here intowages W (employee compensation), indirect business taxes IBT, andprofits P (property-type income), as in actual IO tables. For reasons dis-cussed previously, neither the royalties sector nor the dummy governmentand household industry sectors appear in the measure of total value.

Table 3.12 provides the corresponding algebraic summary. As always,the subscripts p, tt, and ry refer to the production, total trade, and royal-ties sectors, respectively. The subscript dy has been added to refer to theoverall dummy sector, while g, hh, and row refer to the government,household, and rest-of-world dummy industries, respectively. None ofthe dummy industries have any intermediate inputs, but the ROW in-dustry does include property income. Table 3.12 also summarizes thosepatterns which can be said to hold in general, either theoretically or em-pirically. By and large, the Marxian measures of gross and net productare smaller than the corresponding orthodox measures, since the latterinclude many transactions that we would exclude from measures of pro-duction. We show surplus value as larger than the orthodox measures ofprofit-type income because this is empirically true, even though surplusvalue can in principle be smaller (see Section 3.2.2).

3.6.2 The balance between the two sides of the Marxian accountsIn order to establish the balance between the revenue and use sides

of the Marxian accounts, it is helpful to recall that input-output accountsare constructed in such a way that row sums equal column sums for allindustries. Three such identities are particularly useful (cf. Figure 3.11):

(a) GO = GOp + GOtt + GOry+GOdy

= GP = (Mp + Mtt + Mry) + (RYp + RYtt + RYry) + CON

(b) GOry = GPry - RYp + RYtt + RYry + RYcon + RYj + RYx.im + RYg;(c) GOdy = GPd

= Wg+HHc o n

We will show that the equality of TV* and TP* is predicated on theseidentities. Looking once again at Figure 3.11, TV* = TP* implies that

(d) TV*

p y

+ (CON - RYcon - HHcon - ROWcon)+ (I-RYi) + [ (X-IM)-RYx_ i m -ROWx _ i m]+ (G-RY g -W g -ROW g ) .

Table 3.12. Marxian and IO measures: Overall summary


A. Revenue sideTV* = GOp + GOtt

C* = Mp

VA* = TV* - C* = GOp + GOtt - Mp

= (Mp + RYp + VAp)Ytt + VA t t ) -M p

GO = GOp + GOt

= VAp + VAf,+ (RYp + RYtt + Mtt)

V*=Wn

= VA*-V= (Pp+Ptt + IBTtt)

S*/V* = (IBTp

B. Use sideTP* = GPp + GPt,

M p t

+ RYtt + Mtt)/Wp

= (MP + Mtt + Mry) + CON*+ I* + (X*-IM*) + G*

U* = Mp

FP*=TP*-U*= CON* + I* + (X*-IM*)

+ (Mtt + Mry)

NP*=CONWp = Wp

M = (Mp + RYp) + (Mtt + RYtt)+ (Mry + RYry) + (Mdy + RYdy)

VA = G O - M= VAp + VAtt + (VAry + VAdy)

< w=wp+wtt+wry+wdy

P+ = profit-type income*= V A - W = P + IBT

+ (IBTp + IBTtt +dIBTiy + IBTdy)

(Pp + Ptt + Pry + Pdy)/( Wp + Wtt +

< GP = GPp + GPtt + GPry + GPdy

= (Mp + Mtt + Mry) + (RYp + RYtt + RYry)

F D = G P - U

SP* = FP*-NP*= (CONWnp + CONC)* +1*

+ (X* - IM*) + G* + (Mtt + Mry)



Notes:CON* = (CON - RYcon - HHc o n - ROWcon);c

X*-IM* = [(X-IM)-RYx_i m-ROWx _i m];G* = (G - RYg - Wg - ROWg).

a A naive measure of surplus value would be the sum of all profits, rents, interest, and taxes:S*'=VA + (RYp + RYtl + RYry)-W = P + IBT + (RYp + RYtt + RYry). We make use of this inour technique for approximating the rate of surplus value in Section 5.12.b Total consumption CON = CONWp + CONWnp + CONC, where CONWP = consumptionof productive workers, CONWnp = consumption of all other workers, and CONC = con-sumption of capitalists. Thus CON-CONWp = CONWnp + CONC.c As is evident from the discussion in the text, the Marxian measure of consumption CON*excludes the transfer payments RYcon, HHcon, and ROWcon, while the conventional measureof consumption CON includes them. Thus CON* = CON-RYc o n-HHc o n-ROWc o n. Theexpressions for I*, (X —IM)*, and G* are derived in the same way.


In expression (a) we can move the term (GOry + GOdy) to the right-handside and expand it by means of expressions (b) and (c) to obtain

GOp + GOtt s (Mp + Mtt + Mry) + (RYp 4- RYtt + RYry - GOry) -I- CON +1

+ ( X - I M ) + G-GO d y

= (Mp + Mtt + Mry) + (CON - RYcon - HHcon - ROWcon)

+ (I-RY^ + [ (X-IM)-RYx_ i m -ROW x_ i m ]

+ (G-RY g -W g -ROW g )

But the preceding expression is simply the equality TV* = TP*, as canbe seen by comparing it with expression (d). It follows that VA* = FD*and S* = SP*, since these latter two relations are derived by subtractingequal elements from TV* and TP*, respectively.

Marxian categories and national accounts:Labor value calculations

The previously derived mappings describe the relation between input-output accounts and the money value form of Marxian categories, onboth the revenue and use sides of the accounts. We now turn to the cor-responding calculation of the labor value form of these same categories.In what follows, we will outline a procedure first developed in Shaikh(1975) and extended and applied by Khanjian (1989). Only the basic ele-ments will be presented here, since a fuller development is beyond thescope of this book.

4.1 Calculating labor value magnitudesLet us begin by recalling our money value mapping previously

summarized in Figure 3.11 and Table 3.12. Figure 4.1 is a simplified ver-sion of Figure 3.11. In it, we have explicitly labeled elements of the pro-duction and trade rows so as to facilitate later discussion. Thus the (pur-chaser) price of the total intermediate input of the productive sectorsMp = (Mp)p + (Mp)t, where (Mp)p represents the total producer price ofthe commodities used as intermediate input in the productive sectors1

and (Mp)t represents the trading margin on these same goods. The samebreakdown holds for all input and final-demand elements. In addition,final demand has been considered into two main categories: the consump-tion of productive workers CONWp; and surplus demand SD, which isthe remainder of final demand - equal to the sum of the consumption ofunproductive (trade and royalties) workers and capitalists, investment,net exports, and government expenditures. As always, constant capital inmoney form C* = Mp, and Marxian value added VA* and final productFP* are shown in cross-hatched areas.

1 We recall that, at a theoretical level, depreciation is part of intermediate inputs.

78

Labor value calculations 79

GO

• "Surplus Demand"^ (CON)wu+CONc + (X-rM) +

Figure 4.1. IO accounts and Marxian categories: Condensed form.

It should be noted that Figure 4.1 collapses all the productive industriesinto one sector. For aggregate money value calculations, this is adequatebecause we are only interested in the sum of money values. But for laborvalue calculations, we generally need to know the individual elements ofthe productive sectors. Therefore we may also think of the production-row elements in Figure 4.1 as matrices representing corresponding par-titions of the matrix pictured in Figure 3.11. We will use the notation(Mp)p,Mp,... for the sum of money values, and (Mp)p,Mp,.. . to repre-sent corresponding matrices.

The numerical examples in our text are constructed on the assumptionthat selling (i.e. purchaser) prices are equal in magnitude to labor values.2

Indeed, all these examples were predicated on the same physical and rev-enue flows: a total product whose labor value TV = 2000 hours and totalselling price TV* = $2000, composed of 400 in production inputs (C =400 hr, C* = $400) and 1600 in value added (of which 200 represents thewages and consumption of production workers and the rest surplus value,so that V = 200 hr, V* = $200 and S = 1400 hr, S* = $1400). The purposeof all of this was to allow us to check that the various elements add up tothe correct totals, no matter how complicated the transfers of value. Italso ensured that any discrepancies that arose between individual Marx-ian categories and their orthodox counterparts were due solely to differ-ences in their concepts, not to price-value deviations.

As noted earlier, for the money form of Marxian categories, we needto estimate the purchaser price of various commodity bundles becausethese are the final selling prices. However, since input-output tables are

2 We assumed that purchaser prices were proportional to labor values, and alsothat the constant of proportionality was $l/hr (see Section 3.1.1).


constructed in terms of producer prices, this means that we must take thesum of the producer price and the trading margin of the commodity bundlein question. Thus the purchaser price of productive inputs Mp = (Mp)p +(Mp)t. Similarly, the purchaser price of the total product (the total sumof prices) is TP* = GOp + GOt - that is, the sum of the producer price ofproductive sectors GOP and the total revenue of the trading sector GOt

(which is the trading margin on the total output).It is important to note that while there is enough information in stan-

dard (i.e. producer-price) input-output tables to calculate the purchaserprice of aggregate inputs, outputs, and final demand components, thereis not enough to calculate the purchaser price of individual commodities.For instance, theyth column of an input-output matrix lists the producerprice of various individual intermediate inputs [(M)p]/y, but only liststheir combined trade margin [(M)t]y in that trade row of that column.Similarly, the gross outputs [GOp]y of various productive sectors are theproducer prices of their products, while the gross output of the tradingsector GOt is the combined trading margin on all productive sector out-puts. Because the trade margins are always combined ones, we lack theinformation required to estimate individual purchaser prices.

For labor value measures, we need to calculate the labor value of var-ious commodity bundles. Since individual commodities in actual input-output tables are listed in producer prices, we can calculate their laborvalues by multiplying the yth commodity by its labor-value/producer-price ratio A*. The first task, then, is to calculate these A*s. The secondstep is to apply these solely to the producer price components of variouscommodity flows.

If input-output tables recorded actual quantity flows (rather than moneyflows), we could calculate labor values Ay by adding the hours of produc-tive labor3 worked to the labor value of the inputs used in production.For the production sector j , let:

Ay = labor value per unit output;hpy = hours of productive labor per unit output;

app/y = quantity of the /th production input used per unit output =

Xy = quantity of output.Then unit labor values must satisfy the relation

3 Ideally, one should adjust labor time flows for skill differences. If sectoral wage-rate differences are correlated with skill differences, then we could use wage ratesas a first approximation. But this can cause problems (see the discussion of Wolff(1975, 1977) in Section 6.1.2).


If we define row vectors A and hp, with elements Ay and hpy, respec-tively, as well as an input-output coefficients matrix of (productive) in-puts app with elements app/y, then we may equivalently write:

A = hp+A*app;A = hp(I-app)-1.

All this would apply if input-output tables were in quantity terms. Butactual input-output tables are constructed in terms of money flows eval-uated in producer prices, not quantity flows. This means that instead ofinput quantity coefficients a/y we actually have input money value coeffi-cients app* = P/-app/y/py, where p/, py represent producer prices. The cor-responding labor coefficients are hp* = hpy/py. Our empirical equationfor labor values now reads:

A* = hp* + A*.app*;A* = hp*(I-app*)1,

where the estimated unit values A* now represent labor-value/producer-price ratios (Shaikh 1984, apx. B). We have:

A* = the row vector of labor-value/producer-price ratios;A*=A/py,

whereAy = unit labor values;py = unit producer prices.

Since the A*s are ratios of labor values to producer prices, we must becareful to apply them only to the producer-price components of commod-ity flows. Thus the labor value of productive inputs C is derived by multi-plying the producer price of the /th input by the labor-value/producer-price ratio A*. In terms of Figure 4.1, this means that the labor value ofconstant capital is calculated by multiplying only the matrix of elements(Mp)p by A*. Yet the corresponding money value of constant capital C*,which is the purchaser price of productive inputs, is equal to their pro-ducer price (Mp)pplus the trading margin on these same inputs (Mp)t. Inour previous examples, in which purchaser prices are equal to labor values,the two magnitudes C and C* will be equal under this calculation proce-dure. The difference in their mode of calculation is due solely to the factthat input-output tables are cast in terms of producer prices.

The same issue arises in the calculation of the labor value of produc-tive labor power V. Given some estimate of the consumption basket ofproduction workers CONWP, the labor value of this is the labor-value/producer-price ratio vector A* multiplied only by the producer price com-ponent (CONWp)p (see Figure 4.1). On the other hand, the money valueequivalent V* is the sum of both the producer-price elements (CONWp)p


Table 4.1. Labor value and money value measures

Money value measures Labor value measures

A. Revenue sideC* = Mp = (Mp)p + (Mt)p C=A*.(Mp)p

VA* = VAP + VAt + RYp + RYt VA = Hp = total hours of productive labor-I- (Mp)t + (Mt)t in the economy as a whole

V* = Wp = CONWP V = A * • (CONWp)p

= (CONWp)p + (CONWp)t

sB.

UFP

NP

SP

* = VA*-V*Use side* = Mp = (Mp)p + (Mt)p

* = (Mt)p + (Mt)t + (Mry)p

+ (Mry)t + (CONWp)p

+ (CONWp)t + SDp -f SDt

*=V* = CONWP

= (CONWp)p-f(CONWp)t

* = FD*-V*

S = H p - V

U = A*.(Mp)p

FP=A*-[(Mt)P + (Mry)p

+ (CONWp)p + SDp]

NP = V = A*.(CONWp)p

SP = FP-NP

and the corresponding trade margin (CONWt)p. Similarly, the labor valueof the total product TP is the sum of the labor value of constant capitalC and the value of labor power V (whose calculation was discussed pre-viously) and the labor value of the surplus product (calculated as the prod-uct of the vector A* and the matrix of the producer prices of surplus de-mand components SDP in Figure 4.1). Table 4.1 summarizes these results.Khanjian (1989) provides many detailed numerical illustrations of the con-sistency of this procedure, based on an unpublished schema set out byShaikh in 1975, so we will not pursue the issue any further here.

We may illustrate the procedures outlined here by using our basic nu-merical example. Figure 4.2 is a numerical example of the basic flows inFigure 4.1, with the value-added row broken down into wages and prof-its, and with the associated labor flows for each sector shown explicitlybelow the main table.4 This example is particularly simple because it con-tains only one productive sector, but all procedures we illustrate gener-alize readily to the general case of n productive sectors. Figure 4.3 repre-sents the resulting input-output coefficients matrix a* and correspondinglabor coefficients vector h* (derived by dividing production, trade and

4 By construction, in all numerical examples the aggregate labor value added isHp = V + S = 1600 hr, while the aggregate wages of production workers are Wp =$200. This implies an hourly wage rate of $V*. The labor flows in Figure 4.2 arederived by dividing the sectoral wage bills by this wage rate.


Production

Trade

RoyaltyPayments

WAGESPROFITS

GO

LABORFLOWS(Hp)

Production

200 . ^ ^

200

' ' • • • « » • . ' " • : :

a o o • • • • . . " '•••

• , : * » ' : - ; <

1000

1600

Trade

"•- ""•. « o S

• \v

\ 4 a b •• • • ' • • • '

,.. ;•-.;,. •••'ijtfv.-,-Vc-',

1000

3200

Royalties

• • • j f t - : ^ • > ; • • • '

~

100100

250

soo

F i n a l D e i

CONWp

. - • • • • l o o ^ '•'//-•'•O

n a n d

SD*

• '-&$•'.•"•

-

GP

1000

1000

250

* "Surplus Demand"= (CON)Wu+CONc + (X-IM} +

Figure 4.2. Production, trade, and royalties sectors.

a* =

1/10 1/10

1/5 1/10 1/10

1/10 3/20

16/5 16/5

Figure 4.3. Input-output coefficients matrix and labor coefficientsvector.

royalties sectors' column entries, and their labor flow by their respectivegross outputs). Neither the value-added and gross-output rows, nor thefinal-demand and gross-product columns, enter into a*.

In Figure 4.3, the producer-price element app* of productive sectorinputs, and the productive labor coefficient hp*, are each outlined in arectangle. We will write these as (one-element) matrices and vectors, soas to illustrate the general procedure. Thus

app* = [1/5] [$/$];

hp* = (8/5) [hr/$];

A* = hp*-[I-app*]-1 = = 2 [hr/$].


Table 4.2. Calculations of labor value flo ws:Numerical example

Value sideC = A*-(Mp)p = 2-200 = 400

VA = Hp=1600

V = A* • (CONWp)p = 2 • 100 = 200

S = V A - V = 1600-200 = 1400

TV = C + V + S = 2000

Use sideU = A*.(Mp)p = 400

= 2 • (100 -I- 25 +100 + 575) = 1600

NP = V = 200

SP = F P - N P = 1600-200 = 1400

TP = U + NP + SP = 2000

Because there is only one productive sector, the calculated A* = 2 hr/$should represent the ratio of the labor value of the total product TV to itsproducer price GOP (the input-output gross product of the productivesector). This is clearly the case, because by construction TV = 2000 hrand GOP = $1000. Applying the formulas in Table 4.1 to the numbers inFigure 4.2, we correctly recover the labor value flows (in hours of abstractsocially necessary labor time) which underly the money flows depicted.Table 4.2 displays the results.

The mappings shown in Tables 4.1 and 4.2 are consistent, in the sensethat they give the same magnitudes in value terms and in price terms whenunit purchaser prices are equal to unit values (compare the value measuresof Marxian measure flows in Table 4.2 to their money value counterpartsin Table 4.1). In this way, when prices deviate from values, the resultingdiscrepancies between value magnitudes and their price forms are duesolely to the price-value deviations themselves. In actual input-outputtables, where purchasers' prices generally do differ from values, we canthen interpret the deviations between value and money magnitudes as ameasure of the aggregate effects of price-value deviations. This effect isgenerally small. For instance, using the procedure outlined here, Khanjian(1989, p. 109, table 19) finds that the money rate of surplus value S*/V*and the labor value rate S/V differ by only 6°7o-9% in all the years stud-ied. He also finds that the former is consistently lower than the latter.Further details may be found in Section 5.10.


Table 4.3. An inconsistent (symmetric) mapping between Marxian andIO categories: Use side

Money value measures Labor value measures

U*' = C*' = (Mp)p = 200($) U = C = A*.(Mp)p = 400(hr)NP*'=V* = (CONWp)p = 100 NP = V = A*.(CONWp)p = 200FP*' = (Mt)p + (Mry)p + (CONWp)p FP = A*.[(Mt)P + (Mry)p + (CONWp)p

+ SDP +SDP]= 100 + 25 + 100 + 575 = 800 =2-(100 +25+ 100 +575) = 1600

SP*' = FD*'-V*'=700 SP = FP-NP = 1400

However, observed differences in money and labor value ratios will beindicators of price-value deviations only if the mapping involved is con-sistent in the sense just described. If it is not, then the two sets of magni-tudes would differ even when purchaser prices are equal to labor values,simply because the calculation procedure is inconsistent.

It is easy to see how an inconsistent procedure might evolve. As indi-cated in Tables 4.1 and 4.2, only the producer-price components enterinto the value calculations, whereas both the producer price and the trad-ing margin enter into the money calculation. For instance, the necessaryproduct in value terms is NP = V = A* • (CONWp)p, whereas in price termsit is NP* = CONWp = (CONWp)p + (CONWp)t. If one has not derivedthe detailed representation of the money form, as we have attempted todo, then it is tempting to make the price form symmetric with the valueform. As we can see from Figure 4.1, this would mean leaving out all thetrade row and column elements from the revenue- and product-side cal-culation of the money forms - in effect, treating the trade sector as aroyalties sector on the grounds that both are "unproductive." This falsesymmetry would then yield estimated money magnitudes that would besmaller than corresponding value ones, even when prices were equal tovalues. The procedure would be inconsistent, and the levels of moneymagnitudes would be underestimated. Table 4.3 illustrates such a sym-metric - and hence inconsistent - procedure, using the (more complex)product side of the accounts. The revenue side will of course yield thesame discrepancy.

Note that, in our numerical example, the inconsistent procedure biaseseach money magnitude downward (relative to its correct level) by theamount of the trading margin on that bundle of commodities, that beingthe element which such a procedure leaves out. In this particular exam-ple, the ratios of the inconsistent money measures still match the ratios


of (correct) labor value measures (i.e., SP*//NP*/ = 700/100 = SP/NP =1600/200), but this is solely because our numbers embody the convenientassumption that the percentage trading margins are the same for all bun-dles of commodities. In actual IO tables this is definitely not the case, sothat the ratios of money magnitudes could be biased in either directiondepending on the relative trading markups. For example, the inconsistentestimate of the necessary product NP*' is lower than the true estimate bythe amount of the trading margin on productive workers' consumptiongoods, whereas the inconsistent estimate of the surplus product SP*' islower by the amount of the average trading margin on the mix of con-sumer, investment, net export, and government purchases in the surplusproduct. Since consumer goods pass through both wholesale and retailchannels, they tend to have higher overall margins than goods purchasedfor investment or government (Khanjian 1989, pp. 109-13). Leaving outtrading margins therefore imparts a relatively greater downward bias tothe necessary product than to the surplus product. Thus, an inconsistentprocedure in which the calculations of the money forms is made sym-metric with that of the value forms will tend to yield money rates of sur-plus value that are higher than the corresponding value rates, all otherthings being equal.5

The false symmetry described here is not merely hypothetical. As weshall see in Section 6.2.3, the only other attempt to provide a completemapping between input-output accounts and Marxian categories comesfrom Wolff (1977a,b, 1987), and it suffers from precisely this defect: Wolfftreats money and labor value calculations symmetrically, which makesthe former inconsistent with the latter. Indeed, as expected on theoreticalgrounds, Wolff's estimates of money rates of surplus value are uniformlyhigher than his labor value estimates by about 4%-8% (Wolff 1977b,p. 103, table 3, 11. 1, 3). On the other hand, Khanjian's (1989) estimatesare consistent, and they indicate that SVV* is uniformly lower than S/Vby about 6%-8% (Khanjian 1988, p. 109, table 19). This allows us to es-timate that an inconsistent procedure biases the money rate of surplusvalue S*/V* upward by 12%-15% (the sum of the two sets of differencesin years common to both Khanjian and Wolff). Our discussion of the ac-tual empirical techniques is located in Sections 5.10 and 6.2.3.

4.2 Rates of exploitation of productive and unproductive workersThe calculation of labor-value/producer-price ratios A} also en-

ables us to distinguish the rate of exploitation from the rate of surplus5 Assuming that revenue- and product-side estimates are denned correctly, they

will be equal. Thus, an inconsistent procedure will yield biased estimates of themoney rates of surplus value from either side of the money accounts.


Table 4.4. Calculating rates of exploitation

Productive labor Unproductive labor

Vp=A*.(CONWp)p = V Vu=A*.(CONWu)p

ep = ( H p - V ) / V = S/V eu = (Hu-V u) /V u

Notes:ep» eu = rates of exploitation of productive and unproductive workers;

Vp, Vu = values of productive and unproductive labor powers;HP, Hu = total working time of productive and unproductive workers;(CONWp)p, (CONWU)P = producer price components of the consumption

vectors of productive and unproductive workers.

value. The rate of exploitation is the ratio of surplus labor time to neces-sary labor time. This concept applies to all capitalistically employed wagelabor, whether it is productive or unproductive (Shaikh 1978b, p. 21).Necessary labor time is simply the value of the labor power involved, thatis, the labor value of the average annual consumption per worker in theactivities in question. Surplus labor time is excess of working time overnecessary labor time. For productive workers, their rate of exploitation isalso the rate of surplus value, since their surplus labor time results in sur-plus value. Table 4.4 summarizes the calculation of rates of exploitation.

The expressions in Table 4.4 give rise to a powerful approximationtechnique, which we will use in Section 5.10. The two rates of exploita-tion can be written as

l + eu Hu/Vu H u /H p Hu /Hp

l + ep Hp/Vp Vu/Vp [A*.(CONWu)p]/[A*.(CONWp)p] *

The denominator of the last fraction is itself a ratio in which the vectorA* appears in both numerator and denominator. If the consumption pro-portions of productive and unproductive workers are relatively similar,which is quite plausible, then the vector product ratio [A*-(CONWu)p]/[A*-(CONWp)p] will be roughly the same as the scalar ratio (CONWU)P/(CONWp)p, where (CONWu)p and (CONWp)p refer to the sum of theproducer-price components of unproductive and productive workers' con-sumption (see Figure 4.1). Thus

l + eu H u /Hp

l + ep CONWu/CONWp

If the average consumption of workers is roughly equal to their wage(which is empirically true because the saving of some workers is offset by


the dissaving of others), then the consumption of each type of worker isapproximately equal to that worker's wage bill. If we divide the top andbottom of the preceding expression by the employment ratio Lu/Lp, then

l + eu _ hu/hp

l + ep ecu/ecp

wherehu, hp = hours per unproductive and productive worker;

ecu, ecp = employee compensation/?er unproductive and productiveworker.

Finally, since the rate of exploitation of productive workers is simplythe rate of surplus value, we can directly estimate the rate of exploitationof unproductive workers:

In effect, the relative rates of exploitation will depend solely on the rela-tive working time and on the relative wage rates. Both these items areeasily estimated from annual data. In addition, since the money rate ofsurplus value is quite close to the value rate of surplus value (as shown inSection 5.10), we can substitute S*/V* for S/V in the previous expres-sion. This allows us to directly estimate the annual rate of exploitation ofunproductive workers and compare it with that of productive labor. Wewill see that in the United States the two rates remain within 10% of eachother for almost all of the postwar period (see Section 5.6).

Empirical estimates of Marxian categories

Our empirical analysis of the U.S. economy will be set out in severalsections. Sections 5.1 and 5.2 will utilize suitably modified input-outputtables to develop benchmark year estimates of Marxian measures of thetotal, intermediate, and final product, and then use NIPA data to inter-polate between benchmark estimates to create an annual series for eachof these measures. Sections 5.3 and 5.4 develop the estimates of annualemployment, wages, variable capital V*, surplus value S*, surplus prod-uct SP*, and the rate of surplus value SVV*, and compare them to themore conventional measures such as profit-type income and the profit/wage ratio. Section 5.5 measures the Marxian rate of profit, and com-pares it with the average observed rate (net of those parts of surplus valuewhich are absorbed into nonproduction expenses) and the observed cor-porate rate. Section 5.6 measures the rate of exploitation of unproductiveworkers, and compares it to that of productive labor; Section 5.7 com-pares Marxian and conventional measures of productivity. Sections 5.8and 5.9 examine the impact of the state on accumulation, through itsabsorption of surplus value and through the effects of taxes and social ex-penditures on the rate of surplus value. Section 5.10 examines the effectsof price-value deviations on aggregate Marxian measures, and Section5.11 develops a technique that allows us to approximate the rate of surplusvalue in a relatively simple manner. Section 5.12 provides an overall sum-mary and some conclusions. The basic methodology for each section isdescribed in the text, with all further details reserved for the appendixes.

5.1 Primary Marxian measures in benchmark yearsInput-output tables for the United States are available only in

select (benchmark) years: 1947,1958,1963,1967,1972,1977. The theoretical

89


Production Toe Trade Royalties Dummy Sectors

Govt HschW ROW

Grass Final Demand

Con X-IM G

Production

Total Trade

Royalties

Row Lid

Gross Value Added

Gross Output

Figure 5.1. IO accounts and Marxian categories: Summary mapping.

relations between Marxian and orthodox categories in any one such tablewere summarized in Figure 3.11 and Table 3.12.

Figure 5.1 provides a condensed version of this same mapping. Pro-duction, total trade, and royalties are each aggregated into single sectors,so as to highlight the structural patterns of the mapping. Value added(and hence profit) are shown as gross of depreciation, while final demand(and hence investment) are shown as gross of retirements, as in actualinput-output tables. Intermediate inputs of the various sectors thereforedo not include fixed capital used up (D), which is why we label them asMJ, = (Mp-Dp), . . . rather than Mp,.. . as in Figure 3.11 previously. Theinventory valuation adjustment (IVA) row is merged into gross value added(GVA), and the corresponding IVA column into gross investment (IG) onthe final-demand side.1 The cross-hatching around IVA indicates that itis included in the Marxian measures of both gross value added GVA* andgross final product GFP*.

Finally, the total trade sector consists of private and public wholesale/retail trading activities, plus an estimate of the building and equipmentrentals sector (see Appendix B). Distributive transport was not estimated

1 The IVA dummy industry has only one entry, in the intersection of its own rowand column. When the row is merged into GVA and the column into IG, this oneentry is shifted to the GVA row of the IG column.

Empirical estimates of Marxian categories 91

1972

Production Tot Trade Royalties Dummy Sectors

Govt Hsehld ROW

Gross Final Demand

Con X-IM G

Production

Total Trade ^

t>^\*v

Royalties 1411.4 IM72.7

Govtlnd

Rowlnd lftMSJ -M3J

Gross Value Added

Gross Output 1372637^ 314065.5 163115.4 137400.0

6918.1

« 1 5 J

-15112A

70267X1 113899.0 -3405J 252«l#.O

Figure 5.2. 1972 IO table.

because of its relatively small impact2 and because of a paucity of dataon the subject. Estimated building and equipment rental was merged intothe total trade sector, but was neither unbundled nor adjusted for theamortization of building and equipment rented out (ABR). As noted inAppendix B.I, a failure to unbundle has no effect on the major Marxiantotals, though it does somewhat overstate the total trade sector relativeto the production sector. When we move to the annual NIPA-based esti-mates in Section 5.2, we do incorporate an ABR adjustment.3

Figure 5.2 presents an actual summary input-output table for 1972. Likeother similar tables (shown in Appendix C), this was derived in two stepsfrom benchmark tables published by the Bureau of Economic Analysis(BEA). First, a consistent set of 82-order (82 x 88) tables were produced,after making various adjustments to the published tables so as to renderthe classification of industries and treatment of secondary products and

2 In 1972, the gross output of the transportation and warehousing sector (BEA1979, pp. 65-7; see second half of 1972 IO table) came to roughly 3.5Vo of totalgross output. Of this, a large part is passenger transportation and the rest busi-ness-related (most of which is productive transport). If we estimate business-related transportation to be 50°7o of the total, and distributive transport to be25% of this, the latter amounts to only 0.59b of the economywide gross output.

3 Figure B.3 makes it clear that an ABR adjustment without unbundling would beinconsistent at the IO level (compare GO and GP of the production sector). Butaggregate GO = 2000 and aggregate GP = 2000 are unaffected.


comparable imports consistent across years. Second, these 82 x 88 tableswere aggregated into 8x11 summary tables constructed in the form ofFigure 5.1 above. Details are in Appendix A.

As indicated in Figure 5.2, total value TV* is simply the sum of thegross outputs of the production and total trade sectors (the sum of theelements in the bold rectangle). Materials used up in production C& andintermediate productive use UJ are now both net of depreciation (i.e.,CJ = C* — Depreciation and U^ = U* — Depreciation), and so are simplyequal to MJ,, the sum of the first two entries in the top left-hand cornerof Figure 5.2. Marxian gross value added GVA* = TV*-C* is the sumof the downward hatched elements (including M[t) within the dashed rec-tangle. Finally, the commodity uses CON*, I j , X* - IM*, and G* are cal-culated directly from those elements of consumption CON, gross invest-ment IG, net exports X —IM, and government expenditures G which liewithin the Marxian final-use dashed rectangle.

By way of contrast, the IO measure of total gross product GP, whichis really the sum of all transactions, is the sum of all intermediate inputs(including royalty payments) and all final demand GFD (shown as thecolumn sums of the elements within the gross final-demand block). GPappears as the lower right-hand element of the IO table, and GFD ap-pears directly above it.

Comparisons between the elements of corresponding Marxian and or-thodox measures make it clear that TV* will always be less than GO (sincethe former is a subset of the latter), but that GVA* may be less than, equalto, or greater than GFD (because GVA* excludes some elements in GVAand includes others which are not in GVA). Similar remarks apply touse-side comparisons.

Table 5.1 summarizes the calculations of Marxian and IO measures for1972, in millions of dollars, as derived from Figure 5.2. Table 5.2 repeatsthese calculations for each of the benchmark years in which input-outputtables are available. Note that the orthodox measure GP (the sum of allinput-output transactions) is consistently larger than the Marxian mea-sure of total product TP*. On the other hand, the orthodox and Marxianmeasures of gross value added (GFD and GFP*, respectively) are surpris-ingly close: roughly equal in 1947 and roughly 11% apart by 1987.

5.2 Annual series for primary measures, based on NIPA dataOur previous IO benchmark estimates in Table 5.2 can be con-

verted into annual series by making use of National Income and ProductAccounts (NIPA) data. Such a conversion is complicated by two factors.First of all, NIPA data cover only gross value added and gross final de-mand, and even here there is insufficient detail. In terms of Figures 5.1


Table 5.1. Primary Marxian and IO measures, 1972

Marxian measures

TV* = GOp + GOtt = 1,372,637.4 + 314,065.8 = 1,686,703.2

C*=M p = 619,148.1+ 78,676.1 = 697,824.2

GVA* = TV*-C* =988,879.0

= 697,824.2 + (54,809.2 + 22,853.4) + (22,725.3 + 9,696.4)+ (468,702.7 +181,973.3) + (127,993.8 +10,837.9)+ (-22,509.0 + 7,046.5) + (101,767.3 + 2,982.2)

= 1,686,703.2

U*=M'p = 697,824.2

GFP* (with IVA) = TP*-U* =988,879.0

M;t + Mrry = (54,809.2 + 22,853.4) + (22,725.3 + 9,696.4) = 110,084.3

CON* = (468,702.7+ 181,973.3) = 650,676.0

I* (with IVA) = (127,993.8+ 10,837.9-15,182) = 123,649.7

(X-IM)* =(-22,509.0 + 7,046.5) = -15,462.4

G* = (101,767.3 + 2,982.2) = 104,747.5

Comparisons with selected IO measures;y p tt y

+ CON + I + X - I M + G = 1,999,586.0>TP* = 1,686,703.2

+ RYp + RYtt + RYry = 908,419.2 > C*=Mp = 697,824.2

GFD (with IVA) = CON + I + X - I M + G = 1,075,984.2 > GFP* =988,879.0

CON = 702,672.1 > CON* = 650,676.0

1 = 123,899.0 > I* = 123,649.7

X - I M = -3,405.3 > (X-IM)* = -15,462.4

G = 252,819.0 » G* = 104,747.5

and 5.2, this means that we have annual data only on the elements of thegross value-added row, and on certain elements of the gross final-demandblock (such as the column sums CON, I, etc., and the dummy industryentries HHcon, Wg). Intermediate inputs M' and RY are not covered atall in NIPA data, while others such as the elements of the ROW industryare only partially covered (NIPA only lists the total). Second, even wherethe two data sets overlap, their estimates generally differ. Individual sec-tors are defined differently in NIPA than in IO accounts, so that sectoralGVAs do not match (BEA 1980, p. 8). Even total GVA and GNP, whichare constructed so as to be the same in the two sets of accounts, do not


Table 5.2. Primary Marxian and IO measures, benchmark years(millions of dollars)

Variables

Marxian measuresTV*C*=MJ,GVA*TP*U*'=M'P

GFP* (with IVA)

CON*IG*X*-IM*G*

1947

398,680178,823219,858398,680178,823219,858

23,964152,89423,512

9,8839,604

Selected IO measuresGPMGFD (with IVA)

CONIG (with IVA)X - I MG

435,986214,736219,723160,24622,03011,52825,918

1958

699,168306,471392,697699,168306,471392,69743,094

258,60040,253-1,57952,330

792,424381,104410,698274,997

39,7342,206

93,760

1963

892,319384,414507,905892,320384,414507,906

54,511332,10158,043

13963,111

1,022,054479,271541,779355,611

57,1595,812

123,198

1967

1,163,717489,379674,338

1,163,716489,379674,337

74,946418,31594,253

-3,06589,888

1,356,515625,709121 MO452,094

90,7755,132

179,119

1972

1,686,703697,824988,879

1,686,703697,824988,879110,084650,676138,832

-15,462104,750

1,999,586908,419

1,075,985702,672123,899-3,405252,819

1977

2,917,9221,308,6091,609,3122,918,4881,308,6091,609,879

195,9071,059,878

236,438-39,213156,869

3,481,6901,688,8701,794,8421,139,024

238,981-3,981420,817

generally match, because the totals for a given input-output table arebenchmarked on NIPA estimates available when that particular table wascreated whereas currently available NIPA data incorporate many revi-sions of earlier estimates.

For all of these reasons, one cannot simply use NIPA data to fill inobservations between IO benchmark years. Instead, we use NIPA datadirectly for components such as GVAP or CON (containing the latestavailable revisions) and indirectly to interpolate between benchmark esti-mates of other components such as Mp or RYcon.

Consider the estimation of the total value TV*. By definition, we canwrite this as (see Figure 5.1):

TV* = GOP + GOtt = total value,

where= Mp + RYp+[GVAp}, and


We have:

CJ, = M'p = materials inputs into production;

C5 = (Dp) = depreciation of productive fixed capital;

C* = Mp + Dp = constant capital used up (flow);

GVA* s TV* - C* = Marxian gross value added;

VA* = TV* - C* = GVA* - C J = Marxian (net) value added.

Our estimation procedure then consists of three steps:(i) The three items in braces {GVAp,GVAtt,Dp} are calculated di-

rectly from NIPA, by aggregating individual NIPA industriesinto production and total trade sectors in much the same waythat we aggregated input-output sectors earlier,

(ii) The four components Mp, RYp, M'tt, and RYtt are interpolatedbetween benchmark years in a manner to be described shortly,

(iii) The GVAs, Ms, and RYs are used to form GOP and GOtt, andtheir sums give us TV*. Dp and Mp give us C% and C^, respec-tively, which in turn allow us to calculate GVA* and VA*.

The calculation of TP* follows the same general procedure. For instance,from Figure 5.1 we can write

Figure 5.1 also makes it clear that the Marxian final-use categories suchas CON*, I *,... can be derived by reducing the corresponding NIPA mea-sures CON,I,.. . by those items which are excluded from the Marxianmeasure (i.e., which fall outside the dashed hatched rectangle and thecross-hatched section around IVA in Figure 5.1), as well as by those itemsalready excluded from our benchmark tables (e.g., the imputed rentalcomponent GVAir in consumption, as shown in Appendix B.I and FigureB.I). We have:

CON* = (CON) - GVAir - RYcon - (HHcon) - ROWcon;

= {X-IM}-RYx_im-ROWx_im;

G* = {G}-RYG-(WG}-ROWG.

Once again we proceed in three steps.4 As noted earlier, the inventory valuation adjustment IVA was merged into value

added on the revenue side, and hence into I* on the use side.


(i) The items in braces [CON, IG, X - IM, G, WG} are taken directlyfrom NIPA.

(ii) The Ms, RYs, and ROWs are interpolated between input-outputbenchmark years, as described in what follows,

(iii) The remaining components of TP* are then calculated and as-sembled together to yield an estimate of the total.

The Ms, RYs, and ROWs that enter into TV* and TP* do not appearin NIPA at all. They must therefore be carried over from the benchmarkyears in which we have input-output tables, and interpolated to createannual series for each variable. This is accomplished in the followingmanner.

(a) In each input-output year, we calculate the ratio of the com-ponent to either its using or its receiving industry's gross valueadded. For material inputs M' (and depreciation D later on) weutilize the using industry's GVA. Thus for MJ, we create the ratioxp s (Mp/GVAp)IO, where the subscript IO refers to the fact thatboth variables are from input-output tables. For royalties RY weuse the receiving industry's GVA (i.e. GVAry) as the numeraire, asin Xi = (RYi/GVAry)Io. This is done because some royalties suchas RYj and RYx_im appear as components of highly unstable final-demand totals like I or X — IM (see Figure 5.1). Benchmark coeffi-cients created by dividing these royalties by unstable totals are notvery useful. The same reasoning applies to rest-of-world (ROW)entries in Figure 5.1, which are divided by total ROW in order toform coefficients for extrapolation, as in xr0Wg = ROWg/ROW.

(b) All coefficients created as described in (a) are linearly interpolatedbetween benchmark (IO) years. The result is an annual series foreach coefficient, derived entirely from input-output data.

(c) The annual observation for each coefficient is multiplied by theNIPA measure of the relevant gross value added (or ROW in thecase of rest-of-world coefficients) so as to create a NIPA-basedestimate of the original IO variable. Thus

(Mp)NIPA = V(GVAp)N I P A, (RYiJNjpASXi-tGVAryWA,

and

(ROWg)NIPA - xroWg.(ROW)NIPA.

The resulting annual estimates are then used in all subsequentcalculations.

Details of the interpolation procedure are in Appendix D, and of theannual estimates of the primary Marxian measures in Appendix E.


Table 5.3 presents the NIPA-based estimates for the benchmark yearsonly. Since the IO-based measures in Table 5.2 do not include an ABRadjustment (see Section 5.1, para. 3), our present NIPA-based estimatesalso omit this adjustment (although it is incorporated into the full annualseries in Table 5.4). Note that current estimates differ slightly from those inTable 5.2, as indicated by the ratios of NIPA-based estimates to IO-basedones. This is a reflection of the previously noted differences between IO andNIPA measures.5 It is nonetheless striking that the totals are fairly close,although individual components such as investment and net exports differsubstantially. In any case, the stability of almost all ratios at the bottomof Table 5.3 indicates that the trends are the same in both data sets.

Table 5.4 extends coverage to the full period 1947-87, this time with theABR adjustment. The previous patterns are now fully borne out. Figures5.3 and 5.4 compare Marxian real total product (real TP*) and its ortho-dox equivalent (real GNP), both derived through the GNP price deflator(Table J.I). The striking thing in Figure 5.4 is that their ratio falls consis-tently, except for a brief reversal from 1972 to 1977. The ratios TPVGP(Marxian total product to NIPA-based IO gross product), GFPVGNP(Marxian gross final product to NIPA gross national product), and thecorresponding net ratio FPVNNP also fall steadily until 1972 and thenessentially level out. The much larger reversal in the total-product/GNPratio is probably explained by the oil-price rise in 1973, since the ratioof production inputs to GNP (C*7GNP) rises by 17% over this intervalwhile the ratio of Marxian gross final product to GNP (GFPVGNP) isroughly constant.

Figure 5.5 looks at the major components of total value TV* =GOp + GOtt; Figure 5.6 looks at those of TP*, broken down in thiscase into total intermediate use M' = Mp+M(t + Mry and gross final useGFU* = CON* + IG* + (X-IM)* + G* (see Figure 5.1). In both cases,the respective component shares are remarkably constant. Throughoutthe postwar period, the gross trading margin GOtt/TV* holds steady atabout 18%, while the input use share M7TP* holds steady at about 50%of the total product. A similar constancy holds for the productive inputsshare Mp/TP* (calculated from Table 5.4), which hovers around 43%throughout, rising slightly during the oil shock and then coming backdown to normal levels. In Marxian terms, this translates into the prop-osition that the flow of constant capital used as materials C& = M'p is astable proportion of total value TV* (=TP*). This constant-flow/flowratio does not say anything, however, about the ratio of fixed constant

5 The difference in investment measures seems to stem from the fact that the IOmeasure excludes residential investment, which is included in the NIPA measure.

Table 5.3. Primary Marxian and NIP A measures, benchmark years (NIPA based; billions of dollars)

Sources Variables 1947 1958 1963 1967 1972 1977

Marxian measuresTableTableTableTable

TableTableTableTableTable

E.FD.2E.l"E.2

D.2E.2E.2E.2E.2

TV*C* =M'GVA*TP*U*'=Mp

GFP* = TP*-UM;,+M'ryCON*IG*(X-IM)*G*

Selected NIPA-IO measures

Table

TableTableTableTable

D.2

E.2E.2E.2E.2

GP = M + GFDM = M ' +M(,+I>GFD=GNP

CONIG(X-IM)G

Comparisons oflO and NIPA-based estimates

GVA*O/GVA*NIPA

CONfo/CONftIPA

IGfo/IGR[PA

(X-IM)fo/(X-IM)RI P AG*O/GNIPA

395.60173.22222.00395.09173.22221.8724.15

147.1032.479.538.62

711.79308.00403.79711.67308.00403.6743.93

251.6458.40

-2.0351.73

914.05389.68524.38913.42389.68523.7455.95

319.6786.80

-0.2061.52

1200.79500.66700.13

1199.81500.66699.1575.99

421.33117.28-3.3387.90

1728.88714.33

1014.551728.41714.33

1014.08108.05637.77187.77

-15.5596.04

3054.581367.271687.313058.101367.271690.83196.66

1068.01318.62

-35.29142.84

445.20 845.30 1099.77 1462.58 2143.39 3750.53210.00 388.40 492.97 646.08 930.59 1760.03235.20161.9035.0011.9026.40

1.011.030.991.010.991.040.721.041.11

456.90294.6063.60

3.3095.40

0.981.000.970.980.981.030.690.781.01

606.80381.7093.108.20

123.80

0.980.990.970.980.971.040.67

-0.701.03

816.50503.60125.70

7.40179.80

0.970.980.960.970.990.990.800.921.02

1212.80757.60202.00

3.20250.00

0.980.980.970.981.021.020.740.991.09

1990.501257.20344.10

1.90387.30

0.960.960.950.951.000.990.741.111.10

a 1947 data is not shown in Table E.I, but is derived in the same manner.


Table 5.4. Primary Marxian and NIPA measures, 1948-89(NIPA based; billions of dollars)

Sources Variables

Marxian measuresTable E.ITable D.2Table E.ITable E.ITable E.ITable E.2

Table D.2Table E.2Table E.2Table E.2Table E.2

Table J.ITable J.ITable J.I101 \a

705 \a

Table E.ITable E.I

TV*C*=M'P

GVA*VA* = GVA*-C*

c*TP*U*' = M'PG F P * = T P * - U * '

M[t + M'ryCON*IG*(X-IM)*G*

GFU*=GFP*-(M[t + MFP* = GFP*-C*TP*a,GFP*al

GNPreal

GNPGNP deflator

TPVGNPGOP/TV*GOtt/TV*M'/TP**GFUVTP*


Table E.2Table E.2Table E.2Table E.2Table H.I

GP = M+GFDMc

GFD = GNPCONIG(X-IM)G

NNP

ComparisonsTPVGPGFPVGNPJPVNNP

1948

446.25198.47247.78238.35

9.42446.21198.47247.7426.54

158.4644.27

4.0614.40

;y) 221.20238.32

1890.711049.741108.47261.6023.60

1.710.820.180.500.50

501.09239.49261.60174.947.1

7.032.6

241.20

0.890.950.99

1949

432.02189.06242.95233.66

9.29431.96189.06242.9026.67

160.1633.55

3.7618.76

216.23233.60

1838.131033.611107.66260.3023.50

1.660.810.180.500.50

491.85231.55260.30178.336.56.5

39.0238.40

0.880.930.98

1950

481.79212.56269.23258.42

10.81481.62212.56269.0628.60

171.7951.96

-0.7117.42

240.45258.25

2015.131125.761205.86288.2023.90

1.670.820.180.500.50

546.81258.61288.20192.155.12.2

38.8264.60

0.880.930.98

1951

551.61244.59307.02294.17

12.85551.62244.59307.03

31.26185.6556.940.67

32.50275.76294.18

2197.701223.221328.69333.5025.10

1.650.830.170.500.50

628.80295.30333.50208.160.54.5

60.4306.20

0.880.920.96

1952

573.67254.35319.32305.52

13.80573.95254.35319.6132.67

194.1449.73-0.9844.06

286.94305.81

2250.801253.361378.82351.6025.50

1.630.830.170.500.50

660.15308.55351.60219.1

53.53.2

75.8322.50

0.870.910.95

a From NIPA (e.g. BEA 1986), where the first three digits denote the relevant table numberand subsequent digits the line numbers within those tables.


1953

605.61268.66336.95321.9115.04

605.37268.66336.7134.07

204.4150.96-2.6949.96302.64321.68

2337.351300.051434.36371.5025.901.630.830.170.500.50

698.29326.79371.50232.654.91.3

82.7340.70

0.870.910.94

1954

596.59261.36335.23320.1515.08

596.63261.36335.2635.16

209.0949.97-1.5542.59300.10320.18

2268.551274.761416.35372.5026.301.600.820.170.500.50

695.08322.58372.50239.854.12.6

76.0340.00

0.860.900.94

1955

653.31287.18366.14349.0717.07

652.91287.18365.7437.96

224.2765.31-1.8540.05327.78348.67

2400.421344.631492.28405.9027.201.610.830.170.500.50

759.29353.39405.90257.969.73.0

75.3371.50

0.860.900.94

1956

687.44303.11384.33365.7918.54

687.21303.11384.1040.31

234.1867.95-0.2441.89343.79365.56

2445.571366.901523.84428.2028.101.600.830.170.500.50

802.66374.46428.20270.672.75.3

79.6390.10

0.860.900.94

1957

717.68314.63403.05383.2519.79

717.30314.63402.6742.56

246.0366.061.09

46.93360.11382.88

2464.961383.761549.83451.0029.101.590.830.170.500.50

841.93390.93451.00285.371.17.3

87.3409.90

0.850.890.93

1958

711.79308.00403.79383.8719.92

711.67308.00403.6743.93

251.6458.40-2.0351.73359.74383.75

2396.201359.161538.38456.9029.701.560.820.180.490.51

845.30388.40456.90294.663.63.3

95.4414.00

0.840.880.93

1959

774.37334.93439.44417.9921.44774.29334.93439.3647.60269.1974.79-4.1451.92

391.75417.912547.011445.261631.25495.9030.401.560.820.180.490.51

918.12422.22495.90316.380.21.5

97.9451.20

0.840.890.93

1960

796.20343.72452.48430.6921.78

795.67343.72451.9549.10

279.7472.55-0.3750.93

402.85430.162574.981462.611667.96515.4030.901.540.820.180.490.51

949.79434.39515.40330.778.25.9

100.6468.90

0.840.880.92

1961

812.01347.54464.47442.6721.80811.42347.54463.8850.66

286.6971.270.4854.77

413.22442.082600.711486.801710.90533.8031.201.520.820.180.490.51

975.53441.73533.80341.177.17.2

108.4486.10

0.830.870.91

(more)


Table 5.4 (cont.)

Sources Variables



Table J.ITable J.ITable J.I101 1705 1

Table E.ITable E.I

TV*C*=Mp

GVA*VA*=GVA*-CJ

C*TP*U*'=MpGFP* = TP*-U*'

M;t+M;y

CON*IG*(X-IM)*G*

GFU*=GFP*-(M|t + MFP* = GFP*-CJTP*a.GFP*al

GNPrcal

GNPGNP deflator

TPVGNPGOP/TV*GOtt/TV*MVTP*GFUVTP*



GP = M-I-GFDMGFD=GNP

CONIG(X-IM)G

NNP

ComparisonsTPVGPGFPVGNPFPVNNP

1962

870.18371.40498.78475.73

23.05869.52371.40498.12

53.59303.6481.54

-0.9260.26

;y) 444.53475.07

2725.781561.501800.94574.5031.90

1.510.820.180.490.51

1044.76470.26574.50.361.9

87.66.9

118.1525.20

0.830.870.90

1963

914.05389.68524.38500.4623.91

913.42389.68523.7455.95

319.6786.80

-0.2061.52

467.79499.83

2819.181616.481872.84606.80

32.401.510.820.180.490.51

1099.77492.97606.80381.793.1

8.2123.8555.50

0.830.860.90

1964

973.89412.31561.59536.5425.05

973.35412.31561.0560.52

343.5992.94

1.5962.41

500.53536.00

2958.521705.311975.08649.8032.90

1.500.820.180.490.51

1173.84524.04649.80409.3

99.610.9

130.0595.90

0.830.860.90

1965

1057.74447.41610.33583.4226.91

1057.19447.41609.7865.06

370.24109.07-0.3965.80

544.71582.87

3127.771804.072086.39705.2033.80

1.500.820.180.480.52'

1273.88568.68705.20440.7116.2

9.7138.6647.70

0.830.860.90

1966

1150.25483.74666.51637.7228.79

1149.69483.74665.9470.54

400.85120.83-2.4176.14

595.40637.16

3284.821902.692205.71772.0035.00

1.490.820.180.480.52

1389.06617.06772.00477.3128.6

7.5158.6709.90

0.830.860.90


1967

1200.79500.66700.13670.6629.48

1199.81500.66699.1575.99

421.33117.28-3.3387.90

623.17669.683342.091947.502274.37816.5035.901.470.820.180.480.52

1462.58646.08816.50503.6125.77.4

179.8749.00

0.820.860.89

1968

1307.97545.14762.83730.4032.43

1307.46545.14762.3282.18

464.47127.76-6.5194.42

680.14729.893468.052022.062367.90892.7037.701.460.820.180.480.52

1595.80703.10892.70552.5137.05.5

197.7818.70

0.820.850.89

1969

1406.84586.54820.30785.0435.26

1406.26586.54819.7288.39

502.02142.73-6.3992.96731.33784.46

3533.322059.602422.11964.0039.801.460.820.180.480.52

1722.72758.72964.00597.9153.25.6

207.3882.50

0.820.850.89

1970

1457.17602.47854.70818.1136.59

1456.35602.47853.8892.71537.49137.31-4.2590.63761.18817.30

3467.512033.062417.861015.5042.001.430.810.190.480.52

1800.78785.281015.50640.0148.88.5

218.2926.60

0.810.840.88

1971

1568.48644.70923.78884.2239.56

1567.82644.70923.1299.94580.57159.69-9.5692.46823.17883.56

3531.122079.092483.561102.7044.401.420.810.190.470.53

1945.90843.201102.70691.6172.56.3

232.31005.10

0.810.840.88

1972

1728.88714.331014.55970.2844.27

1728.41714.331014.08108.05637.77187.77-15.5596.04

906.03969.813717.012180.822608.171212.8046.501.430.810.190.480.52

2143.39930.591212.80757.6202.03.2

250.01104.80

0.810.840.88

1973

1980.04837.401142.641090.2452.40

1979.91837.401142.52122.49708.07222.71-9.2398.47

1020.021090.123999.832308.112746.061359.3049.501.460.820.180.480.52

2440.001080.701359.30837.2238.816.8

266.51241.20

0.810.840.88

1974

2161.80926.561235.251176.7558.50

2162.38926.561235.82135.35776.70222.26-14.12115.631100.471177.334004.402288.562727.221472.7054.001.470.820.180.490.51

2667.471194.771472.70916.5240.816.3

299.11335.40

0.810.840.88

1975

2366.721023.781342.951277.7765.17

2368.481023.781344.71151.11860.42198.564.02

130.591193.601279.533994.072267.642695.781598.6059.301.480.820.180.500.50

2919.001320.401598.601012.8219.631.1

335.11436.60

0.810.840.89

(more)


Table 5.4 (cont.)

Sources Variables



Table J.ITable J.ITable J.I101 1705 1

Table E.ITable E.I

TV*C*=M'P

GVA*VA*=GVA*-CJ

c*TP*U*'=MP

GFP*=TP*-U*'M(t + M'ryCON*IG*(X-IM)*G*

GFU*=GFP*-(M;(+MFP* = GFP*-Cd*TP*a.GFP*al

GNPreal

GNPGNP deflator

TPVGNPGOP/TV*GOtt/TV*MVTP*GFUVTP*



GP = M+GFDMGFD=GNP

CONIG(X-IM)G

NNP

ComparisonsTPVGPGFPVGNPFPVNNP

1976

2691.951187.331504.621428.45

76.182694.391187.331507.06170.35961.28254.84-12.91133.49

;y) 1336.701430.884270.032388.362825.201782.70

63.101.510.820.180.500.50

3305.491522.791782.701129.3277.7

18.8356.9

1603.60

0.820.850.89

1977

3054.581367.271687.311598.95

88.363058.101367.271690.83196.66

1068.01318.62

-35.29142.84

1494.171602.474543.982512.382957.651990.50

67.301.540.820.180.510.49

3750.531760.031990.501257.2344.1

1.9387.3

1789.00

0.820.850.90

1978

3456.061545.891910.171810.27

99.903456.761545.891910.87221.85

1185.13387.90

-40.48156.47

1689.021810.974787.752646.643115.792249.60

72.201.540.830.180.510.49

4248.521998.922249.601403.5416.8

4.1425.2

2019.80

0.810.850.90

1979

3832.061710.492121.562011.02

110.543833.251710.492122.76248.44

1321.81421.18-44.04175.38

1874.322012.224876.912700.713191.092508.20

78.601.530.820.180.510.49

4731.532223.332508.201566.8454.8

18.8467.8

2242.40

0.810.850.90

1980

4140.141851.272288.872169.23

119.644141.101851.272289.84266.86

1454.98398.22

-36.36206.13

2022.982170.204832.092671.923197.982732.10

85.701.520.830.170.510.49

5146.842414.742732.101732.6437.0

32.1530.4

2428.10

0.800.840.89


1981

4653.192078.342574.852440.54134.31

4654.402078.342576.06301.661599.86485.10-41.22230.67

2274.412441.754951.492740.493247.453052.60

94.001.520.830.170.510.49

5768.062715.463052.601915.1515.533.9

588.12704.80

0.810.840.90

1982

4762.472114.612647.862511.20136.66

4763.862114.612649.25317.071710.89414.52-47.94254.71

2332.192512.594763.862649.253166.003166.00100.00

1.500.820.180.510.49

5951.662785.663166.002050.7447.326.3

641.72782.80

0.800.840.90

1983

5085.622235.612850.012705.53144.48

5086.972235.612851.36352.371853.81466.85-79.65257.992499.002706.884896.032744.333277.863405.70103.90

1.490.820.180.510.49

6407.163001.463405.702234.5502.3-6.1675.03009.10

0.790.840.90

1984

5689.102497.253191.853030.46161.39

5691.022497.253193.77394.43

2013.39626.53

-129.87289.292799.343032.385284.142965.433502.603772.30107.70

1.510.820.180.510.49

7119.723347.423772.302430.5664.8-58.9735.93356.80

0.800.850.90

1985

6014.562618.653395.913226.68169.23

6014.182618.653395.53436.732161.53601.72

-141.28336.83

2958.813226.305374.603034.443587.944014.90111.90

1.500.810.190.510.49

7594.933580.034014.902629.0643.1-78.0820.8

3577.60

0.790.850.90

1986

6236.332664.483571.853399.66172.19

6224.472664.483559.99472.792275.73614.64

-156.38353.203087.203387.805417.293098.343682.864231.60114.90

1.470.810.190.500.50

1914.113743.114231.602797.4659.4-97.4872.2

3771.50

0.780.840.90

1987

6614.452808.663805.793624.28181.51

6606.592808.663797.93511.57

2434.73651.16

-164.96365.443286.363616.425547.093188.863791.444515.60119.10

1.460.810.190.500.50

8510.873995.274515.603009.4699.5

-114.7921.4

4028.60

0.780.840.90

1988

7223.853122.994100.863899.03201.83

7226.223122.994103.23553.24

2619.76694.94

-131.34366.633549.993901.405957.313382.714017.894873.70121.30

1.480.820.190.510.49

9198.454324.754873.703238.2747.1-74.1962.5

4359.40

0.790.840.89

1989

7639.863278.254361.614149.75211.867641.823278.254363.57597.13

2777.29714.89

-110.05384.313766.454151.716050.533454.934117.825200.80126.30

1.470.810.190.510.49

9789.834589.025200.803450.1771.2-46.11025.64646.40

0.780.840.89


5.6

4.2-

2.8 -

1.4-

TP*i«d

GFP*real

0 ' I i I I I I I I l I l l I I I I I1948 1953 1958 1963 1968 1973 1978 1983 1988

Figure 5.3. Real total and final product, and real GNP (billions of 1982dollars). Source: Table 5.4.

1.8

0.7

GFP*/GNP

1948 1953 1958 1963 1968 1973 1978 1983

Figure 5.4. Ratios of real product measures. Source: Table 5.4.


0.8-

0.6-

tOtt/TV

ooppnv*

0 ' i i iI

1948 19S3 19S8 1963 1968 1973 1978 1983 1988

Figure 5.5. Components of total value. Source: Table 5.4.

'l9i53 ' ' ' '19^8 ' ' ' 1963 ' ' ' 'l9JS8' ' ' 'l973 ' ' ' 1978 ' ' ' ' 19^3' ' ' 1988'

Figure 5.6. Components of total product. Source: Table 5.4.


capital to total value or to value added. For information on the latter, seeShaikh (1987, 1992b). Finally, it is worth noting that the relative stabil-ity of the proportion between productive and total trade sectors in Fig-ure 5.5 does not carry over to the proportion between productive andunproductive labor in Figure 5.9, which rises dramatically over the post-war period.

5.3 Employment, wages, and variable capitalThe transition from input-output tables to a NIPA-based data

set allows us to take advantage of the employment and wage data avail-able in NIPA and in related sources such as the Bureau of Labor Sta-tistics (BLS). Our primary database for employment and wages is fromNIPA. For total employment L we use "persons engaged in production"(PEP), since this includes both employees and self-employed persons;for wages we use "employee compensation" (EC), which includes wagesand salaries of employees as well as employer contributions to social se-curity. Employee compensation is the appropriate measure upon whichto base our estimates of variable capital, since it represents the total costof labor power to the capitalist.

NIPA data make no distinction between production and nonproductionworkers, unlike BLS data.6 We therefore use the latter to calculate theratios of production labor to total labor in each production sector. Theseratios are then applied to relevant NIPA employment totals in order tosplit them into comparable components. A combination of BLS and NIPAdata is also used to estimate the wage per production worker, which isthen applied to the previous estimate of the number of productive workersto derive the total wage bill of productive labor (variable capital). Thewage bill of unproductive workers is derived as the difference betweentotal NIPA wages and our estimate of total variable capital. These pro-cedures allow us to retain NIPA estimates of total employment and totalwages - which are tied to the value-added and final-demand estimatesused to create our primary measures - while still making use of importantinformation available only from the BLS. The basic steps involved areoutlined next.

Total labor and productive labor: Productive labor is the production la-bor employed in capitalist production sectors: agriculture, mining, con-

6 The Employment and Training Report of the President (BLS 1981) lists two typesof employment for each sector: total employment, and production and nonsu-pervisory workers. In production sectors we take the latter to be a good estimateof the number of production workers.


struction, transportation and public utilities, manufacturing, and produc-tive services (defined as all services except business services, legal services,and private households, as in Table E.I). It thereby excludes nonproduc-tion labor (sales etc.) employed in the production sectors; it also excludesall labor in nonproduction sectors such as trade or finance. Thus total pro-ductive labor is the sum of the production workers in each productionsector. Total unproductive labor is the sum of the nonproduction workersin the production sectors and all the workers in the nonproduction sec-tors.7 Listing the production sectors as j = 1,...,/: and the nonproductionsectors as y = k +1 , . . . , n, we calculate

Ly = total employment in the yth sector (from NIPA)8

= "persons engaged in production" (PEP)

= full-time equivalent employees (FEE)

+ self-employed persons (SEP);9

L = 2 L, = total labor;

(Lp/L)y = ratio of production/total workers

in the yth production sector, j — 1,..., k (BLS);

= estimated production worker

employment in the jth production sector, j = 1,..., k\

Lp = S(Lp)y = total productive labor;

LU = L — Lp = total unproductive labor.

7 We should in principle attempt to separate out production from nonproductionactivities in the nonproduction sectors, just as we do for production sectors, butthe data for this is lacking. Also, there is a genuine asymmetry between produc-tion and nonproduction sectors. All capitalist enterprises must devote a certainamount of their activities to buying and selling and to finance; thus, even produc-tive sectors will contain a significant amount of nonproduction activities. Butnonproduction sectors have no such systematic reason for incorporating produc-tion activities.

8 To estimate the labor in the productive service sectors, we take the ratio of theGNP of the productive service sectors to the GNP of total services, and applythat to the total employment in services (Table E.I and F.I).

9 Persons engaged in production (PEP) is a standard NIPA series. The inclusionof self-employed persons alongside full-time equivalent employees suggests thatthe former are also largely full-time.

Table 5.5. Total labor and productive employment, 1948-89(thousands)

Variables

LLpLU = L - L P

Lp/Lu

Lp/L

Variables

LLpLU = L - L P

Lp/Lu

Lp/L

Variables

LLPLU = L - L P

Lp/Lu

Lp/L

Variables

LLpLU = L - L P

Lp/Lu

Lp/L

Variables

LLPLU = L - L P

Lp/Lu

Lp/L

Variables

L

LU = L - L P

Lp/Lu

Lp/L

1948

58,30132,99425,3071.300.57

1955

63,36631,71431,6521.000.50

1962

66,09129,93736,1540.830.45

1969

78,87534,12544,7500.760.43

1976

85,15134,67750,4740.690.41

1983

95,95236,08859,8640.600.38

1949

56,91931,20125,7181.210.55

1956

64,52231,86432,6580.980.49

1963

66,65530,01336,6420.820.45

1970

78,27533,24745,0280.740.42

1977

88,11635,79852,3180.680.41

1984

100,60737,87262,7350.600.38

1950

58,60032,22626,3741.220.55

1957

64,77931,43333,3460.940.49

1964

67,87430,28037,5940.810.45

1971

77,93732,72745,2100.720.42

1978

92,53937,61054,9290.680.41

1985

103,03138,22964,8020.590.37

1951

62,36633,12329,2431.130.53

1958

62,76529,34933,4160.880.47

1965

70,12831,36538,7630.810.45

1972

79,85633,89645,9600.740.42

1979

95,52538,59856,9270.680.40

1986

104,83138,31266,5190.580.37

1952

63,45732,76830.6891.070.52

1959

64,09930,02034,0790.880.47

1966

73,30132,56640,7350.800.44

1973

83,29935,46247,8370.740.43

1980

95,73437,86357,8710.650.40

1987

107,89139,34468,5470.570.36

1953

64,24733,04331,2041.060.51

1960

64,98930,04734,9420.860.46

1967

75,13732,85642,2810.780.44

1974

84,61235,65748,9550.730.42

1981

96,58237,73858,8440.640.39

1988

110,96240,53870,4240.580.37

1954

62,32431,23031,0941.000.50

1961

64,74029,36335,3770.830.45

1968

76,92933,44543,4840.770.43

1975

82,82733,61549,2120.680.41

1982

94,99036,20358,7870.620.38

1989

113,51141,14872,3630.570.36

Source: Appendix F.


120000

100000

60000

40000

2 0 0 0 0 ' i i i i i i i i i . i i i i i i i i i i [ i i i i i i i i i i i i i i i i i i i i i1948 1953 19S8 1963 1968 1973 1978 1983 1988

Figure 5.7. Total labor and productive labor (thousands). Source: Table 5.5.

Appendix F gives the details of the calculations. Table 5.5 and Figure5.7 present the estimates for L, Lp, Lu, and Lp/L for the years 1948-89.Note that productive employment rises much more slowly than total em-ployment, so that their ratio in Figure 5.9 declines by more than 37%over the postwar period. The same trend is depicted in Figure 5.11, wherewe see that the ratio of unproductive to productive labor L u/Lp risessharply, by almost 138%, over the same period.

Total wages and variable capital: As noted earlier, we want our basicmeasure of wages to include supplements to wages such as employer con-tributions to social security and other pension funds, since these are partof the total cost of hiring labor power. The NIPA measure of employeecompensation (EC) is therefore the appropriate starting point,10 but wemust make two adjustments to it. First, since EC covers only employeeswhereas total employment L includes both employees and self-employedpersons, we need to make some estimate of the wage equivalent of self-

10 Employee compensation EC includes the salaries of corporate officers (COS) andsupplements to these salaries. Mage (1963) excludes these on the grounds thatthey are really part of capitalist income, not wages. We do essentially the samething (see Appendix G).


employed persons.11 Second, we must split the resulting measure of totalwages into wages of productive and unproductive workers. Let:

EC7 = total employee compensation in the jth sector (NIPA);

FEE, = total full-time equivalent employees in the j th sector

(NIPA);

ecy = (EC/FEE)y = employee compensation per full-time

equivalent employee;

Wy = ecy • Ly = estimated wage equivalent of employees and

self-employed persons in the j th sector; and

W = S Wy = total wage and wage equivalent.

This extends the coverage of employee compensation to include the wageequivalent of self-employed persons. We must now divide total wagesinto those of productive and unproductive workers. Given our previousdata on the numbers of productive and unproductive workers (Lp, Lu),and on the total wage bill of all workers (W), an estimate of the unit em-ployee compensation of productive workers (ecp) would be sufficient toderive the wage bill of unproductive workers (Wp = ecp • Lp) and also thatof unproductive workers (Wu = W —Wp).

The BLS provides data on the unit wages of production workers invarious sectors, excluding the service sector. But unlike our desired mea-sure of employee compensation, BLS wage data do not include employercontributions to social security and other pension plans.12 It is thereforeadjusted upward by the ratio of employee compensation to wages and sal-aries taken from NIPA data. For the service sector, we use the employeecompensation per full-time equivalent employee (ecserv) as our measure of

11 In NIPA, the value added of proprietorships and partnerships is not brokendown into wages and profits. Ignoring the wage equivalent of self-employedpersons (proprietors and partners) amounts to treating all of the value added asprofit-type income. We have chosen instead to impute a wage equivalent to thelabor of self-employed persons, and treat the rest of value added as profit-typeincome (which may be negative in the case of losses). As Mandel (1976, p. 945)notes, Marx includes "engineers, technologists and even managers" under thecategory of collective labor. Of course, only those involved in capitalist produc-tion would count as productive workers.

12 The BLS wage data differ also in reflecting wage per employed worker, whereasour NIPA-based unit compensation ec is per full-time equivalent worker. Byusing the former, we are implicitly assuming that the wage of the average pro-duction worker is fairly close to that of the average full-time production worker.Since the latter is probably higher than the former, we somewhat underestimatevariable capital.


the employee compensation of workers in productive services (see TableG.I). We have:

(wp)y = unit wage of production workers in the jth production sector,j = 1,..., & (from BLS), except services, for which (wp)serv = ecserv;

= ratio of employee compensation EC to wages and salaries W, in thej th production sector, j = 1,...,/: (from NIPA);

(ecp)y = (wp);-(x,)= estimated employee compensation of production workers in the

yth production sector;13

V, = ecy • (Lp)y = (Wp)y = variable capital in the j th production sector;

V* m Wp = S( Wp)y = total variable capital;

Wu as W - V* = total wages of unproductive workers in all sectors;

ecp = Wp/Lp = average wage of productive workers;

ecu = Wu/Lu = average wage of unproductive workers.

Appendix G provides the details of the calculations. Table 5.6 and Fig-ures 5.8-5.11 present the estimates W, V, Wu, ecp, and ecu for the entireinterval 1948-89. Figure 5.8 contrasts the levels of real variable capitaland of the total real wage bill. Their absolute growth is greater than thatof the corresponding labor totals in Figure 5.7 because the wage measuresalso incorporate the effects of growing real wages. But the relative move-ments of wage and employment measures is virtually the same, as is evi-dent in Figure 5.9. VVW declines by 34%, while Lp/L declines by 37%.Figures 5.10 and 5.11 make quite explicit that the unit wages of productiveand unproductive workers change only slightly, whereas their relative em-ployments change drastically. We can therefore unambiguously concludethat the relative decline in productive to total wages Wp/W (= VVW) isalmost entirely due to the relative decline in productive to total employ-ment Lp/L.

5.4 Surplus value and surplus productThe estimates of variable capital in the previous section allow us

to calculate surplus value and surplus product. By definition,

13 This procedure implicitly assumes that the ratio supplements to wages is the samefor both production and nonproduction workers. Our estimates in Appendix Gjustify this assumption.


S* = VA* — V* = surplus value (in money form);

SVV* = rate of surplus value;

NP* = the necessary product (consumption of productive workers) = V*;

SP* = FP* - N P * = surplus product.

It is instructive to compare these Marxian measures with their orthodoxcounterparts, since naive readings of Marx have tended to confuse thetwo sets (see Section 6.1). Let

(P+) = NNP - EC = profit-type income (gross of all business taxes)14

andP = (P+) - IBT = NNP - IBT - E C = profit (gross of profit tax),

whereNNP = net national product in NIPA = VA = value added;

EC = total employee compensation;IBT = indirect business tax;

(P + ) /EC = ratio of profit-type income to wages; andP/EC = profit/wage ratio.

Appendix H gives further details. Table 5.7 and Figures 5.12-5.15 pre-sent the key Marxian ratios and their orthodox counterparts for 1948-89.Figure 5.12 compares real surplus value and real profits (defined here asreal P). Both rise strongly, but not equally so; real surplus value risesabout 16% relative to real profits. This latter movement is a reflectionof the corresponding decline in productive to total wages, because S* =VA*-Wp = VA*-EC p and (P+) = N N P - E C = VA-EC, and the twomeasures of value added remain fairly close (see Figure 5.4).15 Inciden-tally, it is useful to recall that only production and trading profits appearwithin total surplus value (see Section 3.6.1), so that the connection be-tween S* and (P+) is not direct.

Figure 5.13 is the piece de resistance. It compares the rate of surplusvalue SVV* (which is the rate of exploitation of productive workers) withits "naive" equivalent (P+ ) /EC. At midperiod, the former is almost fourtimes as large as the latter. It also rises by over 40% during the postwar

14 P+ is intended as a "naive" measure of surplus value, as directly derived fromNIPA. Since NIPA does not estimate the wage equivalent, the only wage costdirectly shown would be EC. Hence, P + = VA-EC = NNP-EC.

15 For U.S. data, the orthodox measure VA = P + EC remains within 10% of theMarxian measure VA* = V* + S*, so the difference between P/EC and S*/V* islargely due to the fact that V* = W p « . EC. But we cannot assume that the roughequality that holds for the United States between the two value-added measuresis a universal phenomenon.

Table 5.6. Total wages and variable capital, 1948-89

Variables

WV*vvwwu=w-v*Wreal = W/pc*V*a, = VVpC(Wu)reaI = W u / p cpcecp = VVLp = Wp/Lp

ecu = Wu/Lu

Lu/Lp

ec^ecpLp/L

Variables

WV*vvwwu=w-v*Wreal = W/pca

V ^ ^ W p C(Wu)reaI = Wu/pcpcecp = VVLp = Wp/Lp

ecu = Wu/Lu

Lu/Lp

ecu/ecp

Lp/L

Units

billions of $billions of $

billions of $billions of 1982 $billions of 1982 $billions of 1982 $

$/prod. worker/year$/unpr. worker/year

Units




1948

164.7688.410.54

76.35641.10344.01297.0925.70

2,679.593,017.07

0.771.130.57

1955

252.73120.52

0.48132.21856.71408.53448.1829.50

3,800.094,177.14

1.001.100.50

1949

164.7585.020.52

79.73643.57332.12311.4525.60

2,724.933,100.28

0.821.140.55

1956

272.67128.82

0.47143.85905.88427.99477.90

30.104,042.904,404.69

1.021.090.49

1950

178.7693.160.52

85.60682.30355.58326.7226.20

2,890.853,245.65

0.821.120.55

1957

286.75133.00

0.46153.75925.00429.03495.97

31.004,231.174,610.83

1.061.090.49

1951

206.23105.91

0.51100.32741.84380.98360.8627.80

3,197.523,430.59

0.881.070.53

1958

289.27127.72

0.44161.55915.41404.17511.24

31.604,351.674,834.57

1.141.110.47

1952

222.10111.01

0.50111.08782.03390.89391.1428.40

3,387.823,619.70

0.941.070.52

1959

311.71139.57

0.45172.14965.05432.11532.9532.30

4,649.185,051.31

1.141.090.47

1953

236.85117.39

0.50119.46816.71404.79411.9229.00

3,552.623,828.25

0.941.080.51

1960

328.35144.23

0.44184.12998.03438.39559.6432.90

4,800.215,269.27

1.161.100.46

1954

235.67111.95

0.48123.72809.86384.71425.1529.10

3,584.713,978.90

1.001.110.50

1961

338.08146.13

0.43191.95

1,015.24438.83576.4133.30

4,976.645,425.74

1.201.090.45

Table 5.6 (contj

Variables

WV*

vvwwu=w-v*Wrcal = W/pc"Vt, = VVpc(Wu)rcal = Wu/pcpcecp = VVLp = Wp /L p

ecu = Wu/Lu

L u / L p

ecu/ecp

L p /L

Variables

WV*

vvwwu=w-v*Wreal = W/pc"V*al = VVpC(Wu)real = Wu/pcpcecp = VVLp = W p /L p

ecu = W u /L u

L u / L p

ecu/ecp

L n / L

Units




Units




1962

360.89155.54

0.43205.35

1,064.56458.81605.75

33.905,195.525,679.79

1.211.090.45

1969

624.70261.22

0.42363.48

1,523.65637.11886.5441.00

7,654.588,122.58

1.311.060.43

1963

379.43162.76

0.43216.67

1,103.00473.13629.86

34.405,442.925,913.26

1.221.090.45

1970

667.55270.43

0.41397.12

1,556.06630.38925.6942.90

8,133.968,819.44

1.351.080.42

1964

406.66172.00

0.42234.66

1,161.89491.42670.47

35.005,680.276,242.06

1.241.100.45

1971

712.25287.53

0.40424.72

1,586.30640.37945.9344.90

8,785.459,394.50

1.381.070.42

1965

436.64188.43

0.43248.21

1,226.50529.29697.22

35.606,007.476,403.30

1.241.070.45

1972

783.12324.30

0.41458.82

1,676.91694.44982.4746.70

9,567.509,982.99

1.361.040.42

1966

480.94207.07

0.43273.87

1,310.46564.22746.24

36.706,358.516,723.18

1.251.060.44

1973

875.19370.49

0.42504.70

1,764.49746.95

1,017.5349.60

10,447.4710,550.34

1.351.010.43

1967

515.03216.26

0.42298.78

1,369.77575.15794.62

37.606,581.917,066.52

1.291.070.44

1974

961.23398.50

0.41562.72

1,754.06727.20

1,026.8654.80

11,175.9211,494.79

1.371.030.42

1968

566.66236.77

0.42329.89

1,441.89602.47839.42

39.307,079.287,586.58

1.301.070.43

1975

1,024.74410.75

0.40613.99

1,730.98693.83

1,037.1459.20

12,219.1812,476.44

1.461.020.41

Variables Units 1976 1977 1978 1979 1980 1981 1982

wV*

vvwwu=w-v*Wrea, = W/pca

V*al = VVpc(Wu)real = Wu/pcpc

ec' = Wu/Lu

Lu/Lp

ecu/ecp

Lp/L

Variables

W

v*vvwwu=w-v*Wreal = W/pcfl

V*aI = W p c(Wu)rcal = Wu/pcpc

ecu = Wu/Lu

Lu/Lp

ecu/ecp

Lp/L



, $/prod. worker/year$/unpr. worker/year

Units




1,140.36459.63

0.40680.73

1,821.65734.23

1,087.4362.60

13,254.4413,486.78

1.461.020.41

1983

2,199.81839.73

0.381,360.082,113.17

806.661,306.51

104.1023,269.0722,719.44

1.660.980.38

1,268.47515.81

0.41752.65

1,901.75773.34

1,128.4266.70

14,409.0914,386.11

1.461.000.41

1984

2,404.60928.68

0.391,475.922,218.26

856.721,361.55

108.4024,521.5823,526.17

1.660.960.38

1,433.64589.20

0.41844.43

2,002.29822.91

1,179.3871.60

15,666.2815,373.08

1.460.980.41

1985

2,565.70967.99

0.381,597.712,286.72

862.741,423.98

112.2025,320.8924,655.20

1.700.970.37

1,610.76664.78

0.41945.98

2,059.79850.11

1,209.6978.20

17,223.1816,617.40

1.470.960.40

1986

2,719.89998.55

0.371,721.352,358.97

866.041,492.93

115.3026,063.3225,877.64

1.740.990.37

1,773.25706.53

0.401,066.732,047.64

815.851,231.79

86.6018,659.8818,432.98

1.530.990.40

1987

2,913.091,060.90

0.361,852.192,445.92

890.761,555.15

119.1026,964.9627,020.58

1.741.000.36

1,956.87772.35

0.391,184.522,068.57

816.441,252.13

94.6020,466.3420,129.64

1.560.980.39

1988

3,152.111,146.22

0.362,005.892,537.93

922.881,615.05

124.2028,275.2328,483.03

1.741.010.37

2,071.62786.53

0.381,285.092,071.62

786.531,285.09

100.0021,725.6021,860.07

1.621.010.38

1989

3,337.041,206.40

0.362,130.642,568.93

928.711,640.22

129.9029,318.4129,443.84

1.761.000.36

1 pc = consumer price index.


3000

2400-

1200-

1948 1953 1958 1963 1968 1973 1978 1983 1988

Figure 5.8. Total real wage and variable capital (billions of 1982 dollars).Source: Table 5.6.

0.60

0.55 -

0.50

0 . 3 5 ' i [ i i i i i i i i i i i i i i i i i i i i i i i i i i i i i i i i i i i i i i i i1948 1953 1958 1963 1968 1973 1978 1983 1988

Figure 5.9. Productive employment and wage shares. Source: Table 5.6.

30000

25000

20000 -

15000-

10000

5000-

1948 1953 1968 1973 1978 1983 1988

Figure 5.10. Productive and unproductive employment compensation(dollars per worker per year). Source: Table 5.6.

1.80

1.58 -

0.70 ' i , | | , i | | I l l l I I I i i I I I I I I I i I l l l l l l l l I I

Figure 5.11. Relative rates of employment and compensation.Source: Table 5.6.


Table 5.7. Marxian variables and their orthodox counterparts,1948-89 (billions of dollars)

Variables

S?ealPrtalSVV*PVECc* .V*al

cvv**M/EC

Variables

S?ealPrtaiSVV*PVECC*ealV*a,CVV*"M/EC

Variables

S?ea.Pr+ealSVV*PVECCfealV*a,

c*/v*aM/EC

1948

635.36419.97

1.700.70

880.90344.01

2.351.69

1962

1003.76619.99

2.060.60

1236.52458.81

2.541.44

1976

1535.38864.89

2.110.52

2002.39734.23

2.751.44

1949

632.50410.22

1.750.68

844.07332.12

2.331.63

1963

1042.30648.10

2.070.61

1276.51473.13

2.541.43

1977

1609.41909.93

2.100.52

2162.90773.34

2.821.50

1950

691.46456.83

1.770.70

934.59355.58

2.401.66

1964

1108.02683.63

2.120.61

1329.36491.42

2.541.41

1978

1691.23956.47

2.070.52

2279.49822.91

2.791.50

1951

750.01496.43

1.780.69

1025.69380.98

2.431.63

1965

1168.64733.38

2.100.62

1403.30529.29

2.521.42

1979

1712.77955.47

2.030.50

2316.84850.11

2.741.49

1952

762.77494.71

1.750.64

1051.56390.89

2.421.57

1966

1230.43762.71

2.080.60

1464.38564.22

2.481.39

1980

1706.77921.68

2.070.48

2299.78815.85

2.791.47

1953

789.67503.01

1.740.62

1095.36404.79

2.421.55

1967

1265.74761.79

2.100.58

1476.69575.15

2.451.36

1981

1774.67954.67

2.160.50

2353.89816.44

2.861.50

a Flow ratio.

period, whereas the latter actually falls by almost 30%. Thus P+/EC gross-ly understates the level, and falsifies the trend, of SVV*. The profit/wageratio is not a good proxy for the rate of surplus value.

Figure 5.14 pursues the analysis of the central value categories bybreaking down real total value into its principal components: TV* =C* + v* + S*, in 1982 constant dollars. By far the biggest component isC*, which is roughly 50% of total value.


1954

791.63496.70

1.860.62

1051.12384.71

2.471.54

1968

1309.36779.79

2.080.56

1532.02602.47

2.441.34

1982

1724.68875.79

2.190.46

2251.27786.53

2.861.46

1955

840.27535.24

1.900.64

1118.53408.53

2.521.56

1969

1316.15764.15

2.010.53

1562.30637.11

2.381.31

1983

1795.76951.30

2.220.49

2290.75806.66

2.831.49

1956

843.31517.30

1.840.59

1144.64427.99

2.501.53

1970

1303.99734.08

2.030.50

1521.57630.38

2.361.27

1984

1951.511061.17

2.260.52

2468.56856.72

2.861.51

1957

859.98522.82

1.880.59

1149.23429.03

2.511.52

1971

1343.91778.68

2.080.52

1541.12640.37

2.381.28

1985

2018.491081.37

2.330.51

2491.40862.74

2.881.51

1958

862.46519.34

2.010.59

1104.10404.17

2.571.50

1972

1389.20814.11

1.990.52

1631.40694.44

2.341.28

1986

2089.741096.69

2.400.50

2468.82866.042.841.49

1959

915.87559.07

1.990.60

1172.29432.11

2.551.50

1973

1454.04865.40

1.940.53

1797.57746.95

2.401.33

1987

2152.291124.43

2.420.50

2510.64890.76

2.821.49

1960

927.06557.40

1.990.58

1182.87438.39

2.531.46

1974

1441.19822.84

1.950.50

1824.17727.20

2.471.34

1988

2269.421198.93

2.400.50

2740.99922.88

2.901.49

1961

950.45578.65

2.030.59

1183.78438.83

2.531.45

1975

1462.10822.802.110.51

1836.34693.83

2.651.39

1989

2330.441241.01

2.440.51

2763.35928.71

2.891.49

Finally, Figure 5.15 compares the value composition (of the flows) ofcapital C*/V* with its orthodox counterpart, the ratio of intermediateinputs to wages M/EC. Once again, we see that the orthodox measure isnot a proxy for the Marxian one. C*/V* is from 50% to 90% larger thanM/EC, and during the postwar period rises by 23% while the latter fallsby almost 11%. Neither the level nor the trend of the former is capturedby that of the latter.


3000

1800

19S8 1963 1968 1973 1978 1983 1988

Figure 5.12. Real surplus value S* and profit-type income P+ (millionsof 1982 dollars). Source: Table 5.7.

5.5 Marxian, average, and corporate rates of profitThe production of data on the mass of surplus value S* and profit

P allows us then to estimate and compare three measures of the rate ofprofit: the Marxian general rate of profit r*, defined here as the ratio ofsurplus value to total fixed capital K;16 the average rate of profit r, definedas the ratio of profit-type income net of individual business taxes (P =P + — IBT) to K; and the corporate rate of profit rcorp, which is the ratioof the NIPA measure of corporate profit to the BEA measure of cor-porate capital. We also estimate the value composition of (fixed) capitalC*/V* = K/V*, as well as the materialized composition of (fixed) capitalC*/(V* + S*) = K/(V* + S*). All variables are in current dollars, includ-ing the capital stock that is measured at current replacement costs.

Finally, since we are concerned here with the long-term tendencies ofthe rates of profit, all measured ratios are adjusted for cyclical fluctuationsby means of a measure of capacity utilization developed in Shaikh (1987,1992a). The rate of profit may be thought of as responding to long-termstructural changes in the rate of surplus value and the organic composition

16 More properly, one should add the stock of circulating capital (i.e., inventoriesof raw materials and goods in process, which are the stock equivalents of C* andV*, or M and W in the orthodox case) to the stock of fixed capital. But consis-tent data on the former are not readily available.


3.00

2.40

1.80

0.60

0.00* ' ' 'l983' ' ' 'l988'

Figure 5.13. Rate of surplus value S V V* and profit/wage ratio PVEC.Source: Table 5.7.

3000

2400-

1800-

1200-

Figure 5.14. Components of real total value (millions of 1982 dollars).Source: Table 5.7.


3.00

2.50-

2.00 -

0.50-

0.001948 1953 1958 1963 1968

Figure 5.15. Value composition and the input/wage ratio.Source: Table 5.7.

of capital, and to short-term fluctuations arising from cycles and fromspecific historical events such as wars, droughts, and so on. The latterwill be reflected as fluctuations in the rate of utilization of the capitalstock, which show up as corresponding fluctuations in the mass of profit.To eliminate this effect, we divide the mass of profit by the rate of capac-ity utilization, in much the same way as actual output is traditionallydivided by capacity utilization to estimate potential output.

Table 5.8 and Figures 5.16 and 5.17 present the basic results. The dataare partitioned into two major periods. The main period is from 1948 to1980, during which the rate of surplus value rises modestly by almost22%, the adjusted value composition rises by over 77%, and the adjustedmaterialized composition rises by over 56%. Because the large rise inthe value composition overwhelms the modest one in the rate of surplusvalue, the adjusted Marxian rate of profit falls by almost a third over thisperiod. The NIPA-based average rate of profit r' falls even faster, by over48%, and the corporate rate the fastest of all, by over 57%. These morerapid declines can be explained by the relative rise in the proportion ofunproductive to productive activities, which absorbs a growing propor-tion of surplus value and reduces the amount available as profit (see Sec-tions 5.3 and 5.4).

Table 5.8. Aggregate rates of profit and compositions of capital, 1948-89

Sources

Table H.IBEA 1987Shaikh 1992

Table H.IB-79tf

Table H.I

B-84*BEA 1987

Table H.I

125

Variables

r*'=profit rate adjusted for utilization = rVur* = S*/K* = Marxian general rate of profitS*K* =C* = fixed nonresidential gross private capital

u

r'=r/u = NIPA-based general rate of profitr = P/K*P = V A - E C - I B T = (P+)-IBT

IBT=indirect business tax

Ff;=rn/urn = Pn/K*Pn = ( V A - E C ) - I B T - C P T = (P + ) - IBT-CPT

= P - C P T

(r)corp = (r)corP adjusted for utilization = (r)corp/u(r)corp=corporate rate of profit = Pcorp/Kcorp

P1 corpK c o r p

svv*C*7V* = value composition of fixed capital (adj.)C*V( V* + S*) = (C* V V*)/[l + (SVV*)]

1948

0.520J9

149.94384.30

0.75

0.270.21

78.9120.20

0.230.17

66.51

0.140.11

30.30285.69

1.703.271.21

1949

0.530.37

148.64400.20

0.70

0.270.19

75.1021.30

0.230.16

64.90

0.130.09

28.00297.28

1.753.321.21

1950

0.480.38

165.26438.70

0.78

0.250.20

85.6823.50

0.200.15

67.78

0.140.11

34.90323.98

1.773.671.32

1951

0.490.39

188.25480.80

0.81

0.260.21

99.3125.30

0.200.16

76.71

0.140.11

39.90353.42

1.783.661.32

1952

0.490.38

194.51506.20

0.79

0.250.19

98.4527.70

0.200.16

79.05

0.130.10

37.50372.61

1.753.601.31

1953

0.460.39

204.52526.60

0.84

0.230.19

100.5829.70

0.180.15

80.28

0.120.10

37.70388.72

1.743.761.37

1954

0.480.38

208.20546.20

0.80

0.230.18

101.0329.60

0.190.15

83.43

0.110.09

36.60403.72

1.863.881.36

1955

0.460.39

228.55591.20

0.85

0.230.19

113.2932.30

0.180.15

91.29

0.130.11

47.10436.86

1.904.171.44

1956

0.430.36

236.97650.30

0.84

0.200.17

110.3635.00

0.160.14

88.36

0.110.09

45.70482.66

1.844.241.49

1957

0.450.36

250.25689.70

0.81

0.210.17

114.6437.50

0.170.14

93.24

0.110.09

45.30514.62

1.884.171.45

1958

0.47%0.36

256.15710.90

0.77

0.210.16

115.5438.70

0.180.14

96.54

0.100.08

40.30531.35

2.014.271.42

1959

0.450.38

278.42738.00

0.84

0.210.17

128.0641.90

0.170.14

104.46

0.110.09

51.40552.80

1.994.421.48

SS

82

8

2 2

S3

S

2 =

8

SS 8

R g

3! ?

3®

<=>

S£

cJ

® * jjj 8

^

d §

66

58

- « -

SR

PS

S

^*

R8

2

2S

8

S8

8

StS

SO

OO

NQ

O

© ©

r

~

* o

o

oo

d

d

m

vi

^«

n^

?: | S

2

a

= 2

22

5

8 B

S S

8

°°2o

ov

do

do

o 6

N£ §

3

4

O©

rq

©O

d

dt

^^

O

O

p

O

O

VO

VO

OO

O

OO

fO

O

Q

^,

^c

n

-N ^

—

vo

«-• o

do

'd

d d

t' od <s«n

q6 6 if

«j d^ S

id

d^

^ ^

^

d6

oo

d d

*6 -* d

d

<N

d d

oo

S !: ?

2 !:2

3

2S

^d

d (s

oo o

do

l d

dd

2 *

2

^

I8 E: ?

^2

23

SS

Si

dd

vo

^ d

og

d

d^

1126

Variables 1975 1976 1977 1978 1979 1980 1981 1982 1983 1984 1985 1986 1987 1988 1989

r*'r*S*K*u

r'rPIBT

T'n

P.(r) ^

Peon,

svv*c*vv*C»'/(V* + S<

0.41

0.33867.02

2661.700.79

0.170.13

347.92140.00

0.140.11

297.02

0.070.06

117.602016.46

2.115.11

•) 1.64

0.400.33

968.82

2920.800.83

0.160.13

394.15151.60

0.140.11

329.95

0.080.07

145.202216.71

2.115.271.70

0.380.33

1083.133253.50

0.87

0.160.14

446.88165.50

0.130.11

373.88

0.080.07

174.802469.64

2.105.471.76

0.360.32

1221.07

3774.600.89

0.150.14

512.77177.80

0.130.11

429.27

0.080.07

197.202847.30

2.075.721.86

0.360.32

1346.24

4225.200.89

0.150.13

562.30188.70

0.130.11

474.30

0.070.06

200.103203.38

2.035.671.87

0.360.30

1462.70

4844.400.85

0.140.12

577.88212.00

0.120.10

493.08

0.060.05

177.203681.60

2.07

5.801.89

0.360.30

1668.19

5503.700.84

0.140.12

648.09249.30

0.120.10

566.99

0.050.04

188.004187.64

2.165.951.88

0.380.29

1724.68

5859.200.77

0.140.11

619.39256.40

0.120.09

556.29

0.040.03

150.004471.11

2.195.74

1.80

0.360.31

1865.806094.71

0.84

0.140.12

708.30280.10

0.120.10

631.10

0.050.05

213.704631.59

2.226.111.90

0.37

0.332101.78

6432.910.89

0.150.13

833.38309.50

0.130.11

739.48

0.060.05

264.704899.36

2.266.191.90

0.380.34

2258.686706.44

0.89

0.150.13

880.15329.90

0.130.12

783.75

0.060.05

280.705121.71

2.336.191.86

0.400.34

2401.11

7056.520.85

0.150.13

914.60345.50

0.14

0.11808.30

0.060.05

271.605416.32

2.405.981.76

0.390.34

2563.38

7459.320.87

0.150.13

974.20365.00

0.130.11

847.30

0.060.06

319.805738.57

2.426.121.79

0.390.35

2752.81

7895.580.90

0.150.14

1069.00385.30

0.130.12

932.80

0.070.06

365.006110.95

2.406.171.81

0.390.35

2943.35

8387.490.89

0.150.14

1156.40411.00

0.14

0.121021.30

0.060.05

351.706502.54

2.446.201.80

Notes: Shaikh (1992a) calculates capacity utilization as u = uMHI/s up to 1985, where uMH1 is a capacity utilization index based on the McGraw-Hill survey of capital spending,and s is a shift-work index based on Foss (1984). Since the McGraw-Hill survey was discontinued in 1986, the utilization index uMH, was extended to 1989 by means of a regres-sion on the Federal Reserve Capacity Utilization Index (uFRB). For the years 1948-58, CEA (1971, table C-66) and CEA (1983, table B-77) were utilized.° Table number from CEA (1991).


0.50-

0.10 -(rXcoq>)f«Ptoip/(KcofpXu)

0.00 -h—i—(—i—i—i—i—i—i—i—i—\—\—i—i—i—i—i—i—i—i—i—i—i—i—i—i—i—i—i—i—i—i—i—i—i—i—i—i—i—i—r1948 19S3 1958 1963 1968 1973 1978 1983 1988

Figure 5.16. Aggregate rates of profit. Source: Table 5.8.

10.00

1 . 0 0 ' i i i i i i i i i I i i i i I I I i I i i I i I I I I I I I I1948 1953 1958 1963 1968 1973 1978 1983 1988

Figure 5.17. Rate of surplus value and composition of capital(log scale). Source: Table 5.8.


Table 5.9. Changes in profit rates and basic components

Variable

svv*c*vv*C*'/(V* + S*)r*' (Marxian)r'(average)rcorP (corporate)

Overall change (%)

1948-80

+21.8+77.4+56.2-30.8-48.4-57.1

1980-89

+ 17.9+6.9-4 .8+8.3+9.9+7.0

Annualtrend rate (c

1948-80

+0.6+ 1.6+ 1.2-1.0-1.8-2.2

Po)

1980-89

+ 1.8+0.7-0.6+ 1.1+ 1.2+2.6

The second period represents the Reagan-Bush era from 1980 to 1989,in which the capitalist class unleashed a systematic assault on workers'living standards and working conditions (see Section 5.9 for further de-tails). The rise in the rate of surplus value accelerates over this interval, itstrend rate more than doubling. Moreover, the rates of growth of C*/V*and C*/(V* + S*) slow down in this period, because the rate of profit isstill low and accumulation is slow (which in turn slows down the adoptionof new, more capital-intensive technologies). The overall effect is to re-verse the trends in the three measures of the rate of profit: During thisnine-year interval, the Marxian rate of profit recovers about 7% of itsinitial (1948) value, the NIPA-based average rate about 5%, and the cor-porate rate a mere 3%. Table 5.9 summarizes these patterns, with trendrates calculated by regressing the logged values of variables against time.Further analysis of the relation between profitability and accumulation inthe postwar period can be found in Shaikh (1987).

5.6 Rates of exploitation of productive and unproductive workersThe rate of exploitation is the ratio of surplus labor time to nec-

essary labor time. This can be calculated for any capitalistically employedwage labor, be it productive or unproductive. Necessary labor time issimply the value of the labor power involved, that is, the labor value ofthe average annual consumption per worker in the activities in question.Surplus labor time is excess of working time over necessary labor time. Inthe case of productive workers, their rate of exploitation is also the rateof surplus value, since their surplus labor time results in surplus value.

The first step is to calculate the relative rates of exploitation of unpro-ductive and productive labor, in the manner derived in Section 4.2:


3.00

2.50-

2.00 -

1.50

1.00-

0.501948 19S3 1958 1963 1968 1973 1978 1983 1988

Figure 5.18. Rates of exploitation and related measures.Source: Table I.I.

l + eu _ hu/hp

l + e p ~ e c u / e c p '

whereeu> ep = rates of exploitation of unproductive and productive workers;hu, hp = hours per unproductive and productive worker;

ecu, ecp = employee compensation per unproductive and productiveworker.

Because the rate of exploitation of productive workers is simply therate of surplus value, we can directly estimate the rate of exploitation ofunproductive workers. We use the money rate of surplus value SVV*since we already know that it is quite close to the value rate, as shown inSection 4.2:

e,,= ecu/ecp.[1 + SVV*].

The detailed calculations are in Appendix I. Figure S.18 displays thebasic results. The relative rates of exploitation eu/ep depend on two setsof factors: relative working times hu/hp, which never vary by more than


2% (as shown on the middle of the three lower curves in Figure 5.18);and relative wage rates ecu/ecp. At the beginning of the postwar periodthe wage of unproductive workers is some 11%-12% higher than thatof productive workers, but this relative advantage gradually disappearsuntil, by the end of the period, unproductive wages are 3%-4% lowerthan productive wages (see the highest of the three lower curves). Asa result, the relative rates of exploitation move in exactly the oppositefashion (the lowest curve). Looking at the separate rates themselves, wesee that the top two curves of Figure 5.18 both rise strongly over the post-war period, with rate of exploitation of unproductive workers startingout below that of productive workers but surpassing it after 1973. Formost of the postwar period, the two rates stay within 10% of one an-other.17

5.7 Marxian and conventional measures of productivityPrecisely because the Marxian concept of production differs great-

ly from the orthodox concept, the corresponding measures of productivityare also very different. The logic of these measures is outlined in whatfollows; all other details are in Appendix J.

In Marxian terms, the appropriate measure of productivity q* is theconstant-dollar total product TPr divided by the total number of produc-tive worker hours Hp. The corresponding orthodox measure is y, theratio of constant-dollar gross domestic product GDPr divided by total(productive and unproductive) hours worked Hj. Two variants of theorthodox measure are shown: real GDP per employee hour y, and non-farm business real GDP per hour of persons engaged y2 (yi is the equiva-lent BLS measure shown in Appendix J, which is only available in index-number form). Finally, because orthodox measures are always based onthe final product (GDP) rather than the total product, we also calculatea quasi-Marxian measure y * as the ratio of real Marxian gross final prod-uct GFPr to hours of productive labor Hp. This has a much lower levelthan the true measure q*, but has essentially the same trend. Within thelimits of the approximation of the Marxian final product added by GDP(see Table 5.4), we can therefore approximate the trend of the true mea-sure by the ratio of real GDP to hours of productive labor Hp:

17 Implicit in such a calculation is the notion that the differences in productive andunproductive wage rates do not reflect differences in skill. Insofar as part of suchwage differentials do reflect skill differences, the skill-adjusted relative rates ofexploitation will be even closer than our unadjusted figures. It should also beborne in mind that the productive and unproductive sectors are aggregates ofvery many individual sectors, so factors such as gender and race discriminationare likely to be fairly similar across such broad composites.


q* = TPr/Hp = Marxian measure of labor productivity;

y • GDPr/H = conventional measure of labor productivity;

y* s GFPr/Hp = quasi-Marxian measure of labor productivity,

whereTPr = constant-dollar product s TP*/py;

py = GNP deflator from NIPA;18

GFPr = constant-dollar Marxian gross final product = GFP*/py;Hp = productive labor;

GDPr = constant-dollar GDP (real gross domestic product); andH = all labor (productive and unproductive).

Appendix J contains detailed calculations of the Marxian and ortho-dox measures of productivity, along with associated measures of hoursworked. Table 5.10 and Figures 5.19 and 5.20 present the data. Figure 5.19compares the two Marxian measures of productivity q* and y* with theorthodox measure y. Figure 5.20, which is in index number form, alsodepicts orthodox measures y2 and y! (BLS). All measures in Figure 5.19grow steadily throughout the postwar period, and exhibit a slowdown intheir growth rate over time (Figure 5.19 is a log graph, so that the slopeof a curve is the variable's rate of growth). Yet, as Figure 5.19 shows,the Marxian measure of productivity q* is between three and four timesas large as the conventional measure y. Moreover, q* rises relative to yfor significant periods. This is most notable during the post-1972 period,which is exactly when the pernicious and puzzling "productivity slow-down" is supposed to have occurred (Naples 1987). Notice from Figure5.19 that the growth rate of q* slows down gradually over the entire post-war period, whereas y shows a marked change in pattern in the criticalperiod from 1972 to 1982. Figure 5.20 shows that the Marxian measures(q*> y*) grow substantially faster than the orthodox measures (y, y2, yi).

The ratio y/q* = (GDP/TP*)/(L/Lp).19 We have already seen in Figure5.4 that GNP/TP* falls from 1972 to 1982, most probably because theoil-price shock in 1973 raises TP* relative to GDP. At the same time, theratio of total employment relative to productive employment rises morerapidly in this period (because of the relatively rapid growth of unpro-ductive employment), as shown in Figures 5.9 and 5.11. The so-calledproductivity showdown exhibited by the conventional measures (y, yt, y2)in this critical period is the result of these two disparate movements.

18 We chose the implicit GNP deflator because it allows us to deflate both measuresin the same way, so that any differences between q and y only reflect the differ-ences between Marxian and orthodox production measures.

19 The same deflator was used for both real figures, so their real ratio is the sameas their nominal ratio.

Table 5.10. Marxian and conventional measures of productivity, 1948-89

Variables

q* = TPr/Hp

q* (index numbers)a

y* = GFPr/Hp

y* (index numbers)y = GDPr/Hly (index numbers)y,(BLS; 1948 = 100)y2 = GDP2r/H2c

y2 (index numbers)

Variables

Units

$/hr worked, prod, workers


$/hr worked, pt & ft workers*

GDP in $/hr worked by PEP$/hr by workers & SEP

Units

1948

27.56100.0015.30

100.0011.11

100.00100.00

9.59100.00

1955

1949

28.98105.1516.30

106.5011.51

103.61101.7110.03

104.57

1956

1950

30.30109.9616.93

110.64

11.98107.82108.1710.57

110.16

1957

1951

32.04116.2517.83

116.5412.14

109.27

111.4110.87

113.27

1958

1952

33.02119.82

18.39120.1812.34

111.08114.0711.20

116.71

1959

1953

34.21124.14

19.03124.3612.68

114.16116.54

11.60120.92

1960

1954

35.77129.7820.10

131.3513.02

117.22

118.2511.95

124.50

1961

q*=TPr/Hp

q* (index numbers)*y* = GFPr/Hp


y2 (index numbers)





36.55132.6320.48

133.8213.27

119.51121.6712.29

128.06

37.32135.41

20.86136.32

13.26119.39122.4312.39

129.12

38.67140.3221.71

141.8813.52

121.72124.71

12.63131.65

40.70147.6923.09

150.8813.87

124.89127.57

12.81133.47

41.61150.97

23.61154.3014.21

127.97131.7513.33

138.89

42.57154.4624.18

158.0214.34

129.07

133.0813.41

139.75

43.82159.02

25.05163.7414.72

132.57

137.4513.79

143.74

Table 5.10 fcont.)

Variables

q* = TPr/Hp

q* (index numbers)0

y* = GFPr/Hp


y2 (index numbers)

Variables

Units





Units

1962

44.88162.8425.71

168.02

15.05135.49141.8314.16

147.60

1969

1963

46.09167.2626.43

172.7315.40

138.66

146.9614.56

151.70

1970

1964

48.01174.2027.67

180.85

15.88142.98152.8515.08

157.12

1971

1965

48.71176.7428.09

183.61

16.18145.68

156.6515.36

160.07

1972

1966

49.36179.1128.59

186.8616.32

146.94160.2715.51

161.63

1973

1967

50.64183.7329.51

192.8416.57

149.16164.2615.83

165.01

1974

1968

51.73187.7030.16

197.11

16.89152.06169.2016.18

168.65

1975

q* = TPr/Hp

q* (index numbers)a

y* = GFPr/Hp

y* findex numbers)y = GDPr/Hly (index numbers)

y,(BLS; 1948 = 100)y2 = GDP2r/H2'y2 (index numbers)





51.63187.3630.10

196.71

16.82151.46168.6316.04

167.19

52.93192.0731.04

202.8317.06

153.61

169.3916.07

167.50

55.03199.6932.40

211.7617.61

158.57174.52

16.49171.86

55.58201.67

32.61213.12

17.97161.76179.8516.80

175.06

57.21207.6033.01

215.7718.09

162.90183.6516.74

174.46

57.60208.9932.92

215.1317.92

161.37180.23

16.58172.85

61.64223.67

35.00228.72

18.25164.34

183.4616.93

176.40

Variables Units 1976 1977 1978 1979 1980 1981

a 1948 = 100 for all index numbers. b pt=part-time; ft = full-time. c Nonfarm private business.

1982

q* = TPr/Hp

q* (index numbers)a

y* = GFPr/Hp

y* (index numbers)y=GDP r /Hly (index numbers)

y,(BLS; 1948 = 100)y2 = GDP2r/H2c

y2 (index numbers)

Variables

q*=TPr/H p

q* (index numbers)*

y* = GFPr/Hp

y* (index numbers)y = GDPr/Hly (index numbers)

y,(BLS; 1948 = 100)y2 = GDP2r/H2c

y2 (index numbers)





Units





63.70231.1335.63

232.8518.58

167.32188.4017.34

180.70

1983

71.66260.0240.17

262.51

19.56176.10

195.6317.94

187.00

65.61238.0836.28

237.09

18.81169.34

191.8317.57

183.17

1984

73.13265.3741.04

268.2319.90

179.14

199.8118.20

189.72

66.02239.57

36.50238.53

18.94170.55193.5417.65

183.98

1985

74.25269.4141.92

273.9620.01

180.19202.47

18.40191.73

65.55237.8536.30

237.24

18.77169.02

190.4917.38

181.10

1986

74.75271.2542.75

279.4220.45

184.08206.65

19.62204.44

66.99243.08

37.04242.09

18.91170.24

189.9217.49

182.27

1987

74.47270.2142.81

279.7820.54

184.95208.75

19.64204.71

69.13250.86

38.26250.07

19.20172.85

191.8317.68

184.27

1988

78.01283.0544.29

289.4821.07

189.67

213.8819.37

201.84

70.28255.00

39.08255.42

19.10171.93

190.1117.48

182.17

1989

78.03283.1344.56

291.1921.15

190.41

212.3619.33

201.47

I / I


100

q*=TPr/Hp

y*=GFPr/Hp

y=GDPr/Hl

10 -h—i—i—i—i—i—i—i—i—i—i—i—i—i—i—i—i—i—i—i—i—i—i—i—i—i—i—i—i—i—i—i—i—i—i—i—i—i—i—i—i—p1948 19S3 1958 1963 1968 1973 1978 1983 1988

Figure 5.19. Productivity measures (1982 dollars, log scale).Source: Table 5.10.

1953 1958 1963 ' 1968 1973 ^ ' 1978

Figure 5.20. Productivity indexes (1982 dollars, 1948 = 100).Source: Table 5.10.


5.8 Government absorption of surplus valueAnother issue concerns the relation between total surplus value

and government purchases of commodities and of labor power. Govern-ment purchases of commodities directly absorb a portion of the surplusproduct, and government administrative employment indirectly absorbsanother portion through the consumption expenditures of the govern-ment workers (see Section 3.2.B). Thus total government expenditureG£ s G* + WG is a measure of the total absorption of the surplus productby unproductive government expenditures. Table 5.11 and Figure 5.21show the progress of G£ and G£/SP* over the postwar period. What ismost striking here is the stability of the government share of the surplusproduct. For most of the postwar period, this share remains around 35%,in spite of the Korean War buildup from 1950 to 1953 (itself followingupon the demobilization after World War II) and the Vietnam War build-up from 1965 to 1968.

5.9 Net tax on labor and adjusted rate of surplus valueAs noted in Section 3.3, the nominal wages of production work-

ers must be adjusted for the net transfers of royalties (ground rent, inter-est, and taxes) from variable capital. We calculate only the portion of thisarising from the net transfer between workers and the state. The method-ology and actual estimates are from Shaikh and Tonak (1987) for theUnited States from 1952 to 1985.20 Our adjustment procedure involvestwo steps. First, we estimate the social benefit expenditures directed to-ward wage and salary earners by the state, the taxes paid by them, andthe difference between the two, which is the net transfer (a positive num-ber when benefits exceed taxes and negative in the opposite case). Thetrue compensation of wage and salary earners is their apparent compen-sation plus the net transfer.21 The tax, benefits, and net transfer rates arealso calculated relative to the apparent employee compensation. The nextstep is to adjust the rate of surplus value for the net transfer from variablecapital. The previously derived net transfer rate is applied to apparentvariable capital V* to estimate the net transfer from variable capital, andthe resulting sum is added to V* and subtracted from S* to obtain theadjusted rate of surplus value.

It is important to note that the taxes we estimate are those flowing di-rectly out of total employee compensation (the purchase price of labor

20 The necessary data are only available from 1952 onward. See Tonak (1984, chap.4, and apx. 1-2).

21 Employee compensation is our starting point because it represents the direct costincurred by capitalists for hiring labor power; to the individual capitalist this isthe same as variable capital. But for the system as a whole, we must adjust forthe net transfer between wage and salary workers and the state.

Table 5.11. Government absorption of surplus value, 1948-89 (billions of dollars)

Sources

Table E.2Table E.2Table H.I

Sources


Sources


Variables

G* = G* + WGG*WG

SP*G*/SP*

Variables

G*=G* + WGG*WG

SP*G*/SP*

Variables

G*=G* + WGG*WG

SP*G*/SP*

1948

32.5014.4018.10

149.910.22

1955

74.8540.0534.80

228.160.33

1962

115.6660.2655.40

319.540.36

1949

38.8618.7620.10

148.580.26

1956

79.0941.8937.20

236.740.33

1963

120.8261.5259.30

337.070.36

1950

38.6217.4221.20

165.090.23

1957

86.7346.9339.80

249.880.35

1964

126.8162.4164.40

364.000.35

1951

60.2032.5027.70

188.260.32

1958

94.6351.7342.90

256.040.37

1965

135.1065.8069.30

394.440.34

1952

75.5644.0631.50

194.790.39

1959

96.7251.9244.80

278.340.35

1966

154.5476.1478.40

430.090.36

1953

82.3649.9632.40

204.290.40

1960

99.0350.9348.10

285.930.35

1967

175.3087.9087.40

453.420.39

1954

75.5942.5933.00

208.230.36

1961

106.3754.7751.60

295.950.36

1968

192.2294.4297.80

493.120.39

Sources Variables 1969 1970 1971 1972 1973 1974 1975


Sources


Sources


G* = G* + WGG*WG

SP*G?/SP*

Variables

G*=G* + WGG*WG

SP*G*7SP*

Variables

G* = G* + WGG*WG

SP*G*/SP*

200.4692.96

107.50523.25

0.38

1976

337.29133.49203.80971.25

0.35

1983

624.39257.99366.40

1867.150.33

210.1390.63

119.50546.86

0.38

1977

363.34142.84220.50

1086.660.33

1984

679.89289.29390.60

2103.700.32

222.7692.46

130.30596.04

0.37

1978

396.97156.47240.50

1221.760.32

1985

755.83336.83419.00

2258.310.33

238.6496.04

142.60645.51

0.37

1979

435.78175.38260.40

1347.440.32

1986

797.00353.20443.80

2389.250.33

253.4798.47

155.00719.63

0.35

1980

494.43206.13288.30

1463.670.34

1987

837.34365.44471.90

2555.520.33

284.33115.63168.70778.82

0.37

1981

547.37230.67316.70

1669.400.33

1988

871.73366.63505.10

2755.180.32

318.29130.59187.70868.78

0.37

1982

598.61254.71343.90

1726.060.35

1989

925.91384.31541.60

2945.320.31


0.50

1948 1953 1958 1963 1968 1983

Figure 5.21. Government absorption of surplus value (G£/SP*).Source: Table 5.11.

power to individual capitalists). From a Marxian point of view, we areconcerned with the actual flows of royalties into, and out of, the actualflow of variable capital. This is what Ursula Hicks (1946) has called thestatistical or "social accounting calculation" of taxes:

We arrive thus at two fundamental concepts in fiscal theory: (i) the so-cial accounting calculation of the proportions of people's incomes paidover to taxing authorities in a defined period, and (ii) the analysis of allthe economic adjustments through time and space resulting from a par-ticular tax. These two concepts are different in kind Social account-ing is concerned with a statistical comparison at a moment of time . . .[whereas] the analytical concept is essentially hypothetical. It is a com-parison of two complete economic situations, one with a particular taxin force, the other without it. One of these setups will normally be imag-inary. (U. Hicks 1946, p. 49)

We do not attempt here to estimate the analytical or "tax-shifting" inci-dence of taxes. As Hicks notes, this latter calculation concerns itself withthe comparison between the actual level of some income and the hypo-thetical alternative level that might exist in the absence of some taxes.It is a further stage of analysis which requires some plausible model ofthe overall impact of taxes on reproduction; such models are beyond thescope of our present analysis. Thus we concern ourselves only with the


0.35

1956 1960 1964 1972 1980 1984 1988

Figure 5.22. Benefit and tax rates relative to total employeecompensation. Source: Table N.2.

social accounting of taxes and transfers. However, it should be notedthat, where such calculations have been made, they greatly strengthenour conclusion that the net balance is strongly against the working popu-lation; that is, U.S. workers pay a net tax to the state, rather than receiv-ing a net subsidy from it in the form of some "social wage" (Miller 1989).

Appendix N lists the detailed calculations of our social accounting oftaxes and benefits. Figure 5.22 shows the resulting tax and benefit rates(relative to total employee compensation), and Figure 5.23 shows the cor-responding net transfer rate for the United States from 1952 to 1985. Itis immediately evident that, for most of the postwar period, wage andsalary earners paid more in taxes than they received in social benefit ex-penditures. As a result, the true rate of surplus value is generally higherthan the apparent one (see Figure 5.24).

5.10 Empirical effects of price-value deviationsThe previously calculated Marxian measures are the money forms

of Marxian categories - the monetary expressions of realized quantitiesof value. It is therefore of interest to see if these money measures accu-rately represent the levels and movements of the underlying labor value


0.10

0.05 -

-0.05 -

1952 1956 1960 1964 1968 1972 1976

Figure 5.23. Net transfer rate. Source: Table N.2.

1988

1.60 • , , , , , , i , — , , , , , , , , — i , , , , , i — r - i

1952 1977 1982 1987

Figure 5.24. Rate of surplus value adjusted for net taxes.Source: Table N.2.


magnitudes. In other words, we now ask: How significant is the impactof price-value deviations on aggregate measures?

The problem can be approached indirectly by looking at the empiricalmagnitudes of price-value deviations. Shaikh (1984) has argued on math-ematical and structural grounds that individual price-value deviations arelikely to be modest, and that their effects on aggregate measures are likelyto be quite small. He examines a variety of different empirical estimates,and finds that they provide support for the argument. Ochoa (1984,1988)makes a more detailed and systematic investigation of this issue, estimat-ing labor values for the five available input-output tables between 1947and 1972 in the United States. He finds that the average absolute devia-tion of market (producer) prices22 from labor values is only about 12%,and that the average deviation of the market rate of profit from the cor-responding labor value rate of profit is less than 1% (and never exceeds3.5% in any one year). He also calculates Sraffian prices of production,and finds that on average these too deviate from labor values by only15%, while the corresponding "uniform" rate of profit deviates from thelabor value rate by less than 4% (and never exceeds 5%) (Shaikh 1984;Ochoa 1984b, pp. 128, 143, 151, 162, 214; Ochoa 1988, pp. 420-1, tables1-3). Similar results have been found by Petrovic (1987) for Yugoslavia.

On the basis of these results, we would expect that estimates of the valuerate of surplus value would be quite close to the money rate, providedthe method of estimation is consistent in the sense discussed in Section4.1. Following the procedure developed by Shaikh in 1975, Khanjian (1989)has made direct estimates of both labor value and money rates of surplusvalue. His methodology is that outlined in Section 4.1, and his empiricalprocedures are similar to ours except for the treatment of the wage equiv-alent of self-employed persons. We split the income of unincorporatedenterprises into the wage equivalent WEQ of proprietors, partners, andunpaid family members and a profit-type return, whereas he implicitlytreats the whole of unincorporated income as a profit-type return. Thus hismeasure of surplus value is larger than ours, and his measure of variablecapital is smaller. These two effects make his estimates of the rate of sur-plus value roughly 20% higher than ours.

Because Khanjian's method of estimating the value rate of surplus valueis consistent with his estimates of the money rates, the difference between

22 It would be preferable to examine purchaser-price-labor-value deviations, butthis is not possible because input-output tables do not contain enough informa-tion to estimate purchaser prices of individual commodities (since the tradingmargins on the individual commodities in a given column are all aggregated intoone trading-row entry).


Table 5.12. Labor value and money rates of surplus value

Revenue sidee*iSVV*e = S/V(e-e*)/e

Use sidee* = S*/V*e = S/V(e-e*)/e

1958

2.4452.6387.3%

2.4442.6056.2%

1963

2.4672.6446.7%

2.4672.6175.7%

1967

2.6482.8848.2%

2.6482.8587.3%

1972

2.6062.8749.3%

2.6042.8498.6%

1977

2.6742.9138.2%

2.6302.8909.0%

Source: Khanjian (1989, table 19).

the two sets of measures is an index of the aggregate impact of purchaser-price-labor-value deviations. Table 5.12 shows that these differences areminor, ranging from 6% to 9%. Note that the value rate of surplus valueis always smaller than the money rate (although they have the same trend).This is apparently due to the fact that the prices of consumer goods havehigher trading markups than the average bundle of goods in net out-put (consumer goods pass through both wholesale and retail channels,whereas investment goods do not). By construction, the price of the aver-age commodity is equal to its value.23 The relatively greater markup ofconsumer goods tends to make their purchaser prices higher than laborvalues, leading to a money form of variable capital V* which is higherthan the value of labor power V, as well as a money rate of surplus valueS*/V* which is lower than the value rate S/V (Khanjian 1989, pp. 109-13).

The small and stable differences between the value and money rates ofsurplus value implies that their trends are virtually identical. Figure 5.25,which plots the use-side measures of the two rates, makes it abundantlyclear that the money rate of surplus value is an excellent index of thevalue rate of surplus value.

5.11 Approximating the rate of surplus valueOur own calculations of the rate of surplus value have required

a large amount of detailed data, ranging from several input-output tables23 We define direct price (money price proportional to labor value) as the labor

value multiplied by the ratio of the sum of total prices TV* to the sum of totalvalues TV. Alternately, one could define the realized value represented by anymoney price as the money price multiplied by TV/TV*. In either case, the aver-age purchaser price equals the average labor value.


3.50

1964

Figure 5.25. Value (S/V) and money (S*/V*) rates of surplus value,use side. Sources: Khanjian (1989, table 19); Table 5.7.

to annual NIPA data by major industry and annual BLS data on pro-duction and nonproduction workers by major industry. It is of interest,therefore, to ascertain whether a simpler and more intuitive approxima-tion of the rate of surplus value can be constructed. This has particularimportance for countries and periods in which the necessary detail formore precise estimates is unavailable.

Variable capital is the employee compensation of production workers inproductive sectors. One widely used approximation (see the estimates byLabor Research Association 1948, Eaton 1966, and Papadimitriou 1988in Section 6.2.2) is to take the total employee compensation (of both pro-duction and nonproduction workers) in the productive sectors (agricul-ture, mining, construction, transportation and public utilities, manufac-turing, and productive services). Note that this proposed approximationV*' would be larger than the actual variable capital V*, because it wouldinclude the wages of nonproductive workers in the productive sectors.

A commonly cited definition of Marxian value added is the sum of allwages, profits, taxes, interest, and rents (e.g., Gillman 1958 in Section6.2.1). In Section 3.2.1 we saw that orthodox NNP is the sum of all sec-toral wages, profits, and taxes, plus sectoral net interest paid to house-holds, government, and foreigners. Net interest paid by businesses to the


finance sector, as well as business rental payments, are not included inNNP but are rather shifted into intermediate inputs. Therefore, to actu-ally estimate the sum of all wages, profits, rents, and interest paid bybusiness, one would have to shift these items back into value added. Thisapproximation is larger than NNP, and hence larger than Marxian valueadded.24

The approximation to variable capital is V*', the sum of employee com-pensation in agriculture, mining, construction, transportation and publicutilities, manufacturing, and productive services (defined as all servicesexcept business services, legal services, miscellaneous professional ser-vices, and private households, as in Table E.I and Table F.I, note 3). Toarrive at the Marxian value added approximation VA*', we need onlyadd to NNP estimated business net rental payments and net interest pay-ments to the finance sector. Such information can be derived from busi-ness sources, or as Mage (1963) does, from tax information on businessrevenues and expenses (see Section 6.2.2). In our case, the sum of theselatter two items appears in the royalty row of the production, trade, androyalties columns, respectively, in the overall summary IO table of Fig-ure 3.11. Table 5.13 summarizes the calculation procedure and its results.

Both V*' and VA*' considerably overstate the corresponding true mea-sures. Nonetheless, in a ratio the two biases offset each other, thus pro-viding a fairly good overall approximation to the rate of surplus value.Figure 5.26 demonstrates this result.

5.12 Summary of empirical resultsThe purpose of these investigations has been to examine the em-

pirical relation between Marxian and orthodox measures. By and large,we have found them to be very different in size and trend, and to producea very different picture of capitalist reality. Nowhere is this more strikingthan in the differences between key Marxian variables and their orthodoxcounterparts, as in Figures 5.3, 5.9, 5.12, 5.13, 5.15, and 5.19. Table 5.14summarizes the relative changes in these variables over the postwar period,and - in the case of the productivity measures - over the critical period1972-82 in which the productivity showdown puzzle is supposed to belodged.

Not all Marxian variables exhibit different patterns from their orthodoxcounterparts. The two measures of gross value added, GVA* and GVA,were quite close in size throughout the postwar period. And althoughthe Marxian measure of the rate of profit was substantially higher than a

24 Marxian value added VA* is empirically smaller than NNP, but this result doesnot seem to be a logical necessity.

Table 5.13. Approximation to the rate of surplus value, 1948-89

Sources

Table H.I

112 \a

Table D.2

Table G.ITable G.2

Sources

Variables

svv*Approximation procedure:S*//V*/=(VA*/-V*/)/V*/

VA*'=NNP + RYry + RYp + RY,NNPRYry + RY' + RYt't

V*'=ecp r o d + ecprserv

e c p r o d

^^prserv

Variables

1948

1.70

1.83i 255.71

241.2014.5190.2280.859.37

1955

1949

1.75

1.91254.24238.40

15.8487.4477.77

9.67

1956

1950

1.77

1.91282.06264.60

17.4696.9986.7810.22

1957

1951

1.78

1.88325.64306.20

19.44112.88101.87

11.01

1958

1952

1.75

1.84344.03322.5021.53

121.21109.60

11.61

1959

1953

1.74

1.78364.75340.7024.05

131.40118.8912.51

1960

1954

1.86

1.86366.03340.0026.03

127.93114.95

12.98

1961

Table H.I

112 ltf

Table D.2

Table G.ITable G.2

SVV*Approximation procedure:S*'/V*'=(VA*'-V*')/V*'

VA*/=NNP + RYr/y

NNPRYr'y p + RYt't

y p

V * ' = e c p r o d + ecprservec,ecn

prod

1.90 1.84 1.88 2.01 1.99 1.99 2.03

1.88399.72371.5028.22

139.00124.80

14.20

1.80421.09390.1030.99

150.63135.2215.41

1.81443.57409.90

33.67157.66141.05

16.61

1.92450.39414.00

36.39154.30136.7917.51

1.91490.75451.20

39.55168.53149.61

18.91

1.90510.31468.9041.41

176.20155.5020.70

1.96529.46486.1043.36

178.71156.7821.93

£ Table 5.13 (cont.)oo

Sources

Table H.I

112 1*Table D.2

Table G.ITable G.2

Sources

Variables

svv*Approximation procedure:S*'/V*'=(VA*'-V*')/V*'

VA*'=NNP + RYr'y + RY; + RYt'tNNPRYr'y + RY; + RYt't

* ^^prod "•" ^Cprserv

eCprodvvprserv

Variables

1962

2.06

1.97570.28525.2045.08

191.77168.0223.75

1969

1963

2.07

2.00602.63555.5047.13

201.01175.5225.49

1970

1964

2.12

2.01646.90595.9051.00

214.89187.4327.46

1971

1965

2.10

2.04703.68647.70

55.98231.65201.8529.80

1972

1966

2.08

2.02772.44709.90

62.54256.16223.11

33.05

1973

1967

2.10

2.02818.21749.00

69.21270.94234.21

36.73

1974

1968

2.08

2.01894.25818.7075.55

297.46256.3641.10

1975

Table H.I

112 la

Table D.2

Table G.ITable G.2


VA* '=NNP+RY;V+RY;+RYt;NNPRYry + RYp + RYt't

V*'=ec p r o d + ecprserv

ececn

prod

2.01

1.95966.06882.50

83.56327.22280.4846.74

2.03

1.961016.51926.60

89.91342.87291.04

51.82

2.08

2.061103.471005.10

98.37360.64303.8256.82

1.99

2.051212.861104.80

108.06397.58333.9563.63

1.94

2.041361.961241.40

120.76448.58377.2871.30

1.95

1.991468.281335.40132.88491.77411.81

79.96

2.11

2.101528.211436.60

145.61511.13421.93

89.20

Sources Variables 1976 1977 1978 1979 1980 1981 1982

Table H.I

112 1°Table D.2

Table G.ITable G.2

Sources

Table H.I

112 1*Table D.2

Table G.ITable G.2


VA*'=NNP + RYr'y + RY; + RYt'tNNPRY; + RY; + RYt't

* = CC pr0<j + eC p r s e r v

eCprod

^ prserv

Variables

SVV*Approximation procedure:S*VV*'=(VA*'-V*')/V*/

VA*'=NNP + RYr'y + RYI + RYt'tNNPRY;y + RYp- + RYt't

v * / = ecp r o d + ecprserve c p r o d

^C prserv

2.11

2.081768.911603.60

165.31574.52474.79

99.73

1983

2.22

2.233423.123009.10414.02

1060.52839.31221.21

2.10

2.091985.441789.00196.44643.32533.13110.19

1984

2.26

2.293813.153356.80456.35

1158.17919.34238.83

2.07

2.082251.332019.80231.53731.84605.22126.62

1985

2.33

2.364103.643577.60526.04

1222.88963.89258.99

2.03

2.042507.182242.40

264.78824.04682.08141.95

1986

2.40

2.444377.913771.50606.41

1272.37994.68277.69

2.07

2.042725.122428.10

297.02895.62734.30161.32

1987

2.42

2.494703.774028.60

675.171346.921035.67311.24

2.16

2.093040.722704.80

335.92984.62803.02181.60

1988

2.40

2.515088.974359.40

729.571451.531108.04343.49

2.19

2.083137.272782.80

354.471017.83814.52203.31

1989

2.44

2.575447.864646.40

801.461526.371152.03374.34

a From NIPA (e.g. BEA 1986), where the first three digits denote the relevant table number and subsequent digits the line numbers within thosetables.

vo


1978 1983

Figure 5.26. Approximation to the rate of surplus value.Source: Table 5.13.

1988

NIPA-based general rate and the observed corporate rate, all three ex-hibited similar tendencies to decline from 1948 to 1980, and then to re-verse themselves slightly thereafter. Finally, we found that it was possibleto construct a good approximation to the rate of surplus value largelyfrom NIPA data alone. This allows us the possibility of estimating therate of surplus value for countries and periods in which the detailed datawe would prefer is unavailable.

There were some surprises in the data, in that several key Marxianratios were extremely stable over the entire postwar period. The produc-tive and trade-sector shares of total value, and the intermediate and final-use shares of the total product, both remained virtually constant overtime, as shown in Figures 5.5 and 5.6. A similar and interesting resultwas the close parallelism between the unit wages of productive and unpro-ductive workers in Figures 5.10 and 5.11, and hence between the ratiosV*/W and Lp/L in Figure 5.9. Finally, there was the surprising stabilityof the share of the surplus product absorbed by unproductive governmentactivities, as depicted in Figure 5.21.

The data also uncovered some strong empirical trends. The rate of sur-plus value S*/V* rose significantly over the postwar period, as did thevalue composition of capital C*/V* and the productivity of labor q*, asseen in Figures 5.13, 5.15, and 5.19. respectively. The Marxian rate of


Table 5.14. Comparison of key Marxian and orthodoxmeasures

Variable

TPVGPTPVGNPLp/LVVWSVPCVV*M/ECsvv*PVECqVy

a + 1.2% per annum.

Typicalrelativelevels1967

82%147%44%42%

224%245%136%210%

58%306%

*+1.9«

Change inrelative levels

1948-89 1972-82

-12%-14%-37%- 3 3 %+34%+23%-12%+44%-27%+49%* +19%*

% per annum.

profit fell steadily until 1980, when the Reagan-Bush attack on labor ac-celerated the growth of the rate of surplus value and reversed the postwartrend of the rate of profit (although it remains much lower than at thebeginning of the period). Finally, the ratio of unproductive to productivelabor Lu/L p rose dramatically, as is evident in Figure 5.11. The result-ing relative absorption of surplus value by unproductive expenses in turnhelps explain two facts: Both the NIPA-based average rate of profit andthe observed corporate rate of profit declined more rapidly than the Marx-ian one; and the conventional measure of productivity rises much moreslowly than the Marxian one, which is an important clue to the so-calledproductivity growth slowdown of these years.

All these results confirm our basic premise that the theoretical differencebetween Marxian and orthodox economic analysis is reflected in a funda-mentally different empirical picture of capitalist reality.

A critical analysis of previousempirical studies

The classical and Marxian traditions share the distinction between produc-tion and nonproduction labor. But Marx was particularly concerned withthat portion of production labor which is productive of capital, since onlythis labor creates surplus value. The rest of labor is unproductive of capi-tal, even though it may be wage labor (in distribution and state activities)or production labor (productive of value or of use value). Marx himselfdoes not imply that productive labor is in any way superior to, or morenecessary than, unproductive labor. But as we pointed out in Chapter 2,not all Marxists proceed in the same way. Most notably, Baran (1957, p. 32)redefines productive labor as labor that would be necessary under a "ratio-nally ordered" (socialist) society. Marx's definition of productive labor isthereby replaced with a definition based on necessity,1 and the concept ofsurplus value is replaced with the concept of "surplus" - defined as theexcess of the total product over essential personal and public consumption.

This chapter will analyze the various attempts to measure Marxian cat-egories. In order to make the account manageable, we restrict ourselvesto studies published in English, and to estimates of the rate of surplusvalue. Sharpe (1982a) covers some of the literature available in French, buta comprehensive worldwide survey remains to be done. The Japanese arepioneers in this regard. Izumi's brief survey of Japanese estimates makesit clear that many of the issues taken up in the English language literaturewere first, and often better, addressed in the sophisticated Japanese dis-cussion. Matsuzaki makes company-level estimates of the rate of surplus

1 It is no coincidence that Baran turns to a criterion of necessity. Neoclassical eco-nomics is also based on a criterion of necessity. In their case, the benchmarkis a "perfectly competitive market," which perfectly reflects social preferences.Baran retains the necessity criterion, but inverts the benchmark by making a"rationally ordered [socialist] society" the point of reference.

152

Critical analysis of previous empirical studies 153

value as early as 1924, Terashima makes industry-level ones by 1935, ShahRiff develops aggregate estimates by 1940, and Okishio pioneers the useof input-output tables to make labor value estimates by 1959. All in all,Izumi lists 56 sets of estimates of the rate of surplus value in Japan from1924 to 1980 (Izumi n.d.). In our own survey, we will analyze studies byOkishio (1959), Izumi (1980,1983), and Okishio and Nakatani (1985), be-cause these four have been translated into (or published in) English.

The studies we cover will be grouped according to the manner in whichthey treat the distinction between production and nonproduction activ-ities. There are three basic categories of studies: those which implicitlyor explicitly reject the distinction between productive and unproductivelabor, so that they end up treating Marxian categories as equivalent toNIPA categories; those which do base themselves on Marx's distinctionbetween productive and unproductive labor, but differ in the way theyimplement this distinction; and those which substitute some sort of dis-tinction between necessary and unnecessary activities for the distinctionbetween production and nonproduction, thereby substituting some con-cept such as Baran and Sweezy's notion of "surplus" (the excess of totalproduct over necessary social use) for Marx's concept of "capitalist sur-plus product" (the excess of total capitalist product over the consumptionof the productive workers). Within each category, we will also distinguishbetween sectoral and aggregate studies, because systematic transfers ofvalue make the former less reliable than the latter.2 Aggregate studies willalso be distinguished according to whether or not they make labor valueestimates of Marxian categories.

The distinction between money and labor value measures gives rise toa further consideration. We have seen that the distinction between pro-ductive and unproductive labor implies that the money form of surplusvalue will generally differ in magnitude from aggregate profit, even if(final selling) prices were proportional to values. On the other hand, evenif all labor were productive labor, the deviations of prices from valuescould make the money measure of surplus value differ from the labor valuemeasure.3 Of these two theoretically distinct issues, the second is far better

2 If we abstract from transfers of value between nations, or between capitalist andnoncapitalist sectors, then the total surplus value realized in the production sec-tor as a whole will always be less than that produced in it, because of the portiontransferred to the trade sector. Price-value deviations may cause further inter-sectoral and international transfers, which can in principle reverse the outflowfrom production. See Sections 3.1.2 and 3.4.2.

3 Strictly speaking, the comparison is between the money form of surplus valueat prices that are not proportional to values (such as market prices and pricesof production), and the money form of surplus value at prices proportional tovalues (which we call "direct prices").


Labor

All Labor is Productive Some Labor is Productive

Productive = Productive = NecessaryProductive-of -Capital (Baran/Sweezy:"Surplus"Approach)

(Marx)

Sectoral Aggregate

Figure 6.1. Theoretical bases for the type of empirical estimates.

known. But empirical studies typically encompass both issues. For in-stance, the early studies by Wolff (1975, 1977a) estimate both the laborvalue magnitudes and their money forms on the assumption that all wagelabor is productive. This is tantamount to assuming that the money formsof Marxian categories are the equivalent to IO-NIPA categories, because -as we have seen in Section 3.1.1 - the mapping between the two is one-to-one when all labor is treated as productive. On the other hand, laterstudies by Wolff (1977b, 1979, 1987) and Khanjian (1989) do distinguishbetween Marxian and IO-NIPA categories, since they incorporate thedistinction between productive and unproductive labor in their estima-tion of value categories and their money forms.

The impact of price-value deviations on the relation between the moneyand value measures of the rate of surplus value has already been analyzed(in Section 5.10) and shown to be an entirely secondary consideration.Accordingly, in this chapter we will group the studies under review ac-cording to the manner in which they treat the distinction between pro-ductive and unproductive labor. Thus Wolff's earlier studies are placed inthe category of those that fail to distinguish between Marxian and NIPAcategories, while his later studies and the one by Khanjian fall into thecategory of those that do make such a distinction. The issue of price-value deviations will then be addressed as it crops up. Figure 6.1 providesa graphical summary of our schema of categorization.

6.1 Studies that fail to distinguish between Marxian andNIPA categoriesThere exists an entire class of empirical studies that make no real

distinction between NIPA categories and Marxian ones. Studies of thistype generally assume that the rate of surplus value can be approximated


3.00

2 .40 -

1.80 -

1.20 -

0.00'l988'

Figure 6.2. Rate of surplus value S*/V* and profit/wage ratio PVEC.Source: Table 5.7.

by some measure of the profit/wage ratio, so that the levels and move-ments of the former are deduced from those of the latter (except perhapsfor any disturbing influence of price-value deviations). Yet, as we haveseen, such an association is utterly mistaken, both theoretically and em-pirically (cf. Section 3.6.1 and Table 3.12; Section 5.4). Figure 6.2, whichreproduces Figure 5.13, makes it particularly clear that the profit/wageratio (defined here as the ratio of NNP minus employee compensationover employee compensation) is neither an index of the level nor the trendof the rate of surplus value.

6.1.1 Aggregate money value estimatesGlyn and Sutcliffe's (1972) study is one of the earliest, and most

influential, of this type. The authors argue (p. 54) that the secular post-war decline in the British rate of profit lies at the heart of the stagnationof capital accumulation in Britain. And since the capital/output ratio isroughly stable, the decline in the profit rate can in turn be attributed to asecular fall in the profit share.4 But a fall in the profit share is "an increase

4 The rate of profit r = P/K, where P = aggregate profit and K = aggregate capitaladvanced. The rate of profit can also be expressed as r = (P/Y)/(K/Y), whereY = aggregate value added, P/Y = the profit share, and K/Y = the capital out-put ratio.


80%

70

60

50

40

Japan

1952 54 56 58 60 62 64 66 68 70

Figure 6.3. Wage shares in advanced capitalist countries, 1950-70.Source: A. Glyn and R. Sutcliffe, British Capitalism, Workers andthe Profit Squeeze, Harmondsworth: Penguin (1972, p. 76, fig. 7).Reproduced by permission of Penguin Books Ltd.

in labour's share [which is] very roughly the equivalent of a decrease inthe rate of exploitation." This means that real wages must have risen fasterthan labor productivity over extended periods of time. Thus the seculardecline in the British rate of profit is ultimately attributed to the fact that"the position of labour as a whole has been improving relative to that ofcapital" (p. 45). Notice that at the heart of the whole argument is the im-portant association of the rate of exploitation with a NIPA-type measureof the profit/wage ratio.

Glyn and SutclifFe's primary focus is on Britain, but they also attemptto extend their "labor-squeeze" argument to several other advanced capi-talist countries (1972, pp. 73-5). They present data (reproduced in Fig-ure 6.3) on wage shares from 1950 to 1970 for the United Kingdom, theUnited States, Netherlands, Germany, France, Italy, and Japan.

Given the trends evident in the data, and given the misidentification ofthe wage share in GNP with the variable capital share in Marxian valueadded, it is not surprising that the "labor-squeeze" approach gained popu-larity among Marxists. We will confine our discussion to those who explic-itly connect their analysis to Marxian categories. For instance, Boddy andCrotty (1975) transform Glyn and SutclifFe's secular argument into a cyclical


one and apply it to the United States. Basing themselves on chapters ofMarx's Capital (vol. I), in which all labor is still treated as production la-bor, they treat the profit share as an index of the rate of exploitation. Cycli-cal fluctuations in the rate of profit are then explained by fluctuations inthe profit share, and hence in the rate of exploitation (Boddy and Crotty1975, p. 2).5 Sherman (1986) makes the same association when he states thatin "terms of national income accounting, the rate of exploitation is roughlyprofit/wages" (p. 198). But he takes a more agnostic approach to the deter-minants of the cyclical fluctuations in the rate of profit, allowing for both"Marxist supply-side" (labor-squeeze) and demand-side (consumption-demand) effects of cyclical variations in the rate of exploitation (p. 192).

Weisskopf (1979) concerns himself with both the cyclical and secularbehavior of the rate of profit in the United States since World War II. Heexplicitly identifies "variable capital with the total wage bill [and] surplusvalue with the volume of profits,"6 and net output with the NIPA measureof net output (value added). He also implicitly assumes that all labor isproductive, since he defines productivity as real net output per unit of(all) labor (pp. 342-6).7 Not surprisingly, Weisskopf finds that the "longterm decline in the [U.S.] rate of profit from 1949 to 1975 was almostentirely attributable to a rise in the true share of wages, which indicatesa rise in the strength of labour" (p. 370). This argument is further devel-oped by Bowles, Gordon, and Weisskopf (1984), who claim that by thelate 1960s the rising strength of U.S. workers also took the form of areduced work effort which served to slow down the rate of growth of pro-ductivity (pp. 29-32,122-49) and further squeeze profits.

6.1.2 Aggregate labor value estimatesOkishio (1959) is the first to estimate directly the rate of surplus

value in labor value terms. Since he also distinguishes between productive5 It should be noted that although the Marxian measure of productivity differs

markedly from the conventional one in terms of its trend, the (short-run) cyclicalpatterns of the two are quite similar (Section 5.7, Figures 5.19 and 5.20). More-over, cyclical fluctuations in productivity are quite modest compared with thosein real wages, so that cyclical patterns in the wage share of (all) workers may wellmirror corresponding fluctuations in the rate of exploitation. Thus Boddy andCrotty's cyclical results may not be substantially altered when their measure ofproductivity is replaced by a conventional one. But any attempt to link the short-run cycles to longer-term trends would certainly be affected.

6 Weisskopf (1979, p. 343) does acknowledge in a footnote that surplus value"is usually denned to correspond to a substantially larger share of national in-come" than does the NIPA measure of profits, but he ignores this in his data andanalysis.

7 Weisskopf (1979, p. 354) distinguishes between supervisory and nonsupervisorylabor, but only because he believes the two types of employment exhibit differentcyclical patterns.


Table 6.1. Wolff's estimates of the money and value rates ofsurplus value in Puerto Rico

1948 1963 Change

S/V (value rate) 0.9729 0.9328 - 4 . 1 %SVV* = P/W (money rate) 0.5907 0.7529 +28.5%

(S*/V*)/(S/V) 61% 81%

Source: Wolff (1975, p. 940).

and unproductive labor, we will treat his pathbreaking contribution inSection 6.2.3.

Wolff develops labor value estimates by applying the theoretical frame-work developed by Morishima (1973) to actual input-output tables forPuerto Rico (Wolff 1975, 1977a) and for the United States (Wolff 1979,1986). This allows him to directly address the question of price-valuedeviations by comparing his estimates of the money rates of surplus valueto the corresponding value rate. In these particular studies, Wolff doesnot distinguish between productive and unproductive labor.

In his study of Puerto Rico, Wolff explicitly identifies the profit/wageratio as the equivalent of the money form of the rate of surplus value.However, he arrives at the striking result that (at least for Puerto Rico)the problem of price-value deviations has so great an impact that themoney form of the rate of surplus value (the profit/wage ratio in his cal-culations) is a "poor proxy" for either the level or the trend of the true(labor value) rate of surplus value (Wolff 1975, p. 940). Wolff's data indi-cate that the money rate of surplus value is only 60%-80% of the valuerate. Moreover, the money rate displays a significant rise even as the valuerate is actually falling. Table 6.1 reproduces Wolff's estimates for PuertoRico.

There are two separate issues involved here. First of all, there is the largediscrepancy between the money and value measures of the rate of surplusvalue. This problem apparently arises from the fact that Wolff treats rela-tive wages as indexes of skills (Shaikh 1978b, p. 13). Wolff points out thatthe discrepancy between his money and labor value measures of the rateof surplus value depend primarily on the ratio of the direct price (price pro-portional to labor value) of consumption goods to their market price.8 The

8 Wolff normalizes the sum of direct prices (prices proportional to labor values)TV = C + V + S to the sum of market prices TV* = C* + V* + S*. He finds thatthe market price of constant capital was fairly close to its direct price. Thus


lower this ratio in the workers' consumption goods sector, the lower willbe his profit/wage ratio P/W relative to his value rate S/V. Wolff notesthat his empirical estimates of this ratio are mostly less than I.9 And hereit seems very likely that Wolff's procedure leads to biased estimates ofthis value/price ratio. Estimates of labor values require data on input-output flows and also on labor flows. Ideally, these labor flows should beadjusted for skill differences; only if the differences among sectoral wagerates are due largely to skill differences may one then plausibly substituterelative wage coefficients for labor coefficients. Wolff uses wage coeffi-cients because he is unable to obtain data on labor coefficients (Wolff1977a, p. 148, n. 9). But for Puerto Rico, the substitution of wage coeffi-cients for skill-adjusted labor coefficients is highly suspect. It is probablethat in Puerto Rico (as in most Third World countries) poor people spendmost of their income on agricultural products and other staples, and thatthe workers in the sectors that supply these goods are relatively underpaid(relative to their skill level). Agricultural workers in Puerto Rico are par-ticularly underpaid, averaging between 40% and 60% of the wage of otherlaborers (Reynolds and Gregory 1965, p. 65, table 2-8). This means that,in a country like Puerto Rico, the substitution of wage coefficients forskill coefficients is likely to seriously underestimate the labor value ofworkers' consumption goods, thus giving rise to a large discrepancy be-tween the profit/wage ratio and the estimated rate of surplus value. A20%-30% differential between skill-adjusted wage rates in the two typesof sectors would easily account for Wolff's results. Furthermore, to theextent that wages in the consumption-goods sector catch up to the averagewage, the gap between the estimated rate of surplus value and the profit/wage ratio would narrow. In itself, such a rise in relative wages wouldraise the estimate of the labor value of variable capital and hence reducethe growth rate of the value rate of surplus value, all other things beingequal. Thus the bias introduced by wage coefficients would also explainthe apparent fall in Wolff's estimates of the value rate of surplus value inTable 6.1.

The preceding factors appear to explain why Wolff's estimated rates ofsurplus value are so much higher than his profit/wage ratios, why this

V* + S * « V + S, which implies that (1 + S*/V*) = (1 + S/V) • (V/V*), whereS/V = S/V since direct price magnitudes are proportional to labor values. There-fore Wolff's money rate of surplus value differs from his value rate by the ratioof the direct price of workers' consumption V to its market price V*. But thislatter ratio is simply an index of the price-value deviation for consumption goods(Wolff 1977a, pp. 144-5).

9 Wolff normalizes the sum of prices to equal the sum of values, "values" beingdenned here as money prices proportional to labor values. Thus the averagevalue/price ratio is 1.


gap appears to narrow over time, and why the estimated value rate ofsurplus value falls over time. His estimate of the value rate of surplusvalue is biased upward relative to the level of the profit/wage ratio, butbiased downward relative to its trend (to the extent that the gap narrows).

The second problem arises from the fact that Wolff ignores the distinc-tion between productive and unproductive labor. We have seen that evenwhen prices are proportional to values, so that the correct measure of themoney rate of surplus value is equal to the corresponding value rate, theprofit/wage ratio can be a downward-biased index of both the level andthe trend of this true money rate of surplus value. The same reasoningapplies to Wolff's value rate (which is his labor equivalent of the profit/wage ratio) vis-a-vis the true value rate (computed using only productivelabor). Thus we can say that the level of Wolff's value rate of surplusvalue is lower than the level of the true value rate (owing to the failureto distinguish between productive and unproductive labor), and that hisprofit/wage ratio is doubly lower (since its level is downward biased rela-tive to his own measure of the value rate). The impact on trend biases isnot so clear, because the two factors seem to operate in opposite direc-tions in this particular study. In any case, Wolff's results must be inter-preted in the light of all of these considerations.

The conclusion that Wolff's use of relative wages as indexes of skills isthe principal source of the great discrepancy between his value and moneyestimates is borne out by his subsequent studies on the United States.There, by using labor coefficients directly (Wolff 1979, p. 332, n. 9) with-out any adjustment for skill levels, he implicitly assumes that the workersin each sector in his input-output tables all have roughly the same mixof skills. This is the opposite extreme from his Puerto Rico study. Andhere, the results are also quite different: value and money rates of surplusvalue differ by only 8%-15%, and both display the same general trend(p. 334, table 1). His subsequent article with a different definition of wagesyields essentially similar results, although in this case both measures de-cline (Wolff 1986, p. 94, table 2, cited in Khanjian 1989, p. 119). Finally,Khanjian (1989, table 19) finds that price-value deviations result in varia-tions between value and money rates of surplus value of only 6%-9%.Thus price-value deviations do not seem to pose a significant problem.Of course, all the problems associated with the assumption that all laboris productive still remain.

Wolff's methodology is extended by Sharpe (1982a), and applied toCanada (Sharpe 1982b, pp. 12, 42). Following Mandel's definitions of thebasic variables of Marxian economic analysis, Sharpe develops detailedestimates of these variables in both price and value terms. In his variousestimates of the value rate of surplus value, he generally assumes that all


capitalist wage labor (even in the trade and royalties sectors) is produc-tive. In one set of measures, he even assumes that government admin-istrative labor is productive. Consequently, Sharpe's main estimates ofthe rate of surplus value are much lower than, and probably grow moreslowly than, our equivalent measures.10

6.2 Studies that do distinguish between productive andunproductive laborWe turn now to those studies that attempt to incorporate the dis-

tinction between productive and unproductive labor in their estimates ofMarxian categories.

6.2.1 Sectoral money value estimatesVarga (1928, 1935) provides the earliest set of sectoral estimates

of the rate of surplus value. The methodology he developed remains in-fluential to this day. Basing himself on manufacturing census data, hemeasures variable capital as the wages of production workers, and (themoney form of) surplus value as the excess of net value added over vari-able capital,11 for seven benchmark years from 1899 to 1931. In a laterstudy (Varga 1964) he also attempts to update these figures to cover theperiod 1947-58, but these subsequent estimates contain two major calcu-lation errors: for variable capital he mistakenly uses all wages and sal-aries, rather than the production worker wages he used in earlier years;and for surplus value he mistakenly uses gross value added rather than theexcess of gross value added over wage costs (however defined). Althoughthese two errors have offsetting effects on his data, they render his post-war estimates useless.12 They also invalidate his analysis of the long-term

10 Sharpe also calculates two alternative measures of the rate of surplus value. Aspart of his input-output estimate (Sharpe 1982b), he calculates a "narrowly de-fined" measure of the rate of surplus value which is based on the assumption thatsurplus value is the same thing as property-type income. This gives an estimateof 29% in 1976, as compared to 109.1% for his main measure and to 188% forCuneo's estimate of the rate of surplus value in Canadian manufacturing. In anunpublished paper, Sharpe (1982a, pp. 41-5) calculates a NIPA-based constant-dollar estimate which is similar in form to the main estimates of his input-outputstudy. This has a similar trend to his labor value estimates, but an even lowerlevel.

11 Varga actually calculates surplus value as the difference between the money valueof the total product and the sum of materials, depreciation, and wage costs ofproduction. But the difference between the first item and the sum of the next twois simply value added, so his measure of surplus value is net value added minusproduction wages.

12 For instance, the census figures for manufacturing in 1947 (U.S. Bureau of theCensus 1975, series P6-10, p. 666) list gross value added GVA = 74,291, production


trend of the rate of exploitation in the United States. However, as we shallsee, Mandel and Perlo provide the correct figures for the postwar period.

Despite the surprising calculation errors in his later data, Varga's basicapproach is very advanced. He not only distinguishes between productionand nonproduction workers in manufacturing, but is also careful to notethat his estimate of the rate of surplus value "is lower than the actual"rate because it fails to account for surplus value transferred from manu-facturing to the trade sector. It is only the lack of adequate data whichprevents him from correcting for this effect (Varga 1964, p. 107).

Varga's methodology was adopted by Corey (1934) and Varley (1938),with very similar results (Sharpe 1982a, p. 30). Gillman (1958, pp. 33, 39)takes up the same approach for his primary measures, defining variablecapital in manufacturing by the wages of production workers and sur-plus value as the rest of value added (he measures surplus value bothgross and net of depreciation). Gillman provides three sets of estimatesof the rate of surplus value extending from 1849 to 1952, although nosingle set covers the whole period owing to a lack of consistent depreci-ation estimates for the entire interval.13 He also looks at the various com-ponents of surplus value, such as unproductive expenses and "property-type" income. This aspect of his work is discussed separately in whatfollows.

Mandel (1975, pp. 174-5) further develops the Varga method. In histheoretical discussion, Mandel makes several important points. He beginsby noting the difference in structure between Marxian economic categoriesand conventional ones. The salaries "of managers, higher employees inindustry and the state apparatus" belong in the measure of surplus value(p. 165), as do the taxes paid by capitalist firms (p. 176), while that por-tion of the business and personal revenue which is the result of the recir-culation of primary sector flows is excluded from the measure of thesocial product because it represents "revenue which has been spent two

worker wages Wp = 30,244, and total wages and salaries W = 39,696, all in mil-lions of current dollars. In keeping with his earlier methodology, Varga shouldhave calculated the gross rate of surplus value as (GVA-WP)/WP = 146%. In-stead, the figure he shows is GVA/W = 187% (Varga 1964, p. 108). The estimatesin the other years for which he makes calculations (1950, 1955, and 1958) aresimilarly flawed. By the way, it is interesting to note that Varga cites (but doesnot explain) a "first calculation" by Katz of S/V = 209% for 1958, which is veryclose to our own estimate of 200%.

13 Gillman (1958) estimates the gross rate of realized surplus value in manufactur-ing from 1849 to 1938 (p. 37), the net rate based on book-value depreciation from1919 to 1939 (pp. 40, 46, apx. 2), and a more precise net rate based on current-dollar reproduction costs of fixed capital for various benchmark years from 1880to 1952 (pp. 47-9).


or three times over" (pp. 165,176, n. 66). These same points figure promi-nently in our own development of the argument. He also excludes "taxespaid by workers - as distinct from deductions for social security" fromvariable capital (pp. 176-7). This too would accord with our approach ifthese taxes are interpreted as net of the corresponding social expenditureson labor (see Section 3.3). But Mandel also argues that the costs of circu-lation belong "neither to the variable capital paid out each year nor to theannual quantities of surplus-value" (p. 165), and that "services in the realsense of the word - i.e., all except those producing commodity trans-portation, gas, electricity and water - do not produce commodities, andhence do not create any new value" (p. 176). These last two propositionsare diametrically opposed to our own approach. Finally, even thoughMandel is careful to state that the "application of Marx's categories to[conventional statistics] must . . . be handled with extreme caution," henonetheless suggests that "a comparison between the official calculationsof the share of the sum of wages and salaries and the share of the mass ofprofit in the national product certainly provides a reliable indication ofthe medium-term development of the rate of surplus value, for the neces-sary correction of these aggregates to align themselves with Marxist cate-gories is unlikely to alter in any decisive way the proportions betweenthem in these periods of time" (p. 166). Sharpe (1982a, p. 5) cites this asevidence that even so knowledgeable a writer as Mandel falls into theerror of confusing orthodox categories with Marxian ones. But the matteris not so clear-cut. On one hand, in his empirical work Mandel uses theterm "wages and salaries" to mean production worker wages and salaries(a convention that originates in use of the term "wages" to mean "pro-duction worker wages" in the Census of Manufactures), and measures"profits" as the excess of value added14 over production worker wagesand salaries. Indeed, Mandel's own empirical methodology is an exten-sion of that in Varga (1928, 1935) and Gillman (1958), in which the dis-tinction between productive and unproductive labor plays a vital role.On the other hand, Mandel also uses (without any methodological objec-tion) the estimates from Vance (1970), which make no particular distinc-tion between productive and unproductive labor.15 In later texts, though,

14 Since Mandel's empirical estimates focus on manufacturing, the relevant valueadded is that of this sector. But in his theoretical discussion, the relevant valueadded would be that of the primary sectors, since he has already excluded thesecondary sectors as recirculated primary flows.

15 Mandel (1975, p. 164) lists estimates by Vance in which the new value added(variable capital plus surplus value) is'simply NNP (U.S. Bureau of the Census1975, series F146). However, the variable capital is larger than even the sum ofall private wages and salaries and supplements to income (series F166 and F170).


the importance of this distinction is given great prominence (Mandel 1981,pp. 38-61).

MandeFs own contribution to the empirical discussion is to experimentwith the impact of a broader definition of variable capital on Varga'smethodology. He defines manufacturing variable capital in two ways (pro-duction worker wages and the former plus 50% of the salaries of nonpro-duction workers), and finds that the broader measure results in a slowerbut still rising rate of surplus value.16

Perlo (1974) further broadens the range of measures of variable capital,defining it as production worker wages in one case and as all wages andsalaries in the other.17 He places the general trend of the gross realizedrate of surplus value somewhere in between, probably closer to the first.He also notes that any measure of the realized rate of surplus value in aproduction sector will understate the level of the true rate because somevalue is always transferred to the trading sectors (pp. 27-8). Finally, Perloargues that "monopoly pricing and promonopoly taxation" increasinglybenefit capitalists at the expense of workers, so that the realized rate ofsurplus value probably understates the trend of the true rate. To correctfor this bias in the realized rate, he proposes to "calculate the trend in theexploitation of labor by comparing the physical volume of the worker'sproduction with the volume of his consuming power, after allowing forchanging retailing prices and tax deductions from his pay" (pp. 29-30).In practice, this means estimating the trend in the true rate of surplusvalue from the ratio of real take-home pay to labor productivity (p. 30).His "index of worker's share" is therefore much the same as what Agliettalater calls the "real social wage cost."18 The principal difference betweenthe two is that Aglietta apparently uses pre-tax real wages, whereas Perlouses post-tax real wages. We may think of these as implicitly representingtwo alternate positions on the net tax (social wage) paid by workers: if onebelieves that workers' taxes return to them in the form of social welfare

16 Mandel provides estimates of the realized rate of surplus value in manufacturinggross and net of depreciation, and with and without 50% of salaries. This giveshim four alternate measures: gross and net measures with variable capital definedas production worker wages; and gross and net measures with 50% of salariesincluded in variable capital. The first two grow by roughly 50% over the postwarperiod, while the latter two grow more slowly (25% for the gross rate and 35%for the net rate). Mandel feels that these latter measures "probably correspondmore closely to the actual development" (1975, pp. 174-5).

17 Perlo (1974, pp. 26-7) notes that one should estimate surplus value net of depre-ciation, but his empirical estimates are confined to gross surplus value.

18 The numerator of both measures is (pre- or post-tax) hourly wages deflated bythe consumer price index, and the denominator of both is hourly productivity(Perlo 1974, p. 30; Aglietta 1979, pp. 88-91).


expenditures, then the net tax is essentially small and Aglietta's measureis more accurate; on the other hand, if one believes that workers' taxesare used to subsidize the capitalist class and related state activities, thenthe net tax is essentially equal to taxes paid, and Perlo's measure is moreappropriate. It is interesting to note that, for the United States, our esti-mates of the social wage indicate that Aglietta's assumption is closer tothe mark.19

Cuneo (1978,1982) applies Varga's methodology to the manufacturingindustry in Canada from 1917 to 1978. He provides twelve measures inall, of which three are relevant here: RSV^ which is just a Varga-typemeasure of the gross rate of surplus value for Canadian manufacturing;RSV3, which is the constant-dollar gross rate of surplus value, derivedby deflating value added by the Wholesale Price Index and productionworker wages by the Consumer Price Index; and RSV12, which is theconstant-dollar net rate of surplus value derived by subtracting an esti-mate of depreciation from gross surplus value (Cuneo 1978, p. 290; 1982,pp. 399,415). He finds that over the postwar period these rates of surplusvalue rise until the mid-1960s, and then fall afterward (1978, pp. 292-3;1982, p. 399). Cuneo also provides nine other variants of these rates, butthey are all linked to a rather flawed "adjustment" he makes to the basicmeasure RSVls for which he was severely criticized by Van Den Berg andSmith (1982) and Emerson and Rowe (1982).20

Amsden (1981) applies Varga's methodology to the world economy byestimating realized rates of gross surplus value in manufacturing for alarge set of countries21 for the period 1966-77. Her actual estimates forU.S. manufacturing are the same as in Mandel, Perlo, and Shaikh. She iscareful to note that price-value deviations and intersectoral and inter-national transfers of value may make realized sectoral rates of surplusvalue differ from the true rates in a way that "may vary unsystemati-cally between developed and underdeveloped countries." Nonetheless, she

19 Shaikh and Tonak (1987, p. 188) find that the net tax stays within ±5°7o of em-ployee compensation for most of the postwar period in the United States.

20 For RSV2, Cuneo deflates the production worker wage bill by the consumer priceindex, but does not deflate value added or surplus value. This is clearly inconsis-tent. For RSV4-RSVn, he reduces the production worker wage bill in year / bythe ratio of productive employment in 1949 to that in year t. This adjusted mea-sure of variable capital is simply the current wage rate of production workersmultiplied by their employment level in 1949. His measures RSV4-RSVn are var-ious gross, net, and constant-dollar versions of the rate of surplus value basedon this adjusted measure of production worker employment. The rationale forthis is quite obscure (Cuneo 1978, pp. 288, 290; 1982, pp. 397-8, 415).

21 Amsden (1981, p. 232) notes that "statistics are typically restricted to manufac-turing firms above a minimum size," which varies from country to country.


finds that in general the less advanced regions of the capitalist world havemuch higher rates of (realized) surplus value, largely because the wagegap is so much greater than the corresponding productivity gap (Amsden1981, pp. 230-3).22

Lastly, Shaikh provides a long series on the gross-profit/wage ratio inU.S. manufacturing from 1899 to 1984, a la Varga, as part of his analysisof long waves. He finds that this rate is essentially constant in the pre-Depression period 1899-1929, but rises steadily in the post-WWII period1947-84. This differential pattern accounts for a somewhat slower fall inthe manufacturing rate of profit in the postwar period (Shaikh 1992a).

Almost all of these studies measure the rate of surplus value as the dif-ference between variable capital (defined as the sum of production workerwages and possibly some portion of salaries) and value added. So defined,surplus value is inclusive of the materials and wage costs of unproduc-tive activities, of corporate officers' salaries and bonuses, of indirect busi-ness taxes and corporate profit taxes, and of corporate and noncorporateprofits. Clearly, only a portion of surplus value takes the form of profits.We have emphasized this point throughout.

Two further sets of sectoral estimates center around the fact that profitis only one component of surplus value. After presenting his initial set ofestimates, Gillman (1958) goes on to argue that studies of profitability(such as his) should concentrate on that part of surplus value which isin excess of such expenses as the materials and wage costs of unproduc-tive activities.23 He calls this portion of surplus value "'net' surplus value

2 2 Amsden finds that the relationship between rates of surplus value and GNP percapita is actually an inverted-U shape. At very low levels of development bothreal wages and productivity are very low, so the rate of surplus value is relativelylow. At the intermediate levels represented by newly industrializing and semi-industrialized countries, productivity gains race ahead of wage gains, so thatthe rate of surplus value is very high. Then, at the level of developed capitalistcountries, real wage gains begin to catch up to productivity gains, so that the rateof surplus value is the lowest. Amsden (1981, pp. 237-9) notes that this cross-sectional pattern need not contradict Marx's notion that the average rate of sur-plus value rises as capitalism develops. But her findings are contradicted by Izumi(1983), who studies the labor value rate of surplus value instead of the realizedmoney rate (as in Amsden). Izumi explains the difference in results by arguingthat the transfers of value embodied in realized rates of surplus value make suchrates unreliable indicators of the value rate of surplus value. See the discussionof Izumi at the end of Section 6.2.3.

2 3 Gillman finds that the general Marxian rate of profit, the ratio of surplus valueto capital advanced, is roughly constant from 1920 to 1952. But in terms of theportion of surplus value which constitutes property-type income to the capitalistclass, the rate of profit declines somewhat (Gillman 1958, p. 97). Of course, thisis not because of a rising organic composition but rather because of a rising shareof unproductive expenses and taxes. In contrast to this, Shaikh (1992b) finds a


realized," and compares its growth to that of variable capital (pp. 89-91).Whereas surplus value as a whole rises relative to variable capital (i.e.,the rate of surplus value rises), the "net" portion declines relative to vari-able capital because of relatively rising expenses (p. 97). At a later stage,Gillman also excludes indirect business taxes to arrive at the portion ofsurplus value that represents "property-income" (profits, rents, and in-terest),24 which further accelerates the fall in the rate of profit (pp. 101-2).

Gillman's focus on property-type income is perfectly appropriate aslong as it is clear that this represents only a portion of total surplus value(which means that its general patterns cannot be analyzed without refer-ence to the whole). And Gillman himself is generally clear about this,despite occasionally confusing terminology such as the term "net rate ofsurplus value" for what is really a fraction of the rate of surplus value.Unfortunately, such clarity is lacking in the study by the Labor ResearchAssociation (1948). In various places in their discussion, they correctlycharacterize indirect business taxes as "part of surplus value" (p. 22); wagesin trade, finance, insurance, real estate, government, and various unpro-ductive services as the share of surplus value going to unproductive workers(who "do not produce surplus value, but only share in that producedelsewhere"; p. 28); and property-type income as "[s]urplus value goingto members of the capitalist class" (p. 27). Yet, despite their essentiallycorrect definition of total surplus value, they often refer to the ratio ofproperty-type income to variable capital as "the rate of surplus value."For instance, in their estimate of the "national rate of surplus value"(p. 28), they exclude both indirect business taxes and unproductive wagesfrom the "surplus value" part of this ratio.25 They repeat this exercisewhen they turn to the manufacturing sector, further restricting themselvesto that part of "surplus value that remains in the industry" (p. 51). Thismeans that they now exclude not only indirect business taxes and unpro-ductive wages, but also rents and interest costs (since these are paid out

sharply rising organic composition, and hence a falling general rate of profit,using the same manufacturing flow data but new data for capital stock and ca-pacity utilization.

2 4 Marx focused on the general rate of profit, defined as the ratio of surplus valueto capital advanced, because he felt that the general dynamics of profitabilityoriginated at this level. Such a focus requires one to derive more concrete mea-sures of the rate of profit, such as the ratio of property-type income to capitaladvanced, in order to locate them in the context of more general trends.

2 5 They begin from national income, which is value added minus indirect businesstaxes, so that the latter is excluded from the start. Then they divide national in-come into property-type income, wages of workers in productive sectors, andwages of workers in unproductive sectors. The "national rate of surplus value" isdefined as the ratio of the first two elements (Labor Research Association 1948,pp. 27-8).


Table 6.2. Sectoral (manufacturing) estimates of the rate ofsurplus value, 1899-1984

Sources 1899 1900 1901 1902 1903 1904 1905 1906

Shaikh 1.46 1.46 1.46 1.46 1.46 1.47 1.48 1.50Varga 1.28 1.24Gillman 1.44 1.47Mandel 1.46

Sources 1917 1918 1919 1920 1921 1922 1923 1924

ShaikhVargaGillmanMandel

Sources

ShaikhGillmanMandelPerlo

Sources

ShaikhMandelPerlo

Source

Shaikh

1.47

1935

1.541.541.53

1953

1.48

1.48

1971

2.37

1.47

1936

1.51

1954

1.621.51

1972

2.36

1.471.221.471.46

1937

1.491.49

1955

1.74

1973

2.43

1.39

1938

1.60

1956

1.78

1974

2.62

1.321.061.32

1939

1.721.721.82

1957

1.81

1.81

1975

2.64

1.37

1940

1.69

1958

1.851.85

1976

2.72

1.421.181.421.42

1941

1.65

1959

1.95

1977

2.72

1.49

1942

1.62

1960

1.95

1.95

1978

2.73

Sources: Shaikh (1992a); Varga (1935; Sharpe 1982a, p. 29); Gillman (1957;Sharpe 1982a, p. 31); Mandel (1975; Sharpe 1982, p. 34); Perlo (1974).

to other sectors) (pp. 47-51). Although they correctly measure the grossrate of surplus value in manufacturing, inclusive of indirect business taxesand unproductive wages (a la Varga),26 they promptly reduce the measureof gross surplus value by an estimate of "overhead costs" defined as thesum of depreciation, indirect business taxes, rents, interest payments,

26 Their only departure from Varga comes in their estimate of net surplus value,which they derive by subtracting an estimate of overhead costs from gross sur-plus value. But this overhead-cost component includes not just depreciation butalso "interest, repairs, rent, and taxes" (Labor Research Association 1948, p. 55),so that their measure of net surplus value is considerably understated.


1907

1.51

1925

1.571.281.57

1943

1.58

1961

1908

1.53

1926

1.59

1944

1.55

1962

1909

1.551.301.55

1927

1.611.331.61

1945

1.52

1963

1910

1.53

1928

1.70

1946

1.49

1964

1911

1.52

1929

1.811.581.811.80

1947

1.46

1.461.46

1965

1912

1.51

1930

1.80

1948

1.47

1966

1913

1.49

1931

1.781.471.78

1949

1.49

1967

1914

1.481.241.481.49

1932

1.81

1950

1.59

1.59

1968

1915

1.48

1933

1.84

1.84

1951

1.51

1969

1916

1.48

1934

1.68

1952

1.49

1970

2.00 2.03 2.09 2.13 2.18 2.21 2.22 2.26 2.26 2.282.09 2.192.07 2.21 2.26

1979 1980 1981 1982 1983 1984

2.88 2.91 2.95 3.02 3.16 3.24

and all other expenses (pp. 50-1), so as to get back to the portion of sur-plus value retained in the sector as property-type income.27 In this way,they reduce the rate of surplus value to a variant of the profit/wage ratio.

This completes our survey of the main sectoral estimates of the rate ofsurplus value in the United States. Table 6.2 lists these estimates, and

27 Their treatment of variable capital is also confusing. In their estimate of thenational rate of surplus value (Labor Research Association 1948, p. 27), theydefine variable capital as the wages "paid to those workers in the 'productive'industries" (emphasis added). Yet in their estimate of the manufacturing sector,they use the category of "wages" as their measure (p. 54), apparently unaware


0.751899 1905 1911 1917 1923 1929 1935 1941 1947 1953 1959 1965 1971 1977 1983

Figure 6.4. Estimates of the rate of surplus value: Manufacturing.Source: Table 6.2.

Figure 6.4 graphs the main ones. The preceding studies have two salientcharacteristics. First of all, like all sectoral estimates they can only pickup that portion of aggregate surplus value realized in a particular sector(generally manufacturing). At best, this would represent only the realizedrate of surplus value, net of any value transferred into or out of it to othersectors. This is why so many authors, from Varga onward, are careful topoint out that their sectoral estimates are underrepresentative of the truerate of surplus value. To the extent that these transfers have a trend overtime, the resulting estimates will have secular bias.

An entirely separate problem arises from the fact that census data areconstructed quite differently from NIPA data. Table 6.3 illustrates theproblem for the year 1970 by comparing census and NIPA figures for grossvalue added and total employee compensation in manufacturing. The cen-sus figures for gross value added are typically larger than the correspond-ing NIPA figures (by 19% for 1970). At the same time, census figures foremployee compensation and production worker wages are typically smallerthan NIPA-based figures (roughly 20% smaller in 1970). Both these fac-tors serve to make census-based estimates of the sectoral rate of surplus

that this represents only the wages of production workers, not all workers, in thissector (nonproduction workers show up under the category of "payroll").


Table 6.3. Manufacturing sector, 1970 (billions of currentdollars)

GVA

Employeecompensa-tion (EC)

Productionworkerwages (Wp)

Gross rateofSV

(1) Census 300.3 141.9 91.6 228%(2)NIPA, BLS 252.3 181.F 110.3* 129%(3) Census/NIPA 1.19 0.78 0.83 1.77

°NIPA.Sources: Row (1): U.S. Bureau of the Census (1975), series P10 (GVA), P7 (EC),and P9 (Wp). Row (2): Table E.I (GVA), Table G.I (EC), and Table G.2 (V* =Wp).

value much higher than NIPA-based sectoral estimates. The discrepancybetween the two data sources is well known, and still unresolved.

The sectoral effect and the data-source effect seem to work in oppositedirections. Within a common data set, sectoral and aggregate estimatesof the rate of surplus value will generally differ, because the former failsto account for value transfers in and out of the sector: value will alwaysbe transferred out of the producing sector to the trading sector owing tothe difference between producer and purchaser prices, and value may betransferred into or out of the producing sector due to producer price-value deviations induced by the (tendential) equalization of profit rates.To the extent that the latter effect tends to be small, the former will dom-inate, and sectoral rates of surplus value will tend to be lower than aggre-gate ones. Comparing NIPA-based aggregate and sectoral rates of surplusvalue in Figure 6.5 shows this to be the case, although the trends of thetwo rates are similar. The lower curve in Figure 6.6 makes these notionsmore precise, by showing that the ratio of the NIPA sectoral to the aggre-gate rate is roughly 55% and seldom varies by more than ±5%.

The data-source effect works in the opposite direction, because censusmeasures of value added in manufacturing are systematically larger thanNIPA ones, as is evident in Figure 6.5.

The net result of these two effects is that census-based sectoral esti-mates, such as those in Varga and in others who adopt his methodology,tend to have a much sharper upward trend than either the sectoral NIPA-based or aggregate NIPA-IO-based estimates of the rate of surplus value.Figure 6.5 shows that the average level of the census-based estimate overthe whole postwar period is roughly equal to that of the average aggregaterate SVV*, but that the trend of former is much sharper than that of the


Manuf. (MPA)

T—i—i—i—i—i—i—i—i—i—i—i—i—i—i—i—i—i—i—i—i—i—i—i—i—i—i—i—i—i—i—i—i—i—i—i i i r1948 1951 1954 1957 1960 1963 1966 1969 1972 1975 1978 1981 1984 1987

Figure 6.5. Aggregate and sectoral realized rates of surplus value.Source: Table 6.2.

latter. Figure 6.6 shows that the ratio of the former to the latter rises by66% over the postwar period, from 0.80 in 1948 to 1.33 in 1984.

6.2.2 Aggregate money value estimatesOne of the earliest discussions of the general correspondence be-

tween Marxian categories and national economic accounts occurs in thepamphlet by the LRA (Labor Research Association 1948). The bulk ofthe empirical estimates in this pamphlet are sectoral, which is why it wasinitially discussed in the previous section. However, it does contain scat-tered remarks indicating that surplus value consists of indirect taxes, wagesof workers in unproductive sectors, and property-type income in all sec-tors, and that variable capital consists of the wages of workers in the pro-ductive sectors (pp. 22, 27-8). This is not exact (among other things, theintermediate inputs of the trading sectors would be left out, the royaltiessectors would be double-counted in Marxian value added, and unproduc-tive labor in the productive sectors would be included in variable capital),but it is a start in the right direction. On the basis of their own remarks,the LRA pamphlet should have estimated variable capital as the wages of(all) workers in the productive sectors, and surplus value as the rest ofNNP. In fact, however, they do not proceed in this way at all. Instead,


1.30 -

1.20 -

1.00 -

0.90

0.70 -

0.60 -

0.50 -h—r

/ \/ V

Census-Based Mfg./Aggregate

NIPA-Based Mfg./Aggregate

h i i i i i i i | | i i i i i i i i i i i i i i i i i \ i i i i j i r1948 1951 1954 1957 1960 1963 1966 1969 1972 1975 1978 1981 1984 1987

Figure 6.6. Ratios of sectoral rates of surplus valuer to the aggregaterate. Source: Table 6.2.

like Gillman in his second set of estimates, they focus their attention onlyon that part of surplus value which takes the form of profit-type income.Gillman muddied the waters by labeling this "net surplus value."28 TheLRA pamphlet compounds the confusion, and contradicts its own earlierusage, by simply calling it "surplus value."29 Its initial potential is thusdissipated by later contradictions and confusions.

A much more consistent treatment appears in Eaton (1966). Eaton'sapproach is generally quite sophisticated. At a theoretical level, he definesMarxian value added as the value added in productive sectors plus thegross trading margin on this output, and defines variable capital as thewages of workers in the productive sectors (p. 211, including footnote).This is essentially the same as our own revenue-side measures shown inTable 6.4 (to follow).30 Eaton also points out that variable capital should

28 Gross and net national product are gross and net of depreciation. Gross surplusvalue is gross of depreciation. It is therefore plausible that net surplus valueshould be net of depreciation.

29 They call the ratio of profit-type income to variable capital "the national rate ofsurplus value" (Labor Research Association 1948, pp. 27-8).

30 Our measure can be written as VA* = (RYP + VAp) + GOt. If Eaton's measure ofproductive value added includes rental and finance charges (royalty payments),then his measure is the same as ours.


Table 6.4. Our basic mapping between Marxian andIO-NIPA categories

VA* = TV* - C* = VApt + RYpt + Mtt

be corrected for the net tax on productive workers, and quotes Callaghanto the effect that the costs of "social services for the workers. . . is broadlymet from within the working class itself" (Eaton 1966, p. 216). Our owndetailed estimates of the net tax lead us to precisely the same conclusion(see Section 5.9). At an empirical level, Eaton restricts the definition ofproductive sectors to those producing goods only, so that all services aretreated as unproductive. In addition, he assumes that productive labor isall labor within productive sectors and that unproductive labor is all laborwithin unproductive sectors. On this basis, he estimates the rate of sur-plus value in the United Kingdom to be 186% in 1937.

Mage (1963) raises the discussion of the relation between Marxian cate-gories and national income accounts to an entirely new level. He is thefirst to really address the issue at a general (as opposed to a sectoral)level, and the first to attempt estimates in both price and labor valuequantities - although he fails at the latter. Mage begins with a systematicand wide-ranging presentation of Marx's theory of value, price, surplusvalue, productive and unproductive labor (in which services are countedas productive), accumulation, effective demand, long-term profitability,and crises (Mage 1963, chaps. I-V). His primary goal in this section is tolocate Marx's argument about the long-term tendencies of the rate of sur-plus value, the organic composition of capital, and the general rate ofprofit. The rest of his work (chaps. VI-VIII) is devoted to deriving em-pirical estimates of basic Marxian categories in order to test the empiricalvalidity of Marx's propositions.

Although Mage's approach to the relation between Marxian and or-thodox categories is quite sophisticated, it suffers from one major defect.Namely, he never provides a systematic treatment of the overall mappingbetween the two sets of categories. Instead, he proceeds by estimatingseparate components of various Marxian categories and then adding themup to arrive at individual desired magnitudes such as variable capital and(his definition of) surplus value. The elements that do not enter his def-initions of these measures tend to disappear from view (which cannot


happen in our own double-entry IO-based methodology). Nonetheless,one can make the necessary connections between his partial approachand our more general one.

Let us begin with a summary of our own mapping between Marxiancategories and those in national income accounts. Leaving aside questionsconcerning the exact coverage of the trade sector (we include building rent-als in the trade sector, whereas Mage implicitly treats all rents as groundrent), we begin from total value as the sum of production and trade sec-tor IO gross outputs (TV* = GOpt a GOp + GOtt). Constant capital is de-fined as the sum of depreciation and materials used in the productivesectors (C* s Mp + Dp). From this we derive Marxian value added as thedifference between total value and constant capital (VA* = TV* —C* =GOpt — MJ,-Dp), which can also be expressed as the sum of NIPA valueadded in the trade and production sectors (VApt = VAp + VAtt), royalties(ground rent and finance charges) in the production and trade sectors(RYpt = RYp + RYtt), and intermediate inputs in the trading sectors (Mtt).Of this amount, we would count the wages of production workers asvariable capital (V* = Wp). Aggregate surplus value is therefore the rest ofvalue added (S* = VA* — V*), and this can also be written as the sum ofindirect taxes (IBTpt), profits (Ppt), and royalties (RYpt) in the produc-tion and trade sectors, plus trade-sector intermediate inputs (Mtt). Table6.4, which is adapted from Table 3.12, summarizes these relations. Notethat the subscript pt refers to the sum of the production and total tradesectors.

Mage proceeds in exactly the opposite direction, building up certaintotals from the individual components. Variable capital is defined in es-sentially the same way as ours, as the "wage received by the productivelaborers" in the production and trade sectors (Mage 1963, pp. 164, 188).However, he restricts the definition of surplus value to only the "total ofproperty incomes in the forms of profit, interest and rent" of the produc-tion and trade sectors (pp. 79,164).31 The lineage of this narrow conceptionof surplus value can be traced back to Gillman and the Labor ResearchAssociation. Gillman treats "property-income" as a portion of surplusvalue, the Labor Research Association treats it as the only relevant por-tion, and Mage treats it as the very definition of surplus value.32 In our

31 Mage correctly restricts himself to flows "originating in the capitalist sector"(1963, p. 164), so as to avoid double counting of revenues. He defines this orig-inal source of revenues to be the sum of the production and trade sectors (seeAppendix K).

32 Mage criticizes Gillman for misrepresenting Marx's treatment of the costs of cir-culation. Since Gillman's treatment appears to be grounded in Marx's own argu-ment, Mage tries to get around this obstacle by arguing that whereas these costsare indeed a deduction from surplus value from "the point of view of the entire


Table 6.5. Comparison between our mapping and Mage's

Shaikh

V!

S'

VA

(SVV*

and Tonak

*-(Pp, + RYp

*-W p + (Ppl-

) = [(Ppt + RY+

' +(WtlP+Mtl)

+ (Wn + Mtt)

CW + M^J/Wp

Mage

V*'

S*'

VA*'

S*'/V*'

-(Pp.+1

^Wp + (]

s (pp ,+)

Dp)+IBTpt + (Wtt + Mtt)

RYpt)

Ppt + RYpt)

RYpl)/Wp

terms, Mage's measure of surplus value corresponds to the profits-and-royalties (Ppt + RYpt) portion of surplus value. This leaves out indirectbusiness taxes (IBTpt) of the production and trade sectors as well as thecost of circulation (Wtt + Mtt), both of which Mage is then forced to placein total constant capital: "the appropriate treatment for the outlay onunproductive expense in general... is to regard them as part of constantcapital" (p. 66). Table 6.5 provides a summary of the comparison be-tween Mage's categories and ours.

Mage's actual empirical estimates are much lower than our theoreticaldiscussion would suggest. Several concrete features of his estimation pro-cedures account for this widened gap. First of all, he excludes agricultureand government enterprises, whereas we include both.33 Second, as notedearlier, he treats the whole of the (nonimputed) rental sector as a royaltiessector, whereas we put a substantial portion of it into total trade. Conse-quently, even our measure of property-type income will be higher thanhis.34 And third, he subtracts estimated taxes on corporate profits and on

capitalist class" (as Marx notes), they are really constant capital from "the stand-point of the process of capitalist production as a whole" (Mage 1963, pp. 61-8).He cites (p. 62) Marx's division of surplus value into profits, rents, and interest,without mentioning that - in the particular discussion cited - Marx is abstractingfrom unproductive capital.

33 Mage excludes government enterprises on the ground that they are noncapital-ist. Since input-output tables merge government enterprises into industries withsimilar activities, we perforce count them as part of those industries.

34 Mage also subtracts the wage equivalent of proprietors and partners (WEQ)from the income'of unincorporated enterprises. But we do the same thing, be-cause our measure of total wages is employee compensation plus the wage equiv-alent of proprietors and partners. So, other than the actual estimate of the size ofWEQ, this cannot account for the difference between our measures and his.


rental receipts. He even subtracts estimates of the "direct taxes imposed onindividual recipients of surplus value" (Mage 1963, p. 166), on the groundsthat surplus value should represent only the "net income of the . . . capi-talists" (p. 36), "i.e., after-tax net property income" (p. 164).35 Althoughhe does not make it clear, presumably he would add all of these taxes toconstant capital, as he did with indirect business taxes.36 Not surprisingly,his measure of surplus value is substantially lower than ours.37

Mage's actual estimate of variable capital is also quite different fromours. The exclusion of agriculture and government enterprises would makehis estimates smaller than ours even if all other things were equal. More-over, he reduces his measure of variable capital by "the estimated portionof it paid as direct taxes by individual recipients of labor income" (1963,p. 167). This at least has the virtue of consistency, since it parallels histreatment of property-type income. But there is still an inconsistency inhis treatment of the unincorporated sector, which further reduces his mea-sure of variable capital: when he calculates the portion of surplus valuewhich corresponds to unincorporated enterprise profits in the productionand trade sectors, he does so by subtracting the estimated wage (the wageequivalent WEQ) of proprietors and partners from the total value addedof unincorporated enterprises. This removes both the productive wageequivalent (corresponding to the productive portion of the labor of pro-prietors and partners) and the unproductive wage equivalent. To be con-sistent, he should have then added the former to variable capital and thelatter to total unproductive wages; but he neglects to do either. We, onthe other hand, do both.38 Consequently, his measure of variable capitalis somewhat lower than ours.39

35 Mandel (1975, p. 176) criticizes Mage for leaving taxes out of his measure of sur-plus value.

36 Mage also subtracts corporate officers' salaries from wages and adds them to hisestimate of aggregate surplus value. In effect, we do the same thing (see AppendixG), so this does not account for any difference between the two sets of measures.

37 Mage's measure of capital consumption is also different from ours, since they arederived from different capital stock data.

38 We start by adding the wage equivalent in each sector to employee compensationin each sector to obtain total wages in each sector. Then one portion of this totalis allocated to variable capital, and the rest to unproductive wages. When theformer is subtracted from Marxian value added (which includes all wages in theproduction and trade sectors) to get surplus value, the remainder automaticallyincludes the unproductive wages of the production and trade sectors, includingcorporate officers' salaries (which NIPA lists under employee compensation).

39 Because estimates of the ratio of productive to unproductive labor (or wages) ineach sector are used to split total wages into variable capital and unproductivewages, differences in estimates of these ratios also contribute to the difference be-tween Mage's figures and ours. But these do not appear to be a significant factor.


Mage complements his money value measures of Marxian categorieswith a corresponding set of labor value measures. The basic procedure isquite straightforward. By definition, Marxian labor value added is simplythe number of hours worked by productive workers (Hp). If we can some-how estimate the labor value of productive labor power (V) (i.e., of thegoods consumed by productive workers), then we can immediately calcu-late surplus value as S = Hp - V. One could then judge how well the laborvalue measures correspond to the (apparently independent) money valuemeasures.

Since Hp is readily computed from the data already used to make themoney value estimates (Mage 1963, pp. 210-11), the only remaining prob-lem is the estimate of V. And it is here that Mage adopts an apparentlysimple and appealing procedure. Since he already has a measure of themoney value of variable capital (V*), he converts it into a labor valuemeasure (V) through the estimated labor value of one dollar (A*). Byhis definition, V' = A*-V*, andS' = H p -V'=H p -A*-V* (pp. 196-8). Hethen presents labor value measures that are very similar to his earliermoney value measures (compare charts VI-1, VI-2, and table VI-1 on pp.172-5 to charts VIM, VII-2, and table VIM on pp. 204-9).

The money value and labor value measures appear to be largely inde-pendent of one another, so that their close correspondence seems to implythat price-value deviations are negligible. Although this might indeed bethe case, Mage's technique provides no evidence for it at all. To see this,let us define the labor value of one dollar as the ratio of the money valueof Marxian value added to the hours of productive labor (which is thelabor value of Marxian value added): A* = VA*/HP. Then it can be im-mediately shown that Mage's definitions will yield a "labor value" rate ofsurplus value which is identical to the corresponding money rate. Recallthat Marxian value added VA* = V* + S*, while hours of productive laborHp = V + S. Suppose we now define the value of money as A* = Hp/VA*;then we can multiply the expression for VA* by A* to obtain

Hp = A*-V*+A*-S*

It is clear that if we further define the "value of labor power" to be V'=A*-V*, then S' = HP-V'=A*-S*, so that S*/V* = SVV. This is simplyan algebraic identity. Mage seems aware of the tautological nature of hislabor value procedure. He argues that the theoretically appropriate mea-sure of A* would be "the ratio between the number of hours of produc-tive labor performed during the year, and the money value of the netproduct of that year." Had he used his own preferred measure, Magewould have ended up with identical rates of surplus value in both valueand money terms. But he chose instead to use the ratio of gross labor


value added to gross value added, justifying it on the somewhat speciousgrounds that this "allows direct calculation in labor-units and is thereforepreferable in the current context" (1963, p. 197). In fact, his theoreticallypreferred measure of the value of money is readily calculable from hisdata, whereas the measure he actually uses requires him to engage in avery roundabout, iterative estimation procedure (pp. 198, 212-14). Hisjustification for all of this makes no sense, save to provide slightly differ-ing estimates in the two sets of measures.

There is another side to this matter. In recent years, several authors(Foley 1982; Lipietz 1982) have tried to turn Mage's algebraic identity intoa "new" solution to the transformation problem by simply defining boththe value of labor power and the value of money in the appropriate man-ner. What they neglect to mention are the implications of such a proce-dure. As just defined, the value of money A* is the living labor commandedin exchange by the net product. This means that the value of labor powerV is the living labor commanded by the money wage bill of productiveworkers, and that surplus value S' is simply the living labor commandedby the existing mass of profit. Marx argued that price and profits weremonetary forms of value and surplus value. The new approach abandonsthis altogether by defining surplus value to be a form of profit! The wholerelation between surplus value and profit is turned on its head. Moreover,this approach does not even have the virtue of being new, since it is reallynothing more than Adam Smith's second definition of labor value as theliving labor commanded by price. Ricardo and Marx decisively rejectedthis approach, with good reason.

In summary, Mage pioneers the analysis of the relation between Marx-ian categories and national income accounts (albeit only on the value,as opposed to the product, side of the accounts). He is theoretically so-phisticated, and extraordinarily knowledgeable about empirical issues.He correctly identifies the money form of total value as the sum of thegross output (in the IO sense) of the production and trade sectors. Histreatment of variable capital is also a major step forward, since he gen-eralizes Varga's distinction between productive and unproductive laborwithin manufacturing to all productive sectors. But his text is frustratingbecause it does not provide any systematic treatment of the relation be-tween Marxian and NIPA categories. Rather than starting with total valueor even value added and then working down to surplus value, he proceedsinstead by building up the latter from a variety of data sources. Itemssuch as unproductive wages, taxes of various sorts, and the wage equiva-lent of proprietors and partners tend to get lost in such a process. Butperhaps the most important defect of his work is his reduction of sur-plus value and variable capital to the disposable income of capitalists and


workers - that is, to what orthodox economics would call disposable "fac-tor incomes." This is what accounts for his falling rate of surplus value inthe postwar period.

The first systematic derivation of the relation between Marxian cate-gories and national income accounts appears in the work of Shaikh (1978b),who begins from the distinction between productive and unproductivelabor and builds up to the various forms of the circulation of value. He isalso the first to adjust the rate of surplus value for the net tax ("socialwage") on labor. The present book is an extension of this earlier work.

Shaikh (1978b) emphasizes the critical importance of having empiricalcategories that correspond to the theory under consideration (pp. i-iii).He derives the Marxian distinction between productive and unproductivelabor from more general considerations (pp. 1-11), and then shows howthis fundamental distinction affects the relation between Marxian andorthodox economic categories (pp. 12-31). Beginning with only produc-tion activities, he successively introduces trading, rental, financial, andgovernmental activities. Each stage in the argument is used to furtherconcretize the mapping between Marxian and NIPA categories. His finalresult is essentially the same as the revenue side of our present approach(p. 30). As Shaikh notes, the total value of the final product appears asthe gross product of "the productive sector and trading sector... becausethese are the only two sectors through which the commodity-product it-self passes on its way to its realization as money" (p. 31). Constant capitalis the intermediate inputs of the productive sector, and variable capital isthe wage bill (after net taxes) of productive workers in the productivesector. All of the rest of total value is surplus value (pp. 30-1). Shaikhemphasizes the great conceptual and empirical difference between the re-sulting "rate of surplus value and . . . its fetishized form, the profit-wageratio," and points out the implications of this for Glyn and Sutcliffe andothers who confuse the two measures. Tables 6.4 and 6.5, which sum-marize the revenue side of our present approach, can also be viewed as asummary of Shaikh's mapping.

There are some important differences between Shaikh's earlier approachand our current one. Like Mage, he works only on the revenue side, where-as we work within a double-entry framework. Moreover, his empiricaldatabase is structured around national income accounts, whereas ours isgeared to the far more comprehensive input-output accounting frame-work. A major advantage of the latter is that it allows us to track the cir-culation of total value, not just of value added.

In spite of the fact that the basic theory is the same, Shaikh's empiricalestimates differ considerably from ours. His measure of surplus value istoo low because he is unable to derive an estimate of the input costs ofcirculation M(t. Shaikh guesses that this factor is probably small, but our


1.16

0.20 -S-1948 1951 1954 1957 1960 1963 1966 1969 1972 1975 1978 1981 1984 1987

Figure 6.7. Rates of surplus value: Mage, Shaikh, Shaikh and Tonak.Sources: Mage (1963); Shaikh (1978b); Shaikh and Tonak, Table H.I.

data indicates that its inclusion would have raised his estimate of sur-plus value by over 20% in 1958.40 Finally, like Mage, Shaikh covers onlythe private nonfarm economy (whereas we include both agriculture andprimary-sector government enterprises); restricts the definition of tradeto the wholesale/retail sector (whereas we count building rentals as trad-ing activities); and forgets to put the wage equivalent of proprietors andpartners into total wages after he subtracts it from unincorporated incometo get profits of unincorporated enterprises. All four factors work to re-duce his estimate of surplus value to a level considerably below ours. Thesecond factor (exclusion of agriculture and government enterprises) andparticularly the fourth (exclusion of the wage equivalent from total wages)also serve to reduce his estimate of variable capital relative to ours.41

The net result is that Shaikh's 1978 estimates are considerably higher thanMage's, but still lower than ours; see Figure 6.7.

40 From our data, Mt't = $31.61 billion in 1958. Shaikh's estimate of surplus value(without M(t) is $146,620 billion. Thus his estimate would have been raised by21.5%, all other things being equal.

41 Shaikh's estimates of variable capital are incorrect owing to calculation errors inthe treatment of services. For instance, the correct figures for 1929, 1947, and1972 in millions of dollars are 21,890, 56,868, and 230,073, respectively.


Aglietta (1979) places the measurement of the rate of surplus value atthe heart of his theory. According to him, the "nodal point of [a] theoryof capitalist regulation" is that to "study the articulation between thelaws of capitalist accumulation and the laws of competition means to elu-cidate the contradictory process of the generalization of the wage relation"(pp. 17-18). The historical evolution of the rate of surplus value plays acrucial role in this, because "the rate of surplus-value is the pivot of capi-talist accumulation" (p. 87).

Although Aglietta does distinguish between productive and unproduc-tive labor (1979, p. 89), he does not carry this over to the measurement ofthe national product. Like some others in this section, he uses the NIPAmeasure of value added as a proxy for a corresponding Marxian measure(p. 88). But Aglietta does not attempt to measure the money rate of sur-plus value directly, because he believes that the impact of price-valuedeviations is significant enough to make the money rate a biased indicatorof the trend of the value rate of surplus value. For this reason, he sets out"to find a more faithful statistical indicator [of the] long run trend" in thevalue rate of surplus value (p. 88). He concludes that the share of realwages in productivity (the "real social wage cost") is a more appropriatemeasure of the share of the value of labor power in the value added byliving labor, assuming that social productivities (the reciprocals of theunit labor values) of the consumer and producer sectors rise at roughlythe same rate in the long run. Our derivation of this relation is in Appen-dix L. As noted previously, Aglietta's argument is reminiscent of an ear-lier one by Perlo (1974), who also claims that the trend of the rate of ex-ploitation can be more accurately estimated from the "index of workers'share," which he defines to be the ratio of the real take-home pay ofworkers to their productivity (Perlo 1974, p. 30).

We have already seen that price-value deviations have only a minoreffect on aggregates such as the rate of surplus value, since the moneyand value rates are quite close and have virtually identical trends (see Sec-tion 5.10). Thus Aglietta is wrong in making this particular issue a centralconcern.42 Although this does not invalidate his procedure for estimatingthe long-term trend of the rate of surplus value, it does prevent him fromattempting to measure its level.

The theoretical content of Aglietta's technique can be addressed bycomparing his real social wage cost (real wage share) w' to the ratio it ispresumed to approximate - the share v' of the value of labor power inlabor value added. By definition, v'= V/( V + S) = 1/(1 + e), where e = S/V.

4 2 Aglietta could have measured the money rate of surplus value directly, in orderto see if its trend was indeed different from that implied by his real social wagecost indicator.


1 9 * 4 8 ' ' 19'53 ' ' ' ' 19'58' ' 19'63' ' ' ' 19*68' ' 19^73 ' ' ' 19*78' ' ' ' 1^83' ' ' ' 19*88'

Figure 6.8. Aglietta's real social wage cost versus the unit value of laborpower. Source: Table L.I.

We will call v' the unit value of labor power Similarly, Aglietta's realsocial wage cost w'= wr/y, where wr = the real wage rate per unit laborand y = productivity per unit labor. In Appendix L, we show that if thetwo measures use the same data on real wages and productivity, then

v'=(Ac/Ay)w'

whereAc = unit labor value of (workers') consumption goods, andAy = unit labor value of net output.

Thus, as Aglietta notes, the real social wage index w' will reflect theunit value index v' if Ac/Ay, the ratio of the unit labor values of consumergoods to that of the net product, is stable over time. Although this is afairly good assumption (Juillard 1992, p. 24, fig. 7), price-value devia-tions are even more stable, so that Aglietta's roundabout procedure ofestimating the trend in the rate of surplus value is not really necessary.

Figure 6.8 compares the index of the unit value of labor power v*'(based on the money rate of surplus value, which we know from Section5.10 to be a good proxy for the value rate) to two Aglietta-type indexesof the "real social wage cost": v", based on our own data; and w', esti-mated directly from Aglietta (see Appendix L and Table L.I for details).Several things stand out in Figure 6.8. One can see that our Aglietta-type


measure v", based on our own data, is indeed a good proxy for the long-term trend of the (true) unit value index v*'. Thus Aglietta is correct inhis theoretical claims for such an approximation, even though (as we haveargued) the relatively small impact of price-value deviations makes itunnecessary. We also see that Aglietta's own index w', as derived fromhis Diagram 1 (Aglietta 1979, p. 91), is a fair proxy for our index v*': bothindicate a rising rate of surplus value (i.e., a falling unit value of laborpower) until roughly the mid-1960s, and an apparent change in trendafter that. However, it is clear that shorter-run movements are not at allsimilar. These latter movements are quite important, however, becausewithin his theoretical framework they are supposed to be the "essentialdeterminants of the ups and downs of accumulation" in the "regime ofpredominantly intensive accumulation" which supposedly characterizesthe postwar U.S. economy (p. 203). Given the crucial role played by thisindex, it is quite sijrprising that he fails to document the sources andmethods involved in its construction. We will not pursue the issue further,except to note that within our approach it is the rate of profit, rather thanthe rate of surplus value, that drives the long-term patterns of accumula-tion (see Chapter 7 and Shaikh 1992a).

Gouverneur (1983) presents a rich and subtle treatment of capitalist pro-duction and profit. He distinguishes between the production and circula-tion of use values, between value-producing and surplus-value-producinglabors, and between services that are part of commodity production andthose that are part of circulation ("commercial and financial business")or social administration ("education, justice, defence, etc."). He is care-ful to note that unproductive capitalist employees also perform surpluslabor (1983, pp. 73-7). Like Eaton, he assumes that the net tax on laboris zero: "we are going to assume quite simply that the wage-earner's sharein the financing of collective products is equal to their share in the con-sumption of them" (p. 69). At an empirical level, he assumes that the con-ventional measure of value added represents the Marxian measure of "newrevenue created (in monetary terms)," and defines variable capital as theestimated wage bill of productive workers and self-employed persons (pp.93, 243, 246).43 On this basis, he calculates real (constant-price) rates of"surplus labour" for France, Germany, Belgium, Netherlands, and theUnited Kingdom. He finds that these rates range from 62% to 98% in

4 3 Gouverneur calculates the real rate of surplus value S'=[E/(w/d)] — 1, whereE = net national product per hour of productive labor and w/d = real wage ofproductive labor. Productive labor is calculated as the hours of all persons (em-ployees and self-employed) in productive and trade sectors (Gouverneur 1983,pp. 92-4, 243-7). The real wage of productive workers is assumed to be equal tothe average real wage (p. 250).


1978, and that they generally rise over time. On the whole, his estimatesof the rate of surplus value are much smaller than ours would be, largelybecause his measure of variable capital includes unproductive workers inthe productive sectors as well as all workers in the trade sectors. For in-stance, we calculate the rate of surplus value in the United States in 1978to be 207% (Table H.I). If we were to instead use Gouverneur's measureof (NNP — Wpt)VWpt, with Wpt = all wages in productive and trading sec-tors, we would get a rate of surplus value of 81% for the United States -very much the order of magnitude that Gouverneur obtains.44

The next set of NIPA-based estimates of the Marxian aggregates comesfrom Moseley (1982, 1985). Like Shaikh, he is concerned to emphasizethe crucial difference between the rate of surplus value and the profit/wage ratio. He notes that his methodology for measuring variable capital"is broadly similar to that in Mage (1963) and Shaikh (1978)" (Moseley1985, p. 75, n. 1), except that he includes one-half of trade sector wages,and mistakenly includes all agricultural wages and a fraction of the wagesof government administrative employees, in variable capital.45 But likeMage and Shaikh, he too fails to include any portion of the wage equiv-alent of productive-sector proprietors and partners in variable capital,so that his estimate is about 7% smaller than ours (Moseley 1985, p. 71,table A.I).

Moseley identifies Marxian gross value added with the nonimputed GDPof capitalist businesses. As defined in NIPA, the business sector includesgovernment enterprises (and of course agriculture), but excludes govern-ment administration and households and institutions. From this, Mose-ley further excludes all imputations included in business GDP. By andlarge this is correct, because it ends up eliminating the fictitious entryfor the imputed rental value of owner-occupied housing (the gross hous-ing product) and restores the net interest paid by business to the finan-cial sector (NIPA adds this to intermediate inputs, and subtracts it fromvalue added by creating a matching negative entry for "imputed interestreceived," as noted in Section 3.2.1 and in Appendix B). But Moseleyalso subtracts the income of unincorporated enterprises in agriculture,

4 4 For 1978, N N P = $2,019.8 billion (Table 1.2); W; = $1,114,207 billion = all wages(employee compensation plus the wage equivalent of self-employed persons) inthe production and wholesale/retail sectors, calculated as total wages minus wagesin finance, insurance and real estate, and government administration (Table G.I).

4 5 Moseley's estimation of variable capital contains inconsistencies, since he includesall of agricultural wages and part of government wages within productive wageseven though his measure of gross value added excludes both agricultural unincor-porated enterprises and government administration (Moseley 1985, p. 77: "Vari-able Capital," n. 11-12; "New Value," n. 1,10-11). Note that government admin-istration is excluded from the NIPA definition of "business."


construction, and services, presumably on the grounds that they representnoncapitalist flows. This seems improbable to us. Until the invention ofthe legal form called a "corporation," all capitalist enterprises were non-corporate; hence the noncorporate form of these particular enterprisesdoes not render them noncapitalist. Nor is there any compelling reasonto believe that most of noncorporate agriculture, construction, and ser-vices is nonprofit. In any case, this last set of deductions further reducesMoseley's estimates of net value added by about 6% in 1958.

From the point of view of our present procedure (summarized in Table6.4), Moseley's procedure leaves out the portion of royalties RYpt whichrepresents ground rent and financial services charges paid by the produc-tion and trade sectors,46 as well as the intermediate inputs M'n of the trad-ing sectors. On the other hand, it adds in the GDP of the nonimputedroyalties sectors (finance, ground rent, and royalties), which partially off-sets the first two exclusions. The net effect is that his estimate of Marxiangross value added is some 20% lower than ours in 1958. This is the prin-cipal reason for his lower rate of surplus value.

Tonak (1984) focuses on the impact of state taxation and expenditureson the rate of surplus value. As part of his empirical analysis, he extendsShaikh's estimates of the net tax to the whole postwar period in the Unit-ed States. He also attempts to provide a fairly simple approximation ofMarxian value added, from which he subtracts his estimated variable cap-ital to obtain a measure of surplus value. The purpose of this approxima-tion is to trace the impact of the net tax on the U.S. rate of surplus valuein the postwar period.

Tonak approximates Marxian gross value added by using the NIPAmeasure of nonimputed business GDP.47 This is similar to the approachof Moseley, except that Tonak does not make any further subtractions.Thus in 1958 his measure of value added is about 6% higher than that ofMoseley's, though still 12% lower than ours (for the same reasons as inMoseley). As it turns out, his estimate of variable capital is also lowerthan ours by roughly the same percentage (14%), primarily because (likeMage, Shaikh, and Moseley) he neglects to take account of the produc-tive portion of the wage equivalent.48 These two underestimates end up

46 As already noted, Moseley's procedure restores into value added that portion ofroyalties which represents net interest paid to the financial sector.

47 Tonak (1984, p. 110) also makes a small adjustment for surpluses of government-owned liquor stores.

48 Tonak defines variable capital as the employee compensation of production work-ers, estimated as the sum of production worker wages from BLS and the pro-ductive fraction of employer contributions to social insurance from NIPA. Theestimate of employee compensation is too low, since it should have also includedthe productive portion of "other labor income." More importantly, Tonak's pro-cedure does not account for the productive portion of the wage equivalent of


•~i—i—i—i—i—i—i—i—i—i—i—i—i—i—i—i—i—i—i—i—i—i—i—i—i—i—i—i—i—i—i—i—i—i—i—i—i—i—i—r1948 1951 1954 1957 1960 1963 1966 1969 1972 1975 1978 1981 1984 1987

Figure 6.9. Rates of surplus value: Moseley, Shaikh, Tonak, Shaikh andTonak. Sources: Moseley (1985); Shaikh (1978b); Tonak (1984); Shaikhand Tonak, Table H.I.

largely offsetting each other in the determination of the rate of surplusvalue. Figure 6.9 compares the various estimates to ours, with Shaikh'sestimates included as a point of reference for Moseley. It is evident thatMoseley's rate of surplus value essentially duplicates the movements inShaikh's estimates. On the other hand, Tonak's measure approximatesours fairly well up to 1963, but then increasingly overestimates it.

The first systematic investigation of the effects of state taxation andredistribution on the rate of surplus value appears in Shaikh (1978b). Hedefines the net tax on labor as the difference between actual taxes paidby workers to the state and the social benefit expenditures directed backtoward workers by the state. The effective wage of workers is their nomi-nal wage minus any net tax (or plus any "social wage," should the net taxhappen to be positive). Because the wages of unproductive workers arepart of surplus value, any net tax on their wages amounts to a transferwithin surplus value from them to the state. But in the case of productiveworkers, such a transfer redefines variable capital itself, since the net tax

proprietors and partners, even though his estimate of total labor does includethe productive portion of the labor of self-employed persons (Tonak 1984, pp.161-2,165-73).


must be subtracted from variable capital and added to surplus value.Shaikh makes detailed estimates of this effect for 1952, 1961, and 1970.Taxes actually paid by workers are assumed to consist of all of socialsecurity taxes as well as the estimated labor portion of income taxes andof the small category called "other taxes and nontaxes" (personal prop-erty taxes, license and other fees, etc.). The corresponding benefits ofworkers are estimated as the sum of government expenditures on socialsecurity, unemployment benefits, and housing and community develop-ment, as well as the workers' share of health, education, utilities, andtransportation expenditures. The net tax is calculated as the differencebetween labor taxes and labor benefits. Shaikh finds that this quantity ispositive in all three years sampled. Applying the resulting net tax rate tothe wages of productive workers raises his estimated rate of surplus valueby 7<7o-16<7o (Shaikh 1978b, pp. 35-8).

Tonak (1984) extends this approach to the whole postwar period. Be-cause previously published estimates of the labor proportion of incometax payments were available only for selected years, he develops a goodannual proxy for this proportion by taking the share of wages and sal-aries in personal income.49 This "labor share" is then used to estimate notonly the amounts of income taxes and fees paid by workers, but also theamounts of certain social benefit expenditures (such as health and educa-tion) that are deemed to be spent on workers.50 On the tax side, Tonakcorrects for the fact that a portion of property taxes paid by workersshows up under indirect business taxes because NIPA treats homeownersas rental firms renting out their own homes to themselves (a fact we havealready encountered in Section 3.1.3), and re-assigns the lottery receiptsof the government to the category of workers' taxes (as a kind of volun-tary net transfer). On the government expenditure side, he estimates thelabor portion of social benefits, both with and without expenditures onpublic assistance.51 These factors, plus revisions in the NIPA accountsthemselves, account for the differences between Shaikh's and Tonak's es-timates of the net tax on labor; but the basic patterns are the same. Tonaktoo finds that the net tax is generally positive (except in 1975), so that his

49 Tonak shows that his "labor share" is a good proxy for both Kahn's (1966) andWeisskopf s (1984) direct estimates of the portion of income taxes paid by wageand salary earners.

50 The assumption that expenditures can be allocated to labor in proportion to theirshare in taxes paid amounts to the assumption that social benefits are accordedto groups in accordance with their "taxable base."

51 Shaikh omits public assistance on the grounds that it is not a part of labor in-come of employed workers or their families, and hence does not enter into thenet tax on the wages of employed productive workers, i.e. on variable capital(Shaikh 1978b, apx. C.II, p. 60, n. 6).


adjusted rate of surplus value is generally higher than his nominal rate.Our estimates in Section 5.9 are based on Shaikh and Tonak's (forth-coming) extension of these calculations; their effect on the rate of surplusvalue was shown in Figure 5.24.

Papadimitriou (1988) analyzes the Greek economy from 1958 to 1977,using essentially the same schema as we do; any concrete differences aredue to data limitations. Variable capital is defined as the wages of allworkers in the production sector, net of estimated corporate officers' sal-aries (p. 152). Also, the entire real estate sector is treated as a royaltiessector, since no consistent evidence could be found on its division betweenbuilding rents and ground rent (p. 155). Papadimitriou constructs mea-sures of the rate of surplus value, the organic composition of capital, andof the rate of profit. The latter two are adjusted for variations in capacityutilization by means of a Wharton-type measure of the rate of capacityutilization, which he also constructs (p. 157). For the two decades spannedby his data, Papadimitriou finds that the rate of surplus value rises mod-estly, ranging from 2449b in 1958 to a peak of 31797b in 1976, and then fallsback to 288% in 1977. Over this same interval, however, the organic com-position of capital (defined as the ratio of fixed capital to variable capi-tal, divided by the rate of capacity utilization) rises much more sharply,by over 709b. The general rate of profit falls steadily, by roughly 309boverall (p. 153, table 20). Papadimitriou also shows that the rate of sur-plus value S*/V* is about 509b larger, and rises more rapidly, than thebroadly defined profit/wage ratio P/W (pp. 170-1). Similarly, the Marx-ian measure of productivity is almost twice as large as a conventionallydefined measure (p. 176); thus, neither conventional measure is a goodproxy for its Marxian counterpart. However, he does find that the Marx-ian measure of GVA* is well approximated by GNP. This implies that,for the Greek economy, the great source of variation between Marxianand orthodox categories arises from the difference between variable cap-ital and all wages.52

In an independent study, Tsaliki and Tsoulfidis (1988) provide a sim-ilar set of estimates for the Greek economy, also for 1958-73. Workingwith the 35-sector Greek input output tables in current prices, they esti-mate the money forms of the rate of surplus value, the value compositionof capital, and the rate of profit, all for the nonagricultural economy.They divide the economy into three sectors: nonagricultural production,which includes productive services; circulation, which consists of trade,banking, and housing; and social maintenance, which is public services.

52 If GVA* ~ GNP, then gross surplus value SJ • GNP - V* and PG = GNP - W,where W = all wages.


Table 6.6. Rates

PapadimitriouTsaliki and

Tsoulfidis

1958

2 44

3 08

of surplus value in Greece, selected years

I960 1962

2 35 2 43

3.02 3 18

1964

2.46

3.15

1966

2.41

3.01

1968 1970 1972 1974

2.52 2.74 2.79 2.95

3.14 3.27 3.30 3.82

1976

3.17

4.06

1977

? 88

4 08

Sources: Papadimitriou (1988, p. 170, table 21); Tsaliki and Tsoulfidis (1988, p. 205, fig. 1).

Variable capital is defined as the wages of nonsupervisory workers in theproduction sector (Wp)p,53 and all other wages are unproductive. Surplusvalue is defined as the sum of produced profit (realized profit plus thechange in inventories) in the productive sector, plus the gross output (inthe IO sense) of the unproductive sectors. But here they include too much,since only the gross output of the trade sector should be counted (seeSection 3.6). For this reason, their estimates of the rate of surplus valueare too large, typically about 30% larger than those of Papadimitriou(although the trends of the two are similar). Like Papadimitriou, theyadjust their profit rates and value compositions of capital for capacityutilization, which they define as the quadratic trend of real GDP (1988,p. 200, n. 18). In their analysis of the Greek economy, Tsaliki and Tsoul-fidis note that it underwent rapid industrialization in the 1960s and 1970s,with correspondingly rapid mechanization of production and high growthrates of capital and investment. But by the late 1970s, these growth rateshad collapsed and even turned sharply negative (pp. 189-90). Tsaliki andTsoulfidis explain this phase change by the rapid mechanization of theeconomy, which caused the rate of profit to fall, which in turn led to thestagnation of the mass of profit and the collapse of accumulation in themid-1970s. They find that from 1958 to 1973 the rate of surplus value risesmodestly, as do the (utilization-adjusted) wages/capital ratio and the ad-justed Marxian and actual rates of profit. But from 1963 to 1977, all thesetrends are sharply reversed (pp. 205-9, figs. 1-5).

Table 6.6 compares the rate of surplus value estimates of Papadimitriou(1988) and Tsaliki and Tsoulfidis (1988). While the levels are different,the relative movements are quite similar.

6.2.3 Aggregate labor value estimatesThe last set of aggregate estimates in this section is based upon

input-output tables. Such tables permit the calculation of both labor value

53 Tsaliki and Tsoulfidis (1988, p. 199) estimate supervisory salaries to be 3% oftotal wages and salaries.


and money forms of Marxian categories, so that we can directly comparethe two. The relations between the two types of calculation were discussedin Section 4.1. It was shown there that if the two sets of calculations areto be consistent, in the sense that all money magnitudes would be propor-tional to the corresponding labor value magnitudes when purchaser priceswere proportional to labor values, then the two modes of calculationmust be asymmetric.

To be more specific, we showed in Section 4.1 that because all commod-ity bundles in actual input-output tables are valued at producer prices,calculations of unit labor values will actually yield labor-value/producer-price ratios A*. Following the procedure developed in Shaikh (1975), thesemay be calculated as

A* = hp*+A*app*and

whereA* = row vector of labor-value/producer-price ratios;X*j=Xj/Pj;

Xj = unit labor values; andpy = unit producer prices.

In order to derive labor value measures of various commodity bun-dles, we apply the value/price ratios to the prices (money values) of thesesame bundles. But since the A*s are ratios of labor values to producerprices, we must be careful to apply them only to the producer-price com-ponents of these money values. With reference to Figure 4.1, the laborvalue of productive inputs C is derived by multiplying only the matrix ofelements (Mp)p by the vector of value/producer-price ratios A*, just asthe labor value of productive labor power V is derived by multiplyingthe producer-price component of the consumption basket of productionworkers (CONWp)p by A*. Yet the corresponding money value of constantcapital C*, which is the purchaser price of productive inputs, is equal totheir producer price (Mp)p plus the trading margin on these same inputs(Mp)t, while the money form of variable capital V* is the sum of both theproducer-price elements (CONWp)p and the corresponding trade margin(CONWt)p. The asymmetry in the modes of calculation of labor value andmoney magnitudes is due solely to the fact that input-output tables arecast in terms of producer prices. Their consistency is revealed by the factthat they yield the same result when purchaser prices are proportionalto labor values. The revenue side of the money and labor value accounts,shown in Table 4.1 are reproduced here as Table 6.7.

It is a corollary of these results that the procedures which make the cal-culations of money magnitudes symmetric with labor value ones will yield


Table 6.7. Money and labor value measure: Revenue side

Labor valueMoney value measures measures

C*=M p = (Mp)p + (Mt)p C = A*-(Mp)p

VA*=VAp + VAt + RYp + RYt + (Mp)t + (Mt)t VA = Hp

V* = Wp = CONWp = (CONWp)p 4- (CONWp)t V = A* • (CONWp)p

S* = VA*-V* S = V A - V

incorrect estimates of the former. We shall see that this is precisely theproblem with the general methodology proposed by Wolff (1977b, 1987).

The first calculation of the labor value rate of surplus value comesin Okishio's (1959) pathbreaking study for Japan in 1951. Also availablein English are subsequent studies by Izumi (1980, 1983) and by Okishioand Nakatani (1985). As noted in the beginning of this chapter, theseestimates are part of a long tradition in Japan which began as early as1924.

Okishio is the first not only to utilize input-output tables, but also todistinguish between productive and unproductive labor (1959, pp. 1-4).His calculations are similar to those we would use, with two notable excep-tions. First of all, he treats all services as unproductive, although this maysimply be due to the fact that his input-output data combine banking,real estate, and services into one sector (pp. 4, 6). More importantly, histreatment of unproductive activities inflates the measure of productiveworkers' consumption, which in turn reduces his estimate of the rate ofsurplus value. Okishio begins by dividing his estimate of an average work-er's daily consumption bundle into the commodities (conwp)p purchasedfrom productive sectors, and the unproductive expenditures (conwp)u com-prised of trade margins, rental and royalty payments, and expenditures onservices. The correct procedure at this point would have been to multiplythe former by A* to obtain the unit value of labor power n = V/(V + S) =A*'(conwp)p, the unit surplus value (1 — n); and the rate of surplus valuee = (1 — n)/n = S/V. But Okishio argues that - because a portion of theunproductive expenditures goes to support the workers in unproductiveindustries, whose unproductive expenditures in turn support other unpro-ductive workers, and so on ad infinitum - the total unproductive workerconsumption derived from the wages of productive workers should beconsidered as part of the total consumption of productive workers. Thushe ends up with an expanded measure of the productive consumptionvector of productive workers:


(conwp)'p = (conwp)p + (conwp)'u = 1.086(conwp)p,

where (conwp)'u = 0.086(conwp)p.54

Okishio's own estimates of the unit value of labor power are n' =A*-(conwp)p = 0.518, of unit surplus value ( l - f l ' ) = 0.482, and of therate of surplus value e'= (1 -n')/n'= 92.9%. He notes that his estimatedlabor value rate of surplus value "may be considered to be lower than thelevel which is expected" (1959, p. 8), given the results of previous esti-mates of the money rate of surplus value. But he argues that the moneyrates are higher than the value rates because the former reflect large trans-fers of value from the agricultural sector (pp. 8-9). While this may wellbe true, his estimate of the value rate is itself biased downward by histreatment of unproductive expenditures. Correcting for this by dividingri by 1.086 raises the estimated rate of surplus value by about 20%, asshown in Table 6.8 (to follow).

The corrected estimate of e = 112.8% for 1951 is theoretically and empir-ically consistent with the subsequent Okishio and Nakatani (1985) estimateof e = 134.4% in 1980. This latter study also distinguishes between pro-ductive and unproductive labor, but counts services as fully productive -probably because the 1980 input-output table does not merge the servicesector with the banking and real estate sectors. Productive sectors aredefined as all business sectors except trade and finance, insurance, andreal estate. Our procedure is quite close to this,55 except that we countbusiness, legal, household, and miscellaneous professional services aspart of the royalties sector. The calculation procedure for unit-value/price ratios, for the value of labor power, and for the rate of surplusvalue are now identical to the procedures outlined in Section 4.1, with notrace of Okishio's previous treatment of the unproductive expenditures

54 Let production worker wages = wp. Some of this goes for unproductive expen-ditures, of which a portion is the equivalent of the wages of the unproduc-tive workers supported out of this revenue. Okishio calculates that 7.9% ofwp goes to directly support unproductive worker wages. Of course, as theseworkers consume their wages, 7.9% of their wages goes toward unproductiveworker wages, etc. Thus the total wage "associated" with productive workerwages = wp + (.079)wp + (.079)(.079)wp+ ••• = wp-[ 1 / (1- .079)] = wp-(l/.921) =(1.086)-wp. Okishio applies the factor 1.086 to the productive components ofproductive worker consumption to derive his expanded measure of productiveworker consumption (Okishio 1959, pp. 6-7, 9-10, table columns 8-9).

55 Okishio and Nakatani (1985, p. 5) state that unproductive activities are "unnec-essary from the technical point of view of the production process." This is anambiguous statement, due perhaps to the exigencies of translation. Clearly, allnonproduction activities are by definition "technically" unnecessary for produc-tion, but this does not imply that they are socially unnecessary. We have triedto emphasize throughout that unproductive activities are not synonymous withunnecessary activities.


of productive workers. Even so, Okishio and Nakatani's estimate of e =(1 - n)/n = 134.4% in 1980 is substantially lower than Izumi's (1980) esti-mate of e = 205% in 1975, which itself is lower than it should be becauseIzumi overestimates the value of labor power, as we will describe shortly.Okishio and Nakatani (1985, p. 8) once again note that their result is"lower than the expected level," and once again explain this as due to thefact that realized rates of surplus value for manufacturing embody a sub-stantial transfer of value from other sectors. But such a transfer-of-valueeffect would not explain the discrepancy between their result and that ofIzumi, particularly since his measure is for "materials goods producingsectors," in which manufacturing undoubtedly plays a great part. This isan issue that clearly needs further investigation.

Izumi defines productive industries as nonagricultural "materials goodsproducing sectors" only. Trade, finance and insurance, real estate, com-munications, and the whole service sector are relegated to the categoryof "services," all of which are considered unproductive (Izumi 1980, pp.4-6). Unit labor-value/producer-price ratios are calculated in the mannershown in Section 3.6, and these are applied to the producer-price com-ponent of productive worker consumption to derive what we would defineas the value of productive labor power V (pp. 9-10). But at this pointIzumi (p. 10) stops to ask: "By arguing that the labor of only productionworkers in the material goods producing sectors creates value, how dowe account for the consumption of services by production workers?" Hisresponse is to assume that "when production workers consume services,they are, in effect, consuming indirectly the material goods required forthe supply of these services" (pp. 10-11). So he adds an estimate of thelabor value of the total (direct and indirect) materials requirements Cm'u

of the unproductive (service) sectors56 to the value of labor power V,yielding an expanded value of labor power V = V + Cm'u. This is then sub-tracted from the total hours of productive labor Hp to obtain (reduced)surplus value S / = H p - V / = ( H p - V ) - C m u = S-Cmu, where S = ourdefinition of surplus value. Note the similarity between the Okishio (1959)and Izumi (1980) treatments of the unproductive expenditures of produc-tive workers: the former adds to productive worker consumption the directand indirect workers' consumption induced by the unproductive expendi-tures of production workers, while the latter adds the direct and indirectmaterials used up in these same unproductive activities. Quite naturally,Izumi also derives estimates of the labor value rate of surplus value whichare "consistently lower" than the money rate of surplus value estimated

56 Izumi (1980, pp. 10-12) calculates the direct and indirect materials requirementsfor the production of materials used by, surplus product used by, and workers'consumption of, the service sector.


Table 6.8. Estimates of the value rate of surplus value inJapan, selected years

1951 1975 1980

Okishio (1959) 0.929 — —Okishio (corrected) 1.128 — —Izumi (1980,1983) 0.43 2.05 —Okishio and Nakatani (1985) — — 1.344

Sources: Okishio (1959, p. 8); Izumi (1980, table 5; 1983, table 1); Okishio andNakatani (1985, p. 7).

by others at the time (p. 13). He too explains this as arising from transfersof value from agriculture to industry in Japan, which make the realized(money) rate of surplus value in industry much larger than the value rate(1980, p. 13; 1983, p. 13). Izumi (1983) extends his estimates to later yearsin Japan, as well as to the United States and the Republic of Korea. Theselater estimates for Japan are somewhat higher and rise rapidly. Table 6.8compares the estimates of Okishio (1959), Izumi (1980,1983), and Okishioand Nakatani (1985).

Izumi's discussion is sophisticated and insightful, although we disagreewith his treatment of the value of labor power (to which we return shortly).He provides estimates of industry rates of surplus value, and notes thatthey differ greatly from corresponding profit/wage ratios because the latterreflect transfers of value between industries and between industry and agri-culture. This indicates that profit/wage ratios are not reliable indicatorsof industry rates of exploitation, which invalidates many past studies onthe subject (Izumi 1980, pp. 15-21). He also finds that big businesses havehigher value rates of surplus value, again in contradiction to studies basedon money measures (p. 26).

In a subsequent paper, Izumi extends this same method to a compari-son between the rates of surplus value in Japan, the United States, andSouth Korea (Izumi 1983, p. 10). Here his results are even more at oddswith those of other studies, including Amsden's study analyzed earlier inthis section, in that he finds value rates to be lowest for South Korea andhighest for the United States. This implies that the rate of surplus valuerises with the level of development - not only historically, but also cross-sectionally. He explains this by arguing that because previous studies areof money rates of surplus value, they capture not only surplus value pro-duced within the nonagricultural productive sector but also value trans-ferred to that sector. This transfer of surplus value is very large for Japan,


Table 6.9. Rates of surplus value, Izumi vs. Khanjian

Izumi: South KoreaIzumi: JapanIzumi: United StatesKhanjian: United States

Izumi/Khanjian

1958/1960

1.241.722.64

0.65

1963/1965

1.571.892.64

0.72

1967

—2.142.88

0.74

1970/1972

0.921.702.042.87

0.71

1975/1977

1.382.052.312.91

0.79

Sources: Izumi (1983, table 1) - for Japan, 1960, 1965,1970,1975; for the U.S., 1958,1961,1963,1967,1972,1975. Khanjian (1988, table 19) - for the U.S., 1958,1963,1967,1972,1977.

he argues, coming primarily from Japanese agriculture itself. Hence thefinding that the realized rates of surplus value are higher for Japan thanfor the United States does not necessarily contradict his opposite resultfor produced rates of surplus value (pp. 14-16). Table 6.9 presents Izumi'sestimates of the value rate of surplus value, together with Khanjian's as areference point for the United States. Note that Izumi's figures for theUnited States are lower than those of Khanjian by 20%-35% owing tothe former's inflation of the measure of the value of labor power (whichis discussed further in what follows).

Izumi's inclusion of the value of the unproductive sector's total (directand indirect) materials requirement Cm^ within the value of labor poweris quite unnecessary. The problem arises because he does not adequatelyaddress the content of the category of "services." To the extent that somepart of the service sector consists of productive activities, it should bedirectly included within the productive sector (as we have done). On theother hand, we have shown that unit values calculated from actual input-output tables are really labor-value/producer-price ratios, so that the la-bor value of a commodity bundle such as the wage basket of workersmust be calculated as the product of these value/producer-price ratiosand the producer-price component of the commodity bundle. Becausesuch a calculation uses neither the trading margin nor the royalty flows,it seems to exclude unproductive activities simply because they are unpro-ductive. But this is an illusion. Trade margins are excluded because moderninput-output tables are constructed in terms of producer prices, which iswhy the unit-value calculations yield value/producer-price ratios. If thesetables were constructed in terms of purchaser prices then they would yieldlabor-value/purchaser-price ratios, and the corresponding commodityelements in any bundle would also have to be valued at purchaser prices -so that trade margins would now be included. The exclusion of royalties


is another matter altogether, since they represent transfers as opposed topurchases. To be consistent with his own sectoral division, Izumi shouldhave used only the producer-price components of the consumption vector.

Izumi's cross-country comparisons are harder to evaluate. His treat-ment of the value of labor power lowers all of these estimates, but we donot know to what degree this effect operates in Japan and South Korea.He claims that the rate of surplus value is highest in the United States,despite its highest wages and shortest working day, because U.S. averageproductivity is so much greater. The opposite holds for South Korea,with Japan in the middle (Izumi 1983, p. 14). It is interesting to note thatKalmans (1992, pp. 124-30) also finds that both the money and value ratesof surplus value are higher in the United States than in Japan. On thewhole, Izumi's study leads him to three conclusions: the rate of exploita-tion rises over time; it is higher in more advanced capitalist countries; andit grows more rapidly at lower levels of development (p. 19).

Wolff (1977b) provides the first published attempt to construct a generalprocedure for estimating Marxian categories from input-output tables.He begins with the assumption that all labor is productive, shows howunit labor-value/producer-price ratios may then be calculated, and dem-onstrates that money and labor value calculations are completely sym-metric when all labor is assumed to be productive (pp. 88-9). He thenintroduces the distinction between productive and unproductive labor,being careful to note that unproductive activities can be quite necessary(p. 97). This leads him to divide the IO tables into productive and unpro-ductive sectors, with the trade sector counted among the latter (pp. 92-4).On this basis, he provides new procedures for the calculation of value/price ratios and labor value magnitudes (pp. 95-6), which are the same asthe ones we summarized previously. But in the treatment of money mea-sures, he mistakenly generalizes the previous symmetry between Marxianand IO categories to the situation when some labor is unproductive; thisleads him to calculate money magnitudes in an exactly symmetric mannerwith labor value magnitudes (p. 95).57 His money measures are there-fore inconsistent and incorrect. Khanjian (1988, pp. 122-30) illustratesthe problem with a numerical example based on Wolff's procedures. Weshowed in Section 4.1 that the money rate of surplus value estimated inthis manner will typically be larger than the value rate. Indeed, Wolff'sestimates of S*/V* are generally higher than those of S/V by 4%-8%.Given that the consistent estimates made by Khanjian yield money rates

57 By merging trade with other unproductive sectors, Wolff treats all unproductiveflows as types of royalties. It is the absence of a distinct role for trading activitiesthat makes his money accounts symmetric with his labor value accounts; this isalso precisely what makes the two inconsistent.


of surplus value that are smaller than the value rates by 7%-9%, we con-clude that Wolff's inconsistent procedure creates an upward bias in the es-timates of S*/V* of about 12%-15% (in years common to both studies).

There are several other features to be noted. Wolff's mapping betweenMarxian and input-output categories is partial, because it is confined tothe use side alone. His estimates of rates of surplus value are somewhathigher than ours, because he subtracts income taxes from his measure ofproductive worker wages but fails to add in government social benefit ex-penditures. This reduces his measure of variable capital (1977b, p. 112). Healso implicitly treats all income of unincorporated enterprises as property-type income, since he makes no provision for subtracting out the wageequivalent of self-employed persons. Finally, it is striking that Wolff(pp. 87-9,105,108-12) repeatedly treats the Marxian measure of the sur-plus product as synonymous with the Baran-Sweezy concept of "surplus,"although he also argues (p. 97) that unproductive activities can be neces-sary. We will see in Section 6.3 that the two concepts are very different,which becomes quite clear when we compare the respective empirical pro-cedures involved.

Wolff's second attempt comes in his 1987 book, which is a rich andinteresting extension of his earlier analysis. It attempts to provide a fulldouble-entry accounting of the relation between Marxian and input-outputcategories. It shows that U.S. employment and wage bills of unproduc-tive labor rise relative to that of productive labor in the postwar period,and develops a formal two-sector model of their effects on accumulation(1987, pp. x-xi, chaps. 4-5). Productive labor is now distinguished fromunproductive labor within the productive sectors (p. 80, n. 19), and onlythe wages of the former are counted as variable capital. The treatment oftaxes on variable capital is also improved, since only the net tax on labor(the difference between taxes paid by labor and social benefit expendituresdirected toward labor) is deducted from wages (p. 78). Finally, Wolffdistinguishes the rate of exploitation from the rate of surplus value, andintroduces a valuable method of calculating the former (p. 84). As in hisearlier work, Wolff (1977b, pp. 87-89) identifies the Marxian surplus prod-uct with Baran-Sweezy's surplus. But in contradistinction to his earlierposition, he now identifies unproductive activities as unnecessary: "thelabor power provided by unproductive workers is not essential for theproduction of any output" (p, 78).

The core of Wolff's book is his double-entry accounting framework. Butonce again, the framework he presents is symmetric between money andlabor value calculations. As in his earlier work, Wolff treats all unpro-ductive activities as part of a general royalties sector (he uses advertising


as his illustrative example), which allows him to make the two sets of ac-counts symmetric - this time on both product and revenue sides (1987,pp. 69-83). Thus his estimates of the money rate of surplus value continueto be inconsistent with his labor value measures. Interestingly enough,even though he devotes a considerable part of his book to the techniquesfor measuring the rates of exploitation and rates of surplus value, Wolffpresents no direct estimates of either (Khanjian 1988, p. 120).58 However,his estimates of both are implicit in other data that he presents, and wewill examine them shortly.

There are two other striking problems with Wolff's measurement ofthe rate of surplus value. First of all, in his calculation of the net tax onwages, he treats (the producer-price component) of all government ex-penditures as a benefit to consumers. Expenditures on defense, interna-tional affairs, space programs, and so forth are thereby treated as directconsumer benefits (1987, p. 78), which overstates the benefits received byworkers. This treatment of government spending is essentially neoclassi-cal, and is greatly at odds with the one we adopt (see Section 5.9). On theother hand, the taxes paid by workers are understated by Wolff becausehe only counts personal income taxes (net of direct transfers) but notthe portion of taxes paid for social security.59 The end result is that hismethod overstates the measure of variable capital. Other things beingequal, we would expect the estimates of the rate of surplus value in hisbook to be even lower than those in his 1977 paper. We will see that this isindeed the case.

The second problem arises in Wolff's attempt to distinguish the rateof exploitation from the rate of surplus value. He introduces a valuablemethod for calculating the average rate of exploitation of all (productiveand unproductive) workers (1987, p. 84). Using our notation, let

H = hours of all labor = Hp + Hu;

(conw)p = (column) vector of producer price components of thehourly consumption basket of the average worker;

58 Wolff (1987, p. 133) lists only estimates of "surplus" per worker, which do notprovide enough information to calculate his implicit estimates of the money orvalue rates of surplus value.

59 Wolff's rationale for leaving in social security taxes is that these taxes functionlike a pension system and eventually return to working class (1987, p. 62). But healready accounts for the reflux of such payments, since he counts (p. 63) all directtransfers to workers as an addition to wages (actually, as a reduction in net taxespaid). This is inconsistent unless social security taxes are among the taxes de-ducted from wages.


n = A* • (conw)p = unit value of labor power (necessary fractionof the average working hour);

VT = n • H = value of all labor power = V + Vu;and

H - V T 1-/1 ^ r , • •e = = = the average rate of exploitation,

VT nwhere

V = value of productive labor power = n • Hp, andVu = value of unproductive labor power = n • Hu.

Wolff's measure of the average rate of exploitation e is the ratio of totalsurplus labor time (H - VT) over the value of total labor power VT. Thisis clearly correct. As shown previously, it depends only on the consump-tion standards of the average worker for any given vector of value/priceratios. By extension, the rate of exploitation of productive workers wouldbe their surplus labor time ( H p - V ) over the value of their labor powerV. And if, as Wolff assumes, productive workers' consumption standardsare the same as those of the average worker,60 then the rate of exploitationof productive workers would be the same as that of the average worker.But the rate of exploitation of productive workers is the rate of surplusvalue. So, under Wolff's assumption of equal consumption baskets, therate of surplus value would equal the average rate of exploitation:

^ Hp-V _ Hp-(fl-Hp) = \-nC ~ V /2-Hp " n

But Wolff does not define the rate of surplus value in this manner. In-stead, he makes a surprising error. He defines surplus value as the excessof all labor time H over only the necessary labor time of productive work-ers V, so that his rate of surplus value becomes (1987, p. 83):

, = H - V = Hp + H u - V = ( H p - V ) + Hu = S Hu H^e v v v v v e v '

This measure of the rate of surplus value is peculiar in that the labortime of unproductive labor enters directly into the measure of surplusvalue. Moreover, all of this unproductive labor time Hu contributes tosurplus value, whereas only the excess of productive labor time over thevalue of productive labor power V enters into surplus value. Thus, inWolff's formulation, unproductive labor time is super-productive of sur-plus value.

6 0 Wolff assumes that productive and unproductive workers have the same con-sumption basket per worker. Compare his formulas for V and V* (Wolff 1987,pp. 82-4).


Note that if unproductive labor time enters into surplus value in thismanner, then an increase in the relative level of unproductive employ-ment can raise the rate of surplus value! Indeed, noting that H = Hp + Hu

and VT/V = H/H p , we can rewrite the expression for e' as follows:

1-HU/H- i .

Wolff derives the very same expression for the relation between hismeasure of the rate of surplus value e' and the average rate of exploita-tion e, noting in passing that the "rate of surplus value can thus increasefrom . . . an increase in the ratio of unproductive to productive employ-ment" (1987, p. 85). He does not comment on this rather extraordinaryconclusion.

It is possible to extract Wolff's labor value estimates of the average rateof exploitation e, which is really the rate of surplus value e as we woulddefine it (since he calculates e by assuming that unproductive workersconsume the same basket as productive workers). He presents data for1-rt, from which we can calculate e = (l -n)/n, which is the same ase = S/V as we would define it.61

Finally, Khanjian (1989) provides a set of consistent estimates of laborvalue and money rates of surplus value in the United States, based onthe procedures developed in Shaikh (1975). As discussed in Section 4.1,Khanjian's data clearly demonstrate that price-value deviations are smallin their effects on the measurement of the rate of surplus value: S/V dif-fers from SVV* by only 6%-9%, and the trends of the two are virtuallyidentical. This immediately implies that money value estimates of the rateof surplus value are generally excellent proxies for the underlying laborvalue rates. But Khanjian's numerical estimates are substantially largerthan ours, because he makes no adjustment for the wage equivalent ofproprietors and partners in the noncorporate sector. Such an adjustment(which we do incorporate) reduces the measure of surplus value and raisesthe measure of variable capital. This is also why our estimates are lowerthan those in Wolff, other things being equal.

Table 6.10 compares the implicit estimates of the value rate of surplusvalue in Wolff (1987) to his own earlier estimates (1977b, p. 103, table 3),to those in Khanjian (1989, table 19), and to our money rate of surplus

61 Wolff's term SVN = [N-(N-Am)]/N is what we call 1-/?, since Am is the unitvalue of the average labor power. This appears in Wolff (1987, p. 133, table 6.6,line 4).


Table 6.10. Rates of surplus value, Wolff vs. others

1947 1958 1963 1967 1972 1977

Wolff (1987): S/VWolff (1977): S/VKhanjian (1988): S/VOur estimates: SVV*

2.112.25

——

2.602.672.642.00

2.722.802.642.07

2.723.072.882.10

2.37—

2.871.99

2.27—

2.912.10

Sources: For Wolff (1987), 1 -n is from table 6.6, line 4, p. 133. For Wolff (1977),e = (l-n)/n is from table 3, line 1, p. 103. For Khanjian (1989), S/V is from table19. For our estimates, SVV* is from Appendix H.

value (Appendix H). Wolff's later estimates are smaller than his earlierones, most probably because the later estimates add a significant por-tion of government expenditures to the measure of variable capital. Wenoted earlier that Wolff adds too much here, since he counts even de-fense, international affairs, and the space program among his labor bene-fits. This is likely to inflate his estimate of V most of all during the Viet-nam era, which is probably why his estimate of the rate of surplus valuedeclines between 1967 and 1977. The other measures have already beendiscussed.

6.3 Studies based on the distinction between necessary andunnecessary labor (economic "surplus")The Marxian distinction between productive and unproductive

labor is rooted in the concept of surplus value. Capitalistically employedproduction labor is productive of surplus value. All other labor is unpro-ductive of surplus value, even though it may be engaged in petty commod-ity production, in production for direct use, or in various nonproductionactivities such as distribution and social maintenance. The dividing lineis made at surplus value simply because this is the critical fuel for capi-talist accumulation. Profit can also be generated by transfers of valueor use value between the circuit of capital and other capitalist and non-capitalist circuits. Nonetheless, the production of surplus value is the pri-mary source of profit in the capitalist mode of production.

We have taken great pains to emphasize that labor which is unpro-ductive of surplus value is not unnecessary labor. Indeed, it is only inneoclassical economics that the concept of production is subsumed underthe concept of necessity, with the market as the ultimate arbiter. Sinceneoclassical approaches deem as "productive" all activity that earns (orcould earn) a remuneration on the market, only the nonmarket sphere


can possibly harbor "unproductive" (i.e. unnecessary) activities. The state,the household, and the noncapitalist community become prime suspects.

Baran (1957) quite rightly rejects this tradition of market worship. Cap-italism creates and sustains many unnecessary activities, he insists, whichabsorb a significant portion of the economic surplus. Baran (p. 9) definesthe surplus as "the difference between society's actual current output andits actual current consumption," but Baran and Sweezy (1966, pp. 9,112)later refine it to be the difference between "total social output [and] thetotal socially necessary costs of producing it." Under monopoly capital-ism, they argue, surplus tends to grow faster than the demand for it, sothat it becomes increasingly necessary to divert the surplus into wastefulsales efforts, state and military expenditures, unnecessary expendituresgenerated by planned obsolescence, and into external outlets in the ThirdWorld (p. 341). In a more positive vein, the economic surplus can beviewed as a potential fund for socially desirable uses. Lippit (1985, p. 10)argues that the economic surplus, which is that part of national outputover and above "the essential consumption needs, public as well as pri-vate, of all of its citizens," forms a "kind of discretionary fund that thesociety may choose to utilize in a variety of ways." Stanfield (1973, p. 3)quotes Weisskopf to the effect that the economic surplus is "that part ofits productive capacity that a society has some potential freedom to allo-cate among competing alternatives."

In most discussions of the surplus, the NIPA measure of NNP is takento be an adequate measure of output. The measure of surplus thereforedepends on the definition of the "socially necessary costs" of producingthis output. And here the market is no guide, since it clearly sustainshugely wasteful expenditures. Baran and Sweezy therefore turn to someconcept of a "rational allocation" of resources as a guide to social neces-sity. Within this rubric, unproductive labor becomes that labor for which"the demand would be absent in a rationally ordered society" (Baran1957, pp. 5, 32). Unproductive labor is then socially unnecessary labor.

In the appendix to Baran and Sweezy's book, Phillips provides thefirst estimates of economic surplus. He defines this as the sum of prop-erty income, business waste, and all government expenditures (Baran andSweezy 1966, pp. 369-70). This is a rather eclectic definition, since thefirst two items are from the revenue side of NIPA accounts while the thirdis from the use side. Properly speaking, he should have included govern-ment tax revenues rather than government expenditures. Phillips alsomentions that the measure of economic surplus also ought to contain anestimate of that portion of "output which is foregone owing to the ex-istence of unemployment" (p. 370), but he does not attempt this him-self. In any case, property-type income is defined as the sum of after-tax


corporate and noncorporate profits,62 nonimputed rental payments bybusiness, business net interest payments, and corporate officers' salaries.Business waste is estimated as the sum of costs of sales and distribution,and the costs of finance, real estate, and legal services. Government ex-penditures are taken directly from national accounts, net of intragovern-ment transfers (pp. 370-84).

Phillips's economic surplus is essentially the sum of after-tax property-type income, the wage costs of unproductive activities, all taxes, plus thegovernment deficit (since government expenditures equal taxes plus thedeficit). In years where the deficit is small, as in the postwar years coveredby his data, this is basically the same as (NIPA) value added minus thewages of production workers. Thus Phillips's measure of economic sur-plus is conceptually similar to that of surplus value. We will see in Figure6.10 (to follow) that the two are quite close, empirically.

Stanfield (1973) tackles the estimation of the surplus in a much moreconsistent manner. He approaches it from the use side, as indicated inTable 6.11. He also incorporates Phillips's suggestion that the output fore-gone due to unemployment ought to be taken into account. Thus he de-fines potential surplus as potential (full employment) output minus thesum of personal and social essential consumption, whereas actual surplusis actual output minus personal and social essential consumption (Stan-field 1973, pp. 1, 81). He notes that Phillips's estimates are somewhat in-consistent, since they inexplicably "relegate all property incomes and allgovernment expenditures to the economic surplus," thus implicitly assum-ing that neither supports any necessary expenditures. His own approachassumes that property-type income is partially expended on essential cap-italist consumption, just as a part of government expenditure representsessential public consumption (p. 86). By itself, this makes his measure ofeconomic surplus smaller than that of Phillips. On the other hand, hismeasure of the essential consumption of workers is much smaller thantheir actual consumption, which tends to expand his measure of economicsurplus. We will see that the net effect is to make his measure somewhatsmaller than Phillips's.

One of the peculiarities of Stanfield's methodology is that he measuresall aggregates in terms of their cost of production, not at their market

62 After-tax noncorporate profits are derived by multiplying unincorporated incomeby the corporate fraction of after-tax nonlabor income in total income originat-ing in corporations. This estimated after-tax noncorporate nonlabor income isreduced by the net interest payments of unincorporated enterprises (which showup under the net interest component of property-type income) to yield noncor-porate profits (Baran and Sweezy 1966, pp. 371-2). Total business profits are thenadjusted to take account of what Phillips argues is a systematic overstatement ofdepreciation charges in official accounts (pp. 372-8).


Table 6.11. Real surplus value and economic surplus

Year

19481949195019511952195319541955195619571958195919601961196219631964196519661967196819691970

S*

635.62632.69691.58750.05762.72789.52791.38839.91842.84859.38861.74914.62925.67948.89

1002.001040.331106.071166.701228.541263.851307.471314.441302.53

Economic surplus

Stanfield*

544.09525.49589.53669.72667.29696.75627.16689.53689.52691.01644.30708.63710.76706.58801.31808.88871.36952.87

1060.481111.851158.841189.211163.83

Phillips *

528.23568.36591.00664.79722.43747.35722.24754.98765.34798.93824.07869.12880.34926.67975.53

1011.50

(Economic

Stanfield

0.860.830.850.890.870.880.790.820.820.800.750.770.770.740.800.780.790.820.860.880.890.900.89

surplus)/S*

Phillips

0.830.900.850.890.950.950.910.900.910.930.960.950.950.980.970.97

a Stanfield's real surplus measure is based on his real actual surplus (1973, p. 81,table 7-6) and the "ratio of surplus elements in market prices to GNP" (calleds/p; p. 58, table 5-14). Since his real actual economic surplus was calculated atcost prices, the following formula, after converting 1958 dollars to 1982 dollars,was used in order to translate his surplus figures to the ones in market prices:[surplus in market prices] = [surplus in cost prices] x [1/(1 — (s/p)}].b Phillips's real surplus figures are based on his current-dollar estimates (Baranand Sweezy 1966, p. 389, table 22); they are converted to real figures by usingGNP deflators (1982 = 100).

prices. This is accomplished by estimating the proportion of "surplus ele-ments" (items that are not costs of production, such as business taxes,profits, net interest, net rents, and the wage costs of nonproduction sec-tors) in total price, and then using this to restate market-price measuresin production-cost terms.63 For instance, the market price of potential

63 From a Marxian point of view, Stanfield is valuing all commodities at their costof production c -I- v.


GNP is derived by adjusting actual GNP for fluctuations in capacity uti-lization, which is then reduced to its production-cost equivalent (1973,pp. 78-81). The market price of total essential consumption is similarlyreduced.64 It consists of the sum of two items: personal essential consump-tion, defined as the expenditure necessary to maintain the whole popula-tion at the "modest but adequate" level represented by the "City Workers'Family Budget" which he takes froqi the BLS (1973, pp. 13, 27-35); andsocial essential consumption, defined as the sum of social overheadconsumption (government administration, international affairs, civiliansafety, sanitation, postal, etc.), some essential fraction of health, educa-tion, transportation and public utilities (Stanfield 1973, pp. 39-40), andthe replacement-cost depreciation on the capital stock (pp. 22-4, 46).65

Stanfield's methodology produces measures of constant-dollar poten-tial and actual economic surplus, valued at production costs. In order tofacilitate comparisons, we have restated the constant-dollar actual eco-nomic surplus in market prices by reversing Stanfield's own procedure.Table 6.11 and Figures 6.10 and 6.11 compare the economic surplus mea-sures from Phillips and Stanfield with our measure of surplus value, all inconstant (1982) dollars. Figure 6.11 compares our real rate of surplusvalue with what might be called the real rate of economic surplus, definedas the ratio of economic surplus to essential consumption, in Stanfield'sdata. As anticipated, Phillips's measure of economic surplus is much closerto surplus value than is Stanfield's. Moreover, the Stanfield rate of eco-nomic surplus not only is half of the rate of surplus value, but also be-haves quite differently over time.

Finally, Erdos (1970) provides an eclectic variation on these themes. Hismeasure is a kind of "political" economic surplus, even though he labelsit as (redefined) surplus value. His stated intention is to modernize Marx-ian categories by making them "correspond as exactly as possible to theempirical facts of our days." But what he actually does is conflate the rateof surplus value with the rate of exploitation, and the concept of exploita-tion with the concept of oppression. From our point of view, Marxiansurplus value is the surplus labor time of productive workers, becauseonly they produce a capitalist surplus product. Some of this goes to sup-port unproductive workers. Both sets of workers are exploited, in the

64 In actual fact, Stanfield (1973) uses different adjustment factors for total outputand total essential consumption. Compare his current-dollar GNP and adjustedGNP (table 7-4) with unadjusted and adjusted total essential consumption (tables5-10 and 5-15).

65 Stanfield notes that this type of depreciation should apply only to the essentialcapital stock, but does not attempt to distinguish this portion from total depre-ciation (1973, p. 24).


2400

2200-

2000-

1800

1600

1400

1200

1000

800-

600 -

400

SunfickJ (1973)

1948 1951 1954 1957 1960 1963 1966 1969 1972 1975 1978 1981 1984 1987

Figure 6.10. Real surplus value and economic surplus (millions of 1982dollars). Source: Table 6.10.

2.60

2.00

1.40-

0.80-

0.601948 1951 1954 1957 1960 1963 1966 1969 1972 1975 1978 1981 1984 1987

Figure 6.11. Real rates of surplus value and economic surplus.Sources: Stanfield (1973); Table 6.10.


specific sense that their surplus labor time is extracted under a system inwhich they are subordinate to the rule of the capitalist class. The degreeof their exploitation is dependent on the rate of surplus labor, not on theuses to which this surplus labor is put by their employers (cf. Shaikh 1986;see also Section 2.2).

Erdos defines socially necessary costs as that part of "new value" whichis not used by the oppressing class or the oppressive part of the state appa-ratus. This covers not only production activities, but also trade and the"socially useful" portion of government activities. The rest of new valueis the portion of the product implicated in the oppression of workers(Erdos 1970, pp. 371-3). One can see the family resemblance between thispartition and that originally proposed by Baran. At the empirical level,Erdos defines new value as the (NIPA) value added in production andtrade, but not in services. Necessary costs are defined as the wages ofproduction and trade workers, net of taxes and transfers, plus one-thirdof government wages as an estimate of the socially useful portion of gov-ernment expenditures. The political surplus, which he calls "surplus val-ue," is the rest of new value. So defined, his measure of what might becalled the rate of political surplus in the United States is even smaller thanStanfield's rate of economic surplus: 53.1% in 1929, and 46.2% in 1964(Erdos 1970, p. 384).

It should be evident that the notion of economic surplus is very dif-ferent from that of surplus value. Surplus value is the excess of the totalcapitalist product over the actual capitalist costs of its production. It isspecific to the capitalist mode of production, and is the foundation forcapitalist profitability. It supports investment and capitalist consumption,as well as various forms of social consumption arising from circulationand state activities. Whether or not these activities might be necessaryunder some "rationally ordered" society, they are largely necessary in cap-italist society. The economic surplus, on the other hand, is the differencebetween the total product and some "normative judgement of what costsare socially necessary" (Bottomore 1983, p. 340). In principle, this is aconcept applicable to any mode of production. But this is precisely itsweakness, because it abstracts from the historically specific forces thatgenerate not only the output but also the various uses of this output. Totreat the economic surplus as a "kind of discretionary fund" which maybe "allocated among competing alternatives" (Lippit 1985, p. 10; Stan-field 1973, p. 3) is to imagine that any significant re-allocation can beaccomplished without threatening the system which generates this sur-plus. If it is recognized that a social revolution is required for a new kindof discretionary use, then the surplus itself, not just its current uses, will


be significantly altered. Instead of an ahistorical concept such as the eco-nomic surplus, we need concepts of the surplus product specific to eachmode of production under study. Surplus value is just such a concept forthe capitalist mode of production.66

6 6 A concrete social formation will generally encompass some noncapitalist activi-ties. Their products, and any surplus products, must be addressed separately,even if in the end they interact with or enter into the circuit of capital (see Sec-tion 2.4).

Summary and conclusions

National economic accounts provide the empirical foundation for eco-nomic theory and policy. And at the core of all national accounts lie theproduction accounts, for it is the production of new wealth which hasbeen, at least so far, the real foundation of modern economic success.

The classical economists were deeply concerned with the factors thataccounted for the economic success or failure of nations. Their analy-sis of the structure of production led them to the recognition that notall activities resulted in a product. On the contrary, they classified cer-tain activities - such as wholesale/retail trade, military and police, andadministration - as forms of social consumption rather than of produc-tion. It followed from this that one had to distinguish between produc-tion and nonproduction labor. As we have emphasized throughout, sucha distinction does not imply that one of the forms of labor is more neces-sary, more meritorious, or more politically correct. Nor, in spite of AdamSmith, does it imply that services cannot be production activities. Thebasic distinction arises from the difference between outcome and output;not all outcomes are outputs. We noted in Chapters 1 and 2 that one wayto formalize the difference would be in terms of a vector of characteristicsassociated with each commodity, some of which would affect its status asan object of social use, and others its status as an object of distribution,et cetera. This would be an adaptation of the approach proposed by Lan-caster (1968) within the structure of neoclassical economics. Needless tosay, our approach would still differ in substance from a neoclassical one.

To the extent that nonproduction outcomes require the performanceof labor and the consumption of use values, they are, like personal con-sumption itself, forms of social consumption. Marx takes the argumenteven further. To him, the growth of capitalist economies is fueled byprofit. Profit in turn depends on two sources, profit on alienation and

210

Summary and conclusions 211

surplus value, and the latter is the dominant one in industrial capitalism.For this reason, he refined and made concrete the distinction between pro-duction and nonproduction activities. Moreover, within each type of labor,he distinguished sharply between noncapitalist and capitalist activities.It is only capitalist production labor which is surplus-value-producinglabor, productive labor for capital. Other labors are then unproductiveof surplus value, though they may be productive of value or productiveof direct-use value (if they are production labors), or forms of social con-sumption (if they are nonproduction labors).

7.1 Surplus value, profit, and growthThe classical economists recognized that the portion of the net

product which is plowed back into production is crucial in determiningthe rate of growth of the system. It follows that the division of the netproduct between consumption and investment is of the utmost impor-tance. Once one recognizes that some labor activities are really forms ofsocial consumption, it becomes evident that not all increases in employ-ment have the same effects on growth. Increases in any type of labor giverise to an increased demand for inputs to be used alongside of it and anincreased demand for consumption goods to be consumed by it. How-ever, whereas an increase in production labor also gives rise to an in-creased total product, which recovers not only a portion equivalent tothe increased demand for materials and wage goods but also a surplusproduct over and above that, an increase in nonproduction labor has nosuch effect.

Malthus saw in this a saving grace. On the assumption that capitalismsuffered from a chronic lack of demand, the fact that nonproduction em-ployment generated demand without generating supply implied that anincrease in such employment might help "pump up" the system. BothKeynesian and Kaleckian economics picked up this theme, albeit on adifferent footing (Shaikh 1980b). Ricardo, on the other hand, did not sub-scribe to the notion of a chronic demand deficiency. To him, increases innonproduction activities tended to diminish the proportion of the sur-plus product available for investment, and hence to decrease the rate ofgrowth (Coontz 1965, p. 35).

Marx does not fall into either camp. Like Malthus, Keynes, and Kalecki,Marx insists that capitalism is always capable of increasing the level ofits output, and hence the mass of surplus value, in the face of an in-crease in effective demand. But like Ricardo, Marx conducts his analy-sis in terms of a growing economy. Moreover, within his framework, ifthe proportion of unproductive employment happens to rise relative toproductive employment, then - even though the short-term effect can be


stimulatory - the long-term effect on the rate of profit and rate of growthcan be deleterious.1

The problem can be posed much more precisely by elaborating uponthe division of surplus value, and upon the corresponding allocation ofthe surplus product. To illustrate the issues involved, it is sufficient toconsider the simple case in which there are only production, trade, andgovernment activities (as in Section 3.2.B, Table 3.8). Then2

S* = pn + T + Eu = surplus value (1)and

SP* = In + CONC + G + Eu

= value of surplus product (equal in magnitude to surplus value S*),

(2)where

Pn = profit-type income (P+), net of profit (Tp) and indirect businesstaxes (IBT);

T = Tp 4- IBT = profit taxes + indirect business taxes;In = net investment

CONC = capitalist consumption;Wt = wages of the trade sector = CONWt

= consumption of trade workers;Mt = materials costs of the trade sector

= materials use in the trade sector;Eu = Mt + Wt = expenses of the unproductive sector (trade)

= Ut + CONWt = inputs and wage goods absorbed by theunproductive sector (trade); and

G = government nonproduction use of products and (viagovernment employment) of wage goods.

Equation (1) tells us that aggregate profit on production is that portionof surplus value which remains after taxes and unproductive expensesare deducted, while equation (2) tells us that aggregate investment is thatportion of the surplus product which is not absorbed by capitalist per-sonal consumption, government nonproduction activities, and capitalistnonproduction activities.

1 Shaikh (1989) develops a general Marxian model of effective demand in a growthcontext. He shows that a rise in the exogenously given average propensity to con-sume c stimulates a jump in the level of production (this is the short-term demandeffect of a relative rise in consumption), while it also sets into motion a decline inthe growth rate (this is the long-term growth effect of a decline in the savings rate).

2 From Table 3.8, S* = P + IBT + (W, + Mt), where P = profits net of indirect busi-ness tax IBT but gross of direct profit taxes. If we define the latter as TP, profitsnet of that as Pn, T = TP + IBT, and Eu = (Wt + Mt), then S* = Pn + TP + Eu.


If we now divide equation (1) through by the utilized stock of capitalK*«u, we find that the NIPA-based capacity utilization-adjusted net rateof profit r'n equals the similarly adjusted Marxian rate of profit r*' multi-plied by the proportion of surplus value not going to business taxes (t)and to unproductive expenses (eu):

)] = ( l - t - e u ) r * ' = (l-b)r*', (3)

wherer*' = S*/(K*-u);r; = Pn/(K*.u);t = T/S*;

eu = Eu/S*; andb = t + eu.

Marx and the classical economists were concerned with the long-runtendencies of the system under conditions of normal accumulation (i.e.,when capacity utilization fluctuated around a normal level).3 At normalcapacity utilization, the Marxian rate of profit is determined by the rateof surplus value and the value composition of capital. Thus the causationin equation (3) runs from r*' to r . It follows that the observed net rate ofprofit r'n will fall relative to the Marxian general rate r*' when a greaterproportion of surplus value is absorbed in business taxes or unproductiveexpenses. For this reason we label b the social burden rate.4

If we divide equation (2) through by K* and note that SP* = S*, wefind that the actual rate of accumulation capital gK = In/K* equals theMarxian rate of profit multiplied by the product of the social savings rates' (= 1 — c') and the capacity utilization rate u. Although gK is a ratio ofcurrent-dollar values, it may also be thought of as a ratio of constant-dollar values in which both In and K* are deflated by the same priceindex. Note that the social consumption rate c' represents the propor-tion of the surplus product which goes to capitalist personal consumptionand unproductive (government- and trade-sector) use. We then find thatthe observed rate of accumulation will fall relative to the Marxian profitrate when a greater portion of surplus product is absorbed in personal orsocial consumption. We have:

gK = ( l - c c -gov-e u ) (S* /K*) = (l-c /)-u.r*'=s / .u.r*', (4)

3 The path of accumulation at normal capacity utilization is similar to what Har-rod (1939, p. 16) calls the "warranted" path. In Marx, this is perfectly consistentwith a persistent level of unemployment (see e.g. Goodwin 1967).

4 We can also combine equations (1) and (2) to obtain the familiar Kaleckian re-lation Pn = CONC + In + ( G - T ) , in which unproductive expenses Eu appear tohave no role. But this is an illusion. The relation of (Pn + T) to S*, and of(CONC + In + G) to SP*, is mediated precisely by Eu.


wherecc = CONC/S*;

gov = G/S*;c / = c c + gov + eu; ands'=l-c\

The general rate of profit r*' is the common (and principal) determi-nant of both r'n and gK. We saw in Section 5.5 that we can decomposeits movements into those arising from the rate of surplus value S*/V*and the value composition of capital C*/V* (adjusted for variations incapacity utilization so as to bring out the structural, as opposed to cy-clical, pattern). We then found that the data partition into two majorphases. From 1948 to 1980, the rate of surplus value rises modestly byroughly 22%, while the adjusted value composition rises by over 77%(and the adjusted materialized composition C*/(V* + S*) rises by over56%). The rising value composition overwhelms the rising rate of surplusvalue, so that the adjusted Marxian rate of profit falls by almost a thirdover this period. This is striking empirical support for Marx's theory ofthe falling rate of profit. More detailed analysis is presented in Shaikh(1987, 1992b).

The second period, from 1980 to 1989, spans the Reagan-Bush era, dur-ing which the capitalist class and the state collaborated in attacking work-ers' living standards and labor conditions. The rise in the rate of surplusaccelerates in this period, more than doubling its trend rate. Moreover,the growth in the value and materialized compositions decelerate in thisperiod, because the low rate of profit and slow accumulation inhibit theadoption of new, more capital-intensive technologies. The overall effectis to modestly reverse the fall in the general rate of profit, recoveringabout 8% of its initial value (see Table 5.8 and Figures 5.16 and 5.17).

We saw previously that the ratio of unproductive activities rises sharplyover the postwar period (Section 5.3, Figure 5.11). Figure 7.1 shows thecorresponding rise of 16% in the social burden rate over the postwar pe-riod. Figure 7.2 shows that, as a result, the (net of profit taxes) NIPA-based rate of profit rn falls substantially faster than the Marxian rate:5

while the Marxian rate falls by 25%, the NIPA-based rate falls by 39%.Figure 7.1 also plots the path of the social consumption rate c', the

social savings rate s'= 1 — c\ and the adjusted savings rate s'-u. We seethat c', s', and even s'-u are quite stable over the postwar period. Thus, asFigure 7.2 shows, the actual rate of accumulation follows the path of the

5 From equation (3), rn/r* = P/S* = (1 - b ) . Because the actual correspondence be-tween surplus value and profit-type income is more complex than that illustratedin equation (1) (see Section 3.6, Table 3.12), the actual data for Pn are derived bysubtracting total employee compensation, profit taxes, and indirect business taxesfrom NNP, as shown in Table H.I.


1.00

r

0 . 0 0 ' i i i i i i i i i i i i i i i i i i i i i i i i i i1948 19S3 19S8 1963 1968 1973 1978 1983 1988

Figure 7.1. Social burden, consumption, and savings rates.Note: b = l-(Pn/S*), c'=l-(I*/S*), s'=l-c'. Source: Table 7.1.

0.60

0.20-

0.00 ' t i |1948 1953 1958 1963 1968 1973 1978 1983

Figure 7.2. Profit and growth rates.Note: r*'=SVK*u, r; = Pn/K*u, gK = I*/K*. Source: Table 7.1.

1988


Marxian general rate of profit.6 (Data for Figures 7.1 and 7.2 are fromTable 7.1.) This serves to emphasize that the social savings rate s' is de-pendent not merely on the decisions of firm and households to save, asorthodox theory would have it, but also on the decisions of firms andgovernments to engage in nonproduction activities.

7.2 Marxian and conventional national accountsThe distinction between productive and unproductive labor has

other implications as well. We saw in Chapter 2 that the standard of livingof workers can be decomposed into a valorized portion, comprised ofcommodities, and a nonvalorized portion, comprised of direct-use values.Marx focuses on the former, since it is the portion that has to be pur-chased by workers which in turn regulates the price capitalists must payfor labor power. It is for this reason that Marx defines the value of laborpower as the value of the commodities that enter into the workers' stan-dard of living. But the nonvalorized portion of workers' standard of liv-ing is the product of some combination of household labor, village labor,and farm labor. And although this portion is of no direct moment tocapitalists, since they do not have to pay for it, it can nonetheless becrucial to workers. Thus it is entirely possible for workers to becomemore expensive to capitalists (if the value of their valorized portion rises)while still becoming poorer overall (if their overall standard of livingfalls); see Section 2.2.

The classical and Marxian frameworks make a distinction between profitarising from the production of a capitalistic surplus (profit on surplusvalue) and that arising from transfers of wealth and value (profit on alien-ation); aggregate profit encompasses both (Section 2.4). A striking exampleof this is provided in Chapter 3, where it is shown that aggregate profit-type income can exceed aggregate surplus value even within the confinesof a single capitalist economy (Section 3.2.2). Something of this sort isalso involved in the famous puzzles generated by the so-called transfor-mation problem (Shaikh 1984, 1992). A lesson here is that even unpro-ductive labor may increase aggregate profit (but not aggregate value), tothe extent that it is able to effect a transfer into the circuit of capital froma noncapital circuit or noncapitalist sphere of activity.

In all of these instances, the central point has been that it is insufficientto view unproductive labor merely as labor which is unproductive of sur-plus value. Each type of unproductive labor has its own effects and placein reproduction. Indeed, it is precisely this recognition which orthodoxeconomics turns into a justification for the notion that all necessary labor

6 From equation (4), gK/r* = I/S* = 1 - c ' = s'.

Table 7.1. Profit, accumulation, social savings, and burden rates

Sources Variables 1948 1949 1950 1951 1952 1953 1954 1955 1956 1957

b = 1 - (Pn /S*) = social burden rateTable 5.8 Pn = profit-type income net of all taxes

S*

c' = 1 - (I*/SP*) = social consumption rateTable D.I 11- IG* - Dp - Dr'y - D,', = net investment

SP*

s'«uTable 5.8 u=capacity utilization rate

r*' = profit rate adjusted for utilization = r*/u

Table 5.8 r,; = rn/u

gK = (IJ/K*) = rate of accumulationBEA (1987, p. 190) K* = KBEA = fixed nonresidential gross private capital

(billions of dollars)

0.5666.51

149.94

0.7833.24

149.91

0.22

0.17•6.15

0.52

0.5664.90

148.64

0.8522.57

148.58

0.15

0.110.70

0.53

0.5967.78

165.26

0.7639.28

165.09

0.24

0.190.78

0.48

0.5976.71

188.25

0.7841.98

188.26

0.22

0.180.81

0.49

0.5979.05

194.51

0.8333.65

194.79

0.17

0.140.79

0.49

0.6180.28

204.52

0.8433.47

204.29

0.16

0.140.84

0.46

0.6083.43

208.20

0.8432.29

208.23

0.16

0.120.80

0.48

0.6091.29

228.55

0.8045.36

228.16

0.20

0.170.85

0.46

0.6388.36

236.97

0.8046.27

236.74

0.20

0.160.84

0.43

0.6393.24

250.25

0.8342.87

249.88

0.17

0.140.81

0.45

0.23 0.23 0.20 0.20 0.20 0.18 0.19 0.18 0.16 0.17

0.086 0.056 0.090 0.087 0.066 0.064 0.059 0.077 0.071 0.062384.30 400.20 438.70 480.80 506.20 526.60 546.20 591.20 650.30 689.70

J2 Table 7.1 (cont.)00

Variables

bPnS*

c'I!SP*

s'

s'*uu

r*'

KgKK*

1958

0.6296.54

256.15

0.8634.89

256.04

0.14

0.100.77

0.47

0.18

0.049710.90

1959

0.62104.46278.42

0.8249.44

278.34

0.18

0.150.84

0.45

0.17

0.067738.00

1960

0.64104.04286.46

0.8446.74

285.93

0.16

0.140.84

0.45

0.16

0.062755.70

1961

0.63109.64296.54

0.8545.31

295.95

0.15

0.130.83

0.46

0.17

0.058775.40

1962

0.62122.08320.20

0.8354.09

319.54

0.17

0.150.87

0.46

0.18

0.067802.30

1963

0.62129.08337.71

0.8358.27

337.07

0.17

0.150.90

0.45

0.17

0.070832.00

1964

0.62138.11364.54

0.8363.05

364.00

0.17

0.160.93

0.45

0.17

0.072872.30

1965

0.61154.28395.00

0.8077.12

394.44

0.20

0.190.98

0.43

0.17

0.083932.30

1966

0.61167.85430.65

0.8086.75

430.09

0.20

0.201.01

0.42

0.16

0.0861014.40

1967

0.63170.38454.40

0.8282.29

453.42

0.18

0.180.99

0.42

0.16

0.0751093.00

1968

0.64175.58493.63

0.8289.23

493.12

0.18

0.180.99

0.41

0.15

0.0741202.50

1969

0.66177.83523.83

0.81100.75523.25

0.19

0.190.99

0.40

0.14

0.0761320.90

1970

0.67179.61547.67

0.8393.49

546.86

0.17

0.150.90

0.42

0.14

0.0641453.40

1971

0.66204.43596.70

0.81112.14596.04

0.19

0.170.88

0.42

0.15

0.0701598.90

1972

0.65225.26645.98

0.79134.63645.51

0.21

0.190.93

0.40

0.14

0.0771737.70

1973

0.64258.07719.75

0.78160.10719.63

0.22

0.210.%

0.39

0.14

0.0831940.30

Variables

bPn

s*c'I*SP*s'

s'«uu

r*'

fn

gKK*

1974

0.66263.02778.25

0.80152.30778.82

0.20

0.180.90

0.36

0.12

0.0642387.10

1975

0.66297.02867.02

0.86120.41868.78

0.14

0.110.79

0.41

0.14

0.0452661.70

1976

0.66329.95968.82

0.83163.83971.25

0.17

0.140.83

0.40

0.14

0.0562920.80

1977

0.65373.881083.13

0.80212.851086.66

0.20

0.170.87

0.38

0.13

0.0653253.50

1978

0.65429.271221.07

0.78268.031221.76

0.22

0.200.89

0.36

0.13

0.0713774.60

1979

0.65474.301346.24

0.79288.231347.44

0.21

0.190.89

0.36

0.13

0.0684225.20

1980

0.66493.081462.70

0.83254.391463.67

0.17

0.150.85

0.36

0.12

0.0534884.40

1981

0.66566.991668.19

0.81323.441669.40

0.19

0.160.84

0.36

0.12

0.0595503.70

1982

0.68556.291724.68

0.86249.111726.06

0.14

0.110.77

0.38

0.12

0.0435859.20

1983

0.66631.101865.80

0.84290.231867.15

0.16

0.130.84

0.36

0.12

0.0486094.71

1984

0.65739.48

2101.78

0.80429.232103.70

0.20

0.180.89

0.37

0.13

0.0676432.91

1985

0.65783.75

2258.68

0.83392.53

2258.31

0.17

0.160.89

0.38

0.13

0.0596706.44

1986

0.66808.30

2401.11

0.83398.85

2389.25

0.17

0.140.85

0.40

0.14

0.0577056.52

1987

0.67847.30

2563.38

0.83422.292555.52

0.17

0.140.87

0.39

0.13

0.0577459.32

1988

0.66932.80

2752.81

0.84441.912755.18

0.16

0.140.90

0.39

0.13

0.0567895.58

1989

0.651021.302943.35

0.85447.632945.32

0.15

0.140.89

0.39

0.14

0.0538387.49

toCo


(necessity being equivalent to marketability) is productive. But here theargument veers too far in the opposite direction, since it obliterates alldistinction between capitalist and noncapitalist production, and betweenproduction and social consumption (Section 2.3). The whole purpose ofthis book has been to show that the middle road is truly different, boththeoretically and empirically.

The precise mapping between orthodox categories and Marxian onesraises a host of other issues. The primary sectors, production and trade,are directly involved in the production and circulation of the total product.As such, their combined revenue represents the total price of the totalproduct. But the value which is realized in the primary sectors is partiallyrecirculated through a series of transfers between it and various secondarysectors, involving payments of net interest, finance charges, ground rent,fees, royalties, and taxes. The sectors receiving these were grouped intothe (private) royalties sector (finance, insurance, ground rent, etc.), andthe general government sector (government enterprises are treated as partof other sectors, according to the activity in which they engage).

Since the original sources of the revenues of the secondary sectors arealready counted in the revenues of the primary sectors, we cannot countthem again in the measure of the total product and its total value. Secon-dary flows are part of total transactions, but not part of value of the totalproduct. Within IO accounts, this means leaving out the columns androws of both the (private) royalties sectors and the "government industry"dummy sector. These adjustments ultimately account for the major dif-ferences between Marxian and conventional categories.

It should be noted that such exclusions do not mean that we ignore theactual use of the product by the royalties sector or the actual consumptionof its workers and capitalists. Royalties payments are deductions fromthe purchasing power of the primary sector and its associated households;their receipt by the secondary sector enhances purchasing power and thatof its associated households. What the former set loses, the latter gains.In this way the redistribution of value brought about through transfersbetween the primary and secondary sectors leads to a changed use of theproduct. Thus the product use induced by the royalties sector shows upin the intermediate use of the total product, in the government-use por-tion of final demand, and in its workers' and capitalists' portion of thepersonal consumption column of final demand (Section 3.6, Figure 3.11,Table 3.12).

Foreign trade introduces a further instance of transfers of value, sincethe value realized within the primary sectors reflects not only the valueproduced within the country but also any (negative or positive) interna-tional transfers of value. We must therefore adjust for these transfers in


order to recover the magnitude of produced value. Our empirical mea-sures do not include such an adjustment, although we do estimate it to berelatively small for the United States (Section 3.6).

On the whole, royalties flows increase the orthodox measures of grossoutput and gross product relative to their Marxian counterparts, totalvalue and total product. But the effect on the magnitude of conventionalvalu€ added and final demand relative to Marxian value added and finalproduct turns out to be theoretically indeterminate. The same can be saidfor measures of aggregate profit-type income (the sum of profits and roy-alties) relative to aggregate surplus value (Section 3.2.1; see also Appen-dix B).

7.3 Empirical resultsAt an empirical level, Marxian total product TP* is roughly 82%

of the IO measure of gross product GP, but about 1.5 times larger thanthe conventional measure of GNP. Marxian gross final product GFP*,on the other hand, is about 15% smaller than GNP (Table 5.4). Surplusvalue S* is almost double the most inclusive measure of profit-type incomeP+ (defined as NNP minus employee compensation), while productivelabor Lp is less than one-half of all employment L. As a result, the rateof surplus value SVV* is typically almost 4 times as large as the ratio ofprofit-type income to employee compensation P+/EC, while the Marxianmeasure of productivity q* (defined as real total product per productivelabor hour) is about 3 times as large as the conventional measure (definedas real GDP per labor hour) (Section 5.12, Table 5.14).

Trends over the postwar period also differ. Marxian total product de-creases slightly relative to IO gross product, and also declines slightly rel-ative to GNP (except for 1973-77, when the oil-price rise, which shows upin the cost of intermediate inputs, temporarily reverses the trend). Marx-ian gross final product also declines moderately relative to GNP, as doesMarxian net final product relative to NNP (Figure 5.4).

Interestingly, productive employment Lp is stagnant for the first halfof the postwar period, and then begins a steady but modest rise in themid-1960s. But unproductive employment rises sharply throughout, sothat the ratio of productive labor to total employment falls by more than37% while that of unproductive labor to productive labor rises by al-most 138% (Table 5.5 and Figures 5.7, 5.9, and 5.11). A similar patternholds for total wages: the productive worker wage bill Wp (which is thesame as variable capital V*) falls relative to total wages W as the unpro-ductive wage bill Wu rises sharply relative to that of productive labor.This tells us that it is the movement in the relative employment levels,not in the relative wage rates, which is crucial. Indeed, the wage rate of


unproductive labor actually declines relative to that of productive labor,by about 12%, over the postwar period (Table 5.6 and Figures 5.8-5.11).

The Marxian measure of productivity q* is about three times as largeas the conventional measure y, and also rises relative to it for significantperiods. From 1972 to 1982, the ratio of the respective numerators of thetwo measures (i.e. TPVGDP) rises, in good part because the oil-pricerise raises the cost of the intermediate goods that appear in TP* but notin GDP. At the same time, the ratio of productive employment to totalemployment falls more rapidly than in the previous decade. Thus, eventhough the growth rate of q* slows down gradually over the whole post-war period, that of y shows a marked change in pattern in the criticalperiod 1972-82, which is then perceived as a pernicious and puzzling "pro-ductivity slowdown" (Naples 1987, p. 122). It is interesting to note, how-ever, that the trend (but not the level) of the Marxian measure is very wellcaptured by the approximation y*, defined as Marxian real net final prod-uct per productive worker hour (Figures 5.19 and 5.20).

Both surplus value S* and profit-type income P rise strongly over thepostwar period, but the former is much larger and rises somewhat faster.On the other hand variable capital V* (the productive worker wage bill)is much smaller and rises much more slowly than total employee com-pensation EC. Thus the true rate of surplus value is not only almost fourtimes as large as its naive counterpart, the profit/wage ratio P+/EC, butalso moves very differently: the rate of surplus value rises by almost 50%,while the profit/wage ratio actually falls by almost 27%. The latter givesthe impression of a "wage squeeze" on profits; the former shows just theopposite. This serves to emphasize that even the most inclusive measureof the profit/wage ratio is a bad proxy of the rate of surplus value. Asimilar comment applies for the relation between the Marxian flow mea-sure of constant to variable capital and the conventional IO measure ofintermediate input to employee compensation (Section 5.5, Table 5.7,and Figures 5.12-5.15). The ratio of fixed constant capital to variable cap-ital rises by almost 90% over the postwar period, which more than offsetsthe 50% rise in the rate of surplus value. Consequently, the Marxian rateof profit falls by 24%. The corporate rate of profit falls even faster, by57%, because a rising portion of surplus value is absorbed in unproduc-tive expenses (so that the portion remaining for profit declines relative tosurplus value).

The intervention of the state, via taxes and transfers, requires that weaccount for a different kind of transfer - out of wages, particularly thewages of productive workers. The nominal wage is altered by (positive ornegative transfers) involving net interest, net ground rent, and net taxes(net of social benefit expenditures received). Insofar as these impinge on


the wages of production workers, the measure of variable capital changes.Although the calculation of net interest and net ground-rent payments isconceptually straightforward, the estimation of net taxes paid requires acomparison between the gross taxes paid by production workers and thecorresponding transfers and other social welfare expenditures (for health,education, roads, parks, etc.) directed back toward them. To the extentthat the net transfer is positive, it reduces the measure of variable capitaland increases the measures of surplus value and the rate of surplus value.

Although we do not estimate the net interest or ground rent paid by pro-ductive workers, we do calculate the net transfer between them and thestate. For the United States, the taxes paid turn out to be generally largerthan the social benefits received - that is, there is a net tax paid by labor.This implies that true variable capital is somewhat lower, and the truemass and rate of surplus value somewhat higher, than the apparent rates(Section 5.9, Figures 5.23-5.25). Interestingly enough, even though actualgovernment purchases of the total product G* rise substantially over time,they actually decline relative to the mass of surplus value from 1955 to1989 (Section 5.8, Table 5.11 and Figure 5.21). Nonetheless, the total gov-ernment absorption of surplus value G£ = G* + WG remains fairly stable,relative to surplus value, over this same interval.

All of these mappings were constructed on the assumption that pur-chasers' prices were proportional to labor values. This allowed us to checkthat the various elements add up to the correct totals, no matter howcomplicated the transfers of value involved. It also ensured that any dis-crepancies that arose between individual Marxian categories and theirorthodox counterparts were due solely to conceptual differences, not toany price-value deviations that might exist. In Chapter 4 we extend theanalysis to the calculation of actual labor value magnitudes. We showthat the correct procedure is consistent, in the sense that it gives the sameratios in value terms and in price terms when unit purchaser prices areequal to unit values (Tables 4.1 and 4.2). This means that in actual input-output tables, where purchaser's prices generally do differ from values,we can then interpret the deviations between value and money ratios as ameasure of the aggregate effects of price-value deviations, if the pro-cedure used is consistent in the sense just described.

Using the consistent procedure, Khanjian (1989) shows that value andprice rates of surplus value differ by only small amounts (6%-9%), whichindicates that the effects of price-value deviations on aggregate measuresare quite minor (Section 5.10, Table 5.12, and Figure 5.25). On the otherhand, the procedure used by Wolff (1977b, 1987), who also attempts toconstruct a mapping between input-output accounts and Marxian cate-gories, is inconsistent and is therefore biased (Section 6.2.3). As expected


on theoretical grounds, Wolff's estimates of money rates of surplus valueare uniformly higher than his labor value estimates by about 4%-8%(Wolff 1977b, p. 103, table 3, lines 1 and 3). On the other hand, Khanji-an's estimates indicate that SVV* is uniformly lower than S/V by about6%-9% (Khanjian 1988, p. 109, table 19). This allows us to estimate thatWolff's inconsistent procedure biases the money rate of surplus valueSVV* upward by 12%-15% (the sum of the two sets of differences inyears common to both Khanjian and Wolff).

The calculation of labor-value/producer-price ratios also enables us todistinguish the rate of exploitation from the rate of surplus value. Therate of exploitation is the ratio of surplus labor time to necessary labortime. This concept applies to all capitalistically employed wage labor,whether it be productive or unproductive. Necessary labor time is simplythe value of the labor power involved - that is, the labor value of theaverage annual basket of commodities consumed per worker in the activ-ities in question. Surplus labor time is the excess of working time overnecessary labor time. For productive workers, their rate of exploitation isalso the rate of surplus value, since their surplus labor time results insurplus value. We derive expressions for both ratios, show how they areconnected, and derive a simple method of empirically estimating the rateof exploitation of unproductive workers (Section 4.2). At an empiricallevel, the two rates move in remarkably similar ways, with only small dif-ferences in levels: the rate for unproductive labor starts out lower than thatof productive labor, principally because of higher wages for the former,but the gap disappears by the mid-1970s. Both rise strongly over time,always staying within 10% of one another (Section 5.6, Figure 5.18).

7.4 Comparisons with previous studiesMuch of what has been summarized so far has strong implica-

tions for previous attempts to measure Marxian categories. We criticallyreview these attempts in Chapter 6, confining our attention to works pub-lished in English.

We see, for instance, that the rate of surplus value behaves very dif-ferently from a conventional profit/wage ratio, no matter how inclusivelythe profit measure is defined. For example, during the postwar period therate of surplus value rises by almost 50%, while the profit/wage ratioactually falls by almost 27%. The impression of a "labor squeeze" givenby the latter is therefore false. This result has direct bearing on a goodportion of the Marxian literature. In Section 6.1, we critically discussworks by Glyn and Sutcliffe (1972), Boddy and Crotty (1975), Weisskopf(1979), Aglietta (1979), Bowles et al. (1984), and Sherman (1986). All ofthem interpret some measure of the profit/wage ratio as a proxy for the


rate of surplus value, and - upon finding that the latter is falling over thepostwar period - mistakenly conclude that it must be the result of a laborforce strong enough to squeeze profits by increasing real wages fasterthan productivity (i.e., by reducing the rate of exploitation of labor), inboth the United States and the United Kingdom.

Working within an IO framework, Wolff (1975, 1977a,b, 1979, 1987)and Sharpe (1982b) also treat all labor as productive, thereby implicitlyor explicitly associating the rate of surplus value with the profit/wageratio. Thus, even though neither author draws any labor-squeeze impli-cations from his results, their money and "labor value estimates of ratesof surplus value suffer from the same basic problems just outlined.7

Many authors, though, do utilize the distinction between productiveand unproductive labor. But by far the largest portion of these do so onlyin the context of studying a particular sector - the manufacturing sector(Amsden 1981; Corey 1934; Cuneo 1978,1982; Gillman 1958; Mandel 1975;Perlo 1974; Sharpe 1982a; Varga 1928,1935,1968; Varley 1938). The avail-ability of good long-term data on manufacturing makes it a natural ob-ject of study, but it also creates two new problems. First of all, the sur-plus value realized in the manufacturing sector is much lower than thatproduced in it, because of value transferred out to the wholesale/retailsector.8 Thus the NIPA-based realized rate of surplus value in the manu-facturing sector is only about 55 % of the aggregate rate, although thetrends are quite similar. Second, and quite independently, it turns out thatthere is a substantial difference in estimates derived from census-basedmanufacturing data and corresponding NIPA-based ones, at least for theUnited States. This effect works in the opposite direction, and in this caseproduces a substantial upward bias in trend (Section 6.2.1, Table 6.3, andFigures 6.5 and 6.6). It follows that sectoral realized rates of surplus valuedo not, in general, provide good proxies for either the sectoral or aggre-gate produced rates.

Among those who do distinguish between productive and unproductivelabor, a second set of authors attempts to estimate aggregate measuresdirectly, either in money form (Eaton 1966; Gouverneur 1983; Labor Re-search Association 1948; Mage 1963; Moseley 1982, 1985; Papadimitriou1988; Shaikh 1978b; Tonak 1984; Tsaliki and Tsoulfidis 1988) or in both

7 Wolff's (1975) Puerto Rico study has, in addition, other special problems; seeSection 6.1.2.

8 Value is transferred out by the difference between producers* price and purchasers'price, and may be transferred in or out by deviations between purchasers' priceand values. In principle, the overall net transfer could go either way, but in prac-tice price-value deviations are small for any aggregate sector, so that the first setof transfers dominates.


money and value form (Izumi 1980, 1983; Khanjian 1988; Okishio 1959;Okishio and Nakatani 1985; Wolff 1977b, 1987).

Eaton's (1963) sophisticated treatment distinguishes between produc-tive and unproductive sectors, keeps track of the value transferred fromthe former to the trade sector, and even proposes that variable capital beadjusted for the net tax on labor. Mage (1963) raises the discussion to anentirely new level. He attempts to keep track of total value flows, at leastat a conceptual level, by defining it as the sum of the materials costs ofthe production sectors; variable capital (the wages of production workerswithin the productive sectors); profits; net rents paid and net interest paidof production and trade sectors; indirect business taxes paid by the pro-duction and trade sectors; and the wage and materials costs of unproduc-tive sectors. But since he relegates the latter two items to constant capital,Mage effectively reduces his measure of surplus value to just that partwhich shows up as profit-type income. This, and other more concreteconsiderations, lead to a measure of surplus value which is much lowerthan ours and which, unlike ours, falls over the postwar period.

Shaikh (1978b) provides the first systematic framework for measuringthe rate of surplus value in money form. He derives a complete mappingbetween Marxian and NIPA categories, on the revenue side of the ac-counts, and shows that the rate of surplus value rises while the profit/wageratio falls. He also provides the first systematic estimates of the net effectsof state taxation and social expenditures on the wage rate and the rate ofsurplus value. But even though his framework is essentially the same asour present one, his empirical estimates of the rate of surplus are smallerbecause (in the absence of input-output data) he is unable to estimate thesize of the intermediate inputs of the trade sector, and because of sev-eral other specific factors. Moseley (1982, 1985) and Tonak (1984) adoptShaikh's framework, but in an approximate form with some differentassumptions. Tonak also extends Shaikh's sample calculations of the nettax on labor to the entire postwar period, by developing a widely adopted"labor-share" method for splitting tax receipts and social benefit expen-ditures.9 Our present estimates are based on a further development ofTonak's work by Shaikh and Tonak (1987). Finally, Papadimitriou (1988)and Tsaliki and Tsoulfidis (1988) apply our present schema, subject todata limitations, to the case of Greece, and find that from 1960 to 1977the rate of surplus value rises (Section 6.2.2).

Aglietta takes a somewhat different tack. Because he (mistakenly) be-lieves that price-value deviations are quite significant in magnitude, he

9 The labor share method is used in studies on Canada, Australia, the United King-dom, and Sweden; see Shaikh and Tonak (forthcoming).


concludes that the money rate of profit is not likely to be a good indicatorof the trend of the value rate. He therefore derives an alternate proxy forthis latter rate, in the form of "real social wage cost" of productive labor(the ratio of the real wage of production workers to the real net valueadded per unit productive labor). Although this method of approxima-tion is a valid one, it is of course dependent on having adequate measuresof real production workers' wages and Marxian net product per unit pro-ductive labor. The trouble is that Aglietta nowhere explains how he getshis underlying data. We find that, from 1948 to the mid-1960s, his indeximplies roughly the same long-term trend as our rate of surplus value.But shorter-term movements are not at all similar. These discrepanciesare potentially important, because Aglietta places considerable weight onexplaining the "ups and downs of accumulation" from the shorter-termmovements in the rate of surplus value (Section 6.2.2).

Okishio's (1959) pathbreaking work is the first to utilize input-outputtables to estimate the money and value rates of surplus value separately.In this initial study he treats all services as unproductive. He also inflateshis measure of productive worker consumption (and hence of variablecapital) by including within it some portion of the wages of unproductiveworkers. Both factors lead to a downward bias in his estimate of the rateof surplus value, relative to our procedures. Izumi (1980) also treats allservices as unproductive, and also makes an adjustment like Okishio's toexpand the definition of the value of labor power. Okishio and Nakatani(1985) reverse their previous assumptions by treating all services as pro-ductive, which gives them a much higher estimate of the rate of surplusvalue. Izumi (1983), on the other hand, retains his framework and extendsit to a comparison of rates of surplus value in Japan, the United States,and South Korea. By comparing his results on the United States to thoseof Khanjian (1989), we see that his procedure reduces the measured rateof surplus value by 20%-35%, but raises the trend rate slightly. Wolff(1977b, 1987) and Khanjian (1989) have already been discussed (Section6.2.3).

Finally, there is a set of measures that attempts to quantify "economicsurplus." Whereas our measure of capitalist surplus product (SP*) is theexcess of the net capitalist product over the actual capitalist costs of itsproduction, the economic surplus is the difference between the total prod-uct and some "normative judgement of what costs are socially necessary"(Bottomore 1983, p. 340). Aside from the perennial issue of the appro-priate measure of output (all the authors involved seem to treat NIPA netoutput as the appropriate measure), these two concepts serve differentbut complementary needs. It is perfectly appropriate within our frame-work, as we noted in Chapters 1 and 2, to keep track of noncapitalist


production and use of wealth. But it is not appropriate, we would argue,to conflate capitalist and noncapitalist surplus products, precisely becausethe former is the foundation for aggregate profit. Moreover, it seems tous ill-advised to treat economic surplus as a "kind of discretionary fund"to be "allocated among competing alternatives" (Lippit 1985, p. 10; Stan-field 1973, p. 3).

In any case, economic surplus is generally derived by subtracting somemeasure of essential social consumption from NNP, which assumes thatNNP itself is an adequate measure of net product. Phillips (in an appen-dix to Baran and Sweezy 1966) arrives at the economic surplus by addingtogether after-tax property-type income, the wage costs of unproductiveactivities, all taxes, and the government deficit (since government expen-ditures equal taxes plus the deficit). Because the government deficit issmall in the postwar years covered by his data, Phillips's measure amountsto the difference between (NIPA) value added and the wages of produc-tion workers, and is therefore similar to that of surplus value. Stanfield(1973) attempts to account for the surplus foregone due to unemploymentby defining potential surplus as full-employment output minus the sumof personal and social essential consumption, in contrast to actual sur-plus based on actual output (pp. 1, 81). On the whole, Phillips's measureof economic surplus is much closer to surplus value than is Stanfield's.Finally, Erdos (1970) provides an eclectic variation on these themes. Hismeasure is a kind of political economic surplus, even though he labels itas (redefined) "surplus value." His stated intention is to modernize Marx-ian categories by making them "correspond as exactly as possible to theempirical facts of our days." He defines socially necessary costs as thatpart of "new value" which is not used by the oppressing class or the op-pressive part of the state apparatus. At the empirical level, he defines newvalue as the (NIPA) value added in production and trade. Necessary costsare defined as the wages of production and trade workers, net of taxesand transfers, plus one-third of government wages (an estimate of the so-cially useful portion of government expenditures). The political surplus,which he calls surplus value, is the rest of new value. So defined, his mea-sure of the rate of political surplus in the United States is even smallerthan Stanfield's rate of economic surplus. Overall, measures of real eco-nomic surplus are somewhat lower than our corresponding measures ofreal surplus value, whereas at least Stanfield's measure of the rate of eco-nomic surplus is much smaller, and moves differently, from our measureof the rate of surplus value.

7.5 ConclusionsThe distinction between production and nonproduction activi-

ties is a fundamental one, since all branches of economics must at least


differentiate between production and personal consumption. But the clas-sical and Marxian traditions also distinguish between production and non-production labor, and hence between production and social consumption.And with this distinction comes a substantially different way of account-ing for the level and progress of the wealth of nations.

The rise of neoclassical economics all but obliterated these distinctions.Instead, all necessary labor was deemed productive, and the market wasenthroned as the ultimate arbiter of social necessity. In spite of its otherdifferences with neoclassical theory, Keynesian economics is part of thisofficial tradition. Soviet-style accounts did little to combat this hegemony;if anything, the physicalist notion embodied in the Soviet-type measureof "national material product" only served to strengthen the grip of theofficial Western concepts.

But even though it has been virtually banished from orthodox eco-nomic theory, the concept of nonproduction labor has remained a part ofpractical discourse - through the observations and comments of businessleaders, government officials, and occasionally even economists, many ofwhom have pointed to the burden of "unproductive" financial, trading,and guard activities. Moreover, as a purely practical matter, the growthof such activities has been a widely noted feature in all countries of thepostwar world.

Within orthodox national accounts, issues of this sort are a matter ofdetail, because all such activities are forms of national production. Butwithin classical and Marxian frameworks, the consideration of nonpro-duction labor changes the very nature of the accounts, the picture that wesee, and the conclusions that we draw.

In our presentation, we have concentrated on production accounts,since that is where our essential difference with conventional accountsarises. Extending our accounts to encompass other circuits would onlyfurther develop this difference, since all such extensions must build onthe core provided by the production accounts. We share with most ex-tended accounts the goals of including household and Other noncapitalistproduction activities; of keeping track of financial flows; of linking ob-served flows and the corresponding stocks; and of accounting for the de-pletion of resources. But at the same time, the core differences continueto show up even at this level. For instance, unlike orthodox extendedaccounts, we would not treat household and government durables as cap-ital goods merely because they are durable, and we would not impute afictitious flow of gross profits. Much less would we apply the same pro-cedure to accumulated "human capital" (see Section 1.3).

Finally, it is important to note that we have emphasized the effects ofunproductive activities on profitability and growth because we believe thatthese interactions are essential to an understanding of the actual workings


of the capitalist system. This is not meant to imply that growth is neces-sarily a good thing. In a world beset with environmental problems and adevastating maldistribution of income, wealth, and resource use, growth(and even maintenance of present levels of production) must be viewedwith a jaundiced eye indeed. But capitalism is nonetheless fueled by prof-itability and driven toward growth. To move beyond these imperatives itis necessary to understand how they operate, in theory and in practice. Itis our hope to contribute to this understanding by constructing a frame-work within which this dynamic, with its attendant contradictions, canbe traced and analyzed.

APPENDICES

A Methodology of the input-output database

B Operations on the real estate and finance sectors

C Summary input-output tables

D Interpolation of key input-output variables

E Annual estimates of primary variables

F Productive and unproductive labor

G Wages and variable capital

H Surplus value and profit

I Rates of exploitation of productive and unproductive workers

J Measures of productivity

K Government absorption of surplus value

L Aglietta's index of the rate of surplus value

M Mage and NIPA measures of the capitalist sector gross product

N The net transfer between workers and the state, and its impacton the rate of surplus value

231

Methodology of the input-output database

The primary database from which the condensed tables in Section 5.1and Appendix C are derived is composed of input-output tables that cor-respond to the 85-industry IO tables, in that the final versions have 82rows and 88 columns. All the input-output tables used are originally de-rived from the benchmark tables produced by the BE A (Bureau of Eco-nomic Analysis), which is part of the U.S. Department of Commerce. Inan effort to improve the compatibility of the data for different years andfrom different sources, various adjustments and modifications were car-ried out on the data series used. Most significantly, Juillard (1988) carriedout several adjustments on the input-output tables so as to have as con-sistent a methodology as possible for all the benchmark years. Severaladditional adjustments and aggregations were conducted in order to ren-der data sets from different sources more consistent. Among these, themajor adjustments were: (1) reversing the methodology of force accountconstruction used with the BEA IO tables; (2) adjusting the BLS (Bureauof Labor Statistics, Department of Labor) capital stock and depreciationmatrices for oil and gas exploration costs;1 and (3) modifying employmentand employee compensation data so as to maximize consistency withinthe adjusted IO tables for all benchmark years.

We wish to thank Michel Juillard and Ara Khanjian for their help with input-output data and methodology, and Paul Cooney for the preparation of the textof Appendix A and the calculation of the U.S. summary input-output tablesused in this study.

1 In the BEA capital stock series, oil and gas exploration costs have been includedas part of the capital stock for the petroleum refining industry. Yet these samecosts are included as intermediate inputs in the same industry of the BEA IOtables. Hence one must adjust one of the two data sets.

233


A.I Original sourcesThe Bureau of Economic Analysis of the Department of Com-

merce has successively published benchmark input-output tables for 1947,1958, 1963, 1967, 1972, and 1977 (see respectively, BEA 1970, 1965, 1969,1974,1979,1984). Table A.I lists industries and commodities for the 1972table. The 1972 BEA table consists of 85 industries with the following sixdummy industries: (1) noncomparable imports; (2) scrap; (3) governmentindustry; (4) the rest of the world; (5) the household industry; and (6) inven-tory valuation adjustment. Additional rows are for value added, which isbroken down into three components: (1) employee compensation; (2) indi-rect business taxes; and (3) property-type income and totals of intermediateinputs and total industry outputs. There are an additional nine columnsof final demand listed in Table A.I; the units are millions of 1972 dollars.

Because there were few differences between the list of industries and sec-tors at the 85-order aggregation level, only the 1972 table is included here.However, there were some changes in industrial classification, in particularfor dummy industries, so the lists of industries corresponding to this orderfor the other five years are included at the end of this appendix (see the BEApublications for individual years). In order to facilitate comparison of theoriginal BEA tables and the present database, a mapping of the sectors fromthe 1972 85-order table with those of this database is presented in Table A.I.

A.2 Modifications by Juillard (1988)The BEA tables vary with respect to the degree of detail of indus-

trial classification and with regard to the treatment of methodologicalproblems such as imports or secondary products. For the most part, anygiven methodology has been used twice: 1947 and 1958 are more or lesscomparable, so are 1963 and 1967, and lastly 1972 and 1977. The mostserious break with the past occurs with the publication of the 1972 study.Because the methodology employed for the different tables had changedover time, a number of major changes or treatments had to be employed.Juillard carried out this substantial undertaking in order to producea consistent database. Only the treatment of imports for final use of pre-vious years could not be updated to the new formula (owing to lack ofinformation), so an intermediary solution had to be chosen. The neces-sary transformations concern (1) industrial classification, (2) secondaryproducts, (3) treatment of imports, and (4) the industry "eating and drink-ing places." These specific changes are summarized next.

A.2.1 Industrial classificationThe industrial classification used in the input-output tables pub-

lished by the BEA are based upon, yet distinct from, the Standard Indus-

Methodology of the input-output database 235

Table A.I. Mapping between sectors of the original 1972 85-ordertable and the final 82 x 88IO tables

Original IO sector

1 Livestock and products2 Other agricultural products3 Forestry and fishery products4 Agricultural forestry5 Iron mining6 Nonferrous metal mining7 Coal mining8 Crude petroleum and natural gas9 Stone and clay mining

10 Chemical and fertilizers11 New construction12 Maintenance and repair construction13 Ordnance and accessories14 Food and kindred products15 Tobacco16 Fabrics, yarn, and thread mills17 Miscellaneous textile goods and floor coverings18 Apparel19 Miscellaneous fabricated textile products20 Lumber and wood products21 Wood containers22 Household furniture23 Other furniture and fixtures24 Paper and allied products25 Paperboard containers and boxes26 Printing and publishing27 Chemicals and allied products28 Plastics and synthetic materials29 Drugs, cleaning, and toilet preparations30 Paints and allied products31 Petroleum refining32 Rubber and miscellaneous plastic products33 Leather tanning and finishing34 Footwear and other leather products35 Glass and glass products36 Stone and clay products37 Primary iron and steel manufacturing38 Primary nonferrous metals manufacturing39 Metal containers40 Heating and fabricating metal products41 Screw machine products42 Other fabricated metal products43 Engines and turbines44 Farm machinery and eauioment

Final tables sectora

1 Agriculture1 Agriculture1 Agriculture1 Agriculture2345678 Construction8 Construction9

10111213141516171819202122232425262728293031323334353637383940


Table A.I (cont.)

Original IO sector

45 Construction machinery and equipment46 Materials handling machinery and equipment47 Metalworking machinery and equipment48 Special industry machinery and equipment49 General industrial machinery and equipment50 Miscellaneous machinery51 Office and computing machines52 Service industry machines53 Electric industrial equipment54 Household appliances55 Electrical wiring and lighting equipment56 Radio, TV, and communication equipment57 Electronic components and accessories58 Miscellaneous electrical machinery59 Motor vehicles and equipment60 Aircraft and parts61 Other transportation equipment62 Scientific and controlling instruments63 Optical, ophthalmic, and photographic equipment64 Miscellaneous manufacturing65 Transportation and warehousing66 Communications except broadcasting67 Radio and TV broadcasting68 Public utilities69 Wholesale and retail trade70 Finance and insurance71 Real estate and rental72 Hotels and repair places, except auto repair73 Business services74 Eating and drinking places75 Auto repair and services76 Amusements77 Medical and educational services78 Federal government enterprises79 State and local government enterprises80 Noncomparable imports81 Scrap, used, and secondhand goods82 Government industry83 Rest-of-the-World industry84 Household industry85 Inventory valuation adjustment

I Total intermediate inputsVA Value addedEC Compensation of employees

IBT Indirect business taxes


414243444546474849505152535455565758596061626364656667686965 Trade7071727374757677787980

N.I.*81

N.I.N.I.


Table A.I fcont.)

Original IO sector

PTI Property-type incomeT Total industry output

Final demand (reference is to columns)91 Personal consumption expenditure (PCE)92 Gross private fixed capital formation (INV)93 Change in business inventories (CBI)94 Exports95 Imports96 Federal government, national defense97 Federal government, nondefense98 State government, education99 State government, other

Total final demandTotal commodity output


N.I.82

818283848586 Federal government86 Federal government87 State government87 State government

N.I.88 Row totals

a Sectoral names are listed only when they differ from the names of the original sector.b N.I. = not included.

trial Classification (SIC) used for the economic census. The degree ofdetail varies with the different studies: for 1947 and 1958, the productivesystem is disaggregated into 79 industries, or a 2-digit IO classification;for 1963 and 1967, 368 industries are available, or a 4-digit IO classifica-tion; in 1972, the degree of detail reaches 496 industries, or a 6-digit IOclassification. Finally, in 1977, 537 industries are available in an updatedversion of the 6-digit IO classification. The U.S. national accountantstried as much as possible to maintain the consistency of the classificationthrough the years, so that the classification would remain compatible atthe higher aggregation levels available for several consecutive years. Forthis reason, the 2-digit IO classification remained more stable and hasintegrated the changes in the SIC classification in a consistent way.

However, the list of dummy industries, which are used to describe ac-tivities that - for conceptual or statistical reasons - cannot be assigned toany particular industry, has changed between the different studies. For the1972 table, the dummy industries include: (1) the government industry,which transfers the value added by the employees of the federal, state,or local administration to the final demand; (2) the rest-of-world in-dustry, which accounts for the income of the production factors locatedabroad; (3) the noncomparable imports industry; (4) the households in-dustry, which accounts for the compensation of household employees;


(5) the inventory valuation industry; and (6) scrap and second-hand goods,which are treated in the 1972 study as the secondary product of severalother industries. Before 1972, other secondary products were added tothe list of the dummy industries: office supply, business trips, and gifts.For 1958, research and development is also included as a dummy indus-try. The importance of the differences in the list of dummy industries islimited with regard to activities not present in the later studies as othersecondary products. Although based on the SIC, input-output studiesincorporate explicit redefinitions whose scope changes for different years.These redefinitions always attempt to yield more homogeneous industries.

A.2.2 Secondary productsThe basic statistical unit of the economic census is the establish-

ment, generally, characterized by a unique location, in contrast to a com-pany, which is based on the legal criterion of ownership. The establish-ment is assigned to the industry corresponding to its primary production.However, the establishment may have several other types of production,which are referred to as secondary products. It is in the interest of IOanalysis regarding technology to achieve the greatest possible homogeneityfor the definitions of production processes, thus ensuring the greatest sta-bility possible for the technical coefficients. For this reason, national ac-countants try to reclassify the secondary products in order to obtain morehomogeneous production processes. This reclassification of secondaryproducts can be dealt with in three different ways: (1) constant-commoditytechnology; (2) constant-industry technology; and (3) separation of theinput-output table into two tables, Use and Make.

The first case applies when the technology used for production of thesecondary product is clearly different from the technology used to pro-duce the primary product. In this case, the activity resulting in the secon-dary product is simply redefined as belonging to another industry on theassumption of constant-commodity technology; this treatment was usedin all six tables. Alternatively, the secondary product may be the objectof a fictitious sale - from the industry actually producing it to the one forwhich this product would be the primary product. This transfer methodwas used in the 1947,1958,1963, and 1967 tables in order to deal with the^classifications made under the assumption of constant-industry technol-ogy. This method has the defect of artificially increasing the share ofintermediary products in overall production, with no corresponding jus-tification on technological grounds. The third method, which was usedfor the tables of 1972 and 1977, corrects this problem by describing indus-tries and commodities separately. This method, which was inspired bythe Von Neumann model, requires the separation of the input-output


table into two tables. The first table, known as the Use table, describesthe use of the different commodities by the different industries and thefunctions of the final demand; the second, or Make, table displays theproduction of each commodity by the different branches.

In order to unify the treatment of secondary products in the six tables,this third method was also applied to the earlier tables. These operationswere carried out at the highest degree of detail possible: 79 industries for1947 and 1958, and 368 industries for 1963 and 1967. The first probleminvolves a number of specific redefinitions: from 1972 on, and contrary towhat was done before, the electricity produced and sold by the manufac-turing, mining, and railroad sectors is systematically redefined as beingproduced by the electricity industry. The same is true for the reselling ofcommodities taking place in the manufacturing sector, which is redefinedas occurring in the wholesale trade industry, and for rents and royalties,which are systematically redefined into the real estate industry (BEA1980,p. 49). In the studies before 1972, these ^classifications were dealt withby using the transfer method, therefore implying the opposite assumptionof constant-industry technology.

For published tables that report only the total transfers by industry,magnetic-tape data files are available (distributed by the BEA) that con-tain the detail of the transfers by commodity and industry. It is thereforepossible to use either of the two assumptions of constant technology. Itis important to realize that the information in the transfer table is equiva-lent to that included in the Make table. The transfers indicate the quan-tity of secondary products produced by each industry. On the other hand,a table without the transfers represents the direct allocation of primaryproducts and their use by the different industries and functions of thefinal demand; the row totals of this table represent the total productionof each commodity. By comparing these totals and the column totals ofthe transfer table, it is possible to calculate the quantity of each commod-ity which is produced as the primary product of the corresponding indus-try. This is accomplished by calculating the differences between the twosets of totals. It is therefore possible to use the transfer table to rebuildUse and Make tables for years prior to 1972, although the manipulationof the two matrices is quite complicated.

By systematically applying the assumption of constant-industry tech-nology to the secondary products described outside the main diagonalof the Make matrix, it is possible to rebuild an input-output table thatdescribes the transactions between industries. Of course, these transac-tions are made of heterogeneous commodities, since primary and secon-dary products are mixed together. To obtain such a table, it is enough topre-multiply the Use table by the column coefficients of the Make table.


However, for such a table there is no ideal solution for the treatment ofscrap and second-hand goods, even though the small amounts they repre-sent have little influence on the final results.

If these second-hand products are treated as the other secondary prod-ucts and so attributed to other industries in the proportion in which theyare produced, then they appear as input required by production, and thusany increase in the level of activity of an industry using scrap will generatean increase in the demand for scrap and second-hand goods for the input-output model. On the other hand, because the business sector resells usedcars to households and buildings to the government, the gross privateinvestment in the fixed-capital column of an input-output table has anegative amount for scrap and second-hand goods. The mechanical redis-tribution of this negative amount among the industries producing scrapand second-hand goods results in the appearance of negative amounts inseveral cells of the investment column, because those industries (such assteel) that are relatively large producers of scrap do not produce invest-ment goods. The advantage of treating scrap and second-hand goods asother secondary products is that it ensures that the balance of accountsfor each industry will be maintained. This was the method used for thefirst five tables: 1947,1958,1963,1967, and 1972.

In order to avoid generating a demand for scrap and second-hand goods,the BEA (1980) recommended an alternative method, which takes scrapand second-hand goods out of the total production of each commodity.This technique has the disadvantage of destroying the equilibrium be-tween resources and uses for each industry, and requires that an implicitadjustment be incorporated into value added. This is the method usedfor 1977 in this study. It should be stressed again that the amount of scrapand second-hand goods is at most a few percentage points of total pro-duction, and that the problem is of a more conceptual nature and lessimportant with respect to its empirical consequences.

A.2.3 ImportsThere are two categories of imports, and these are treated dif-

ferently in the IO tables: comparable imports, for which an equivalentexists domestically; and noncomparable imports, which do not have anequivalent in domestic production. The latter is treated as a dummy in-dustry, entitled noncomparable imports. This industry does not have anyinput, and the corresponding column is therefore empty. The row de-scribes the utilization of noncomparable imports by the different indus-tries and the functions of the final demand. To ensure overall balance ofthe table and to show the total amount of imports in final demand, thetotal of the noncomparable imports is entered with a negative sign at the


intersection of the noncomparable-imports row and the net-export col-umn (before 1972) or in the imports column (in 1972 and 1977). The non-comparable imports are recorded at the foreign port value, and the trans-oceanic margins are recorded in the appropriate industries. One shouldnote that if the transport (or other activity recorded as a margin) is accom-plished by a foreign carrier, it is a comparable import of services and isdealt with accordingly. The specific treatment for comparable imports de-pends on whether they are (1) intermediate inputs or (2) for final demand.

Intermediate inputs: In the BEA tables prior to 1972 (in a manner simi-lar to the treatment of secondary products), comparable imports of inter-mediary goods are added as inputs to the industry that would producethem in the United States. In the 1972 and 1977 tables, comparable im-ports of intermediary goods are separately recorded as negative entriesin a special column of the final demand reserved for imports. In this case,the imports must be valuated in a unit as close as possible to the value ofthe same commodity on the domestic market; they are therefore recordedat their value at the domestic port of entry, duty included.

The details provided for the tables prior to 1972 are sufficient to presentthe comparable imports of intermediary goods in the new methodology.Although the details of the operations necessary were not included in thewritten publication of the BEA, they were available in the magnetic-tapedata files. The comparable imports of the earlier tables must be valuatedat their domestic-entry port value by adding the transoceanic margins totheir foreign port value. These amounts are then written with a negativesign in the new column of the final demand reserved for imports. In orderto maintain the balance of accounts, the addition of transoceanic mar-gins must be compensated for by subtracting them from the industry thatproduces the margin services (transportation, wholesale trade, and insur-ance). Since the imports are recorded with a negative sign in the newpresentation, this adjustment is in fact simply an algebraic addition.

Final demand: Prior to 1972, the comparable imports of commoditiesdirectly used for final demand were directly imputed to the different func-tions of the final demand in total, and in the same row as the noncom-parable imports. In this case also, the imports are recorded at the foreignport value. It was desirable to present the comparable imports of goodsallocated to final demand in the new methodology (from 1972 on). Un-fortunately, it is not possible to know the detail of the commodity im-ported directly for final use for the tables prior to 1972. In order to makeall six tables consistent, the comparable imports were taken out of finaldemand for the 1972 and 1977 tables and placed in a separate row, as hadbeen done for the years prior to 1972. Thus, the tables from 1947 to 1967


were kept intact in this regard. The imports used for the final demand inthe 1972 study have been identified by comparing a 1972 table presentedin the old methodology (BEA 1979) with the new table. For 1977, thecomparable imports used directly for the final demand have been esti-mated on the assumption that the share of the market by imports wasconstant regardless of the destination of a given commodity - with theexception of export and government use, which have been excluded fromthe potential users of imports. This choice is justified on the basis of thecomparison of the two tables available for 1972.

A.2.4 Eating and drinking placesIn the tables from 1947 to 1967, eating and drinking places are in-

cluded in the retail trade industry; however, they are treated separately in1972 and 1977 (industry 74). If it were only a disaggregation of the indus-trial classification then there would be no problem in keeping the consis-tency between both presentations. However, the trade industry is a mar-gin industry that records only the margin added at the time of the businesstransaction. When eating and drinking places are treated as trade, thefood appears as directly sold by the food industry to the consumer (house-holds or another industry), and only the costs and the value added ofpreparing the meal are accounted for in the trade industry. In contrast,when eating and drinking places are treated separately, the food appearsas input for the eating and drinking places industry, and the output ofthis industry includes not only the costs and the value added of prepar-ing the meal but also the value of the intermediary goods. Therefore thechange in treatment results in an important change in the proportion be-tween input and value added in the input-output tables. In order to correctthis inconsistency between the different studies, the elements necessary toseparately compute eating and drinking places in the earlier studies havebeen roughly estimated between 1947 and 1967.

The first step was to determine the total output of eating and drinkingplaces. For 1947 this task was made easier with the information includedin the original version of a table published by Leontief (1951) and Evansand Hoffenberg (1952).2 The original study, although incompatible in itsmethodology with later studies, treats eating and drinking places sepa-rately. For 1958, 1963, and 1967, the figures published by the EconomicGrowth Project (BLS1979) were used. The main destination of eating anddrinking places' production is of course household consumption. Thisitem is reported in the NIPA (BEA 1986) in table 2.4, line 4. In each year

2 The 1947 table used by us is a revised version prepared by the Office of BusinessEconomics (now the BEA) in order to make it comparable to the later studies(BEA 1970).


the share of household consumption represents between 75% and 80%of the total output of the industry. For other destinations of the productit was not possible to find direct information, so the following estimationmethod has been used. Starting with the demand structure for eating anddrinking places in the 1972 study, an iterative method was employed toensure that the amount of input shown in each industry is compatiblewith the tentative level of demand for the eating and drinking places'product.

The input structure is determined in two steps. As mentioned, eatingand drinking places are treated in earlier studies as a "margin" industryintegrated with trade. It follows that basic inputs are shown directly attheir destination and that the margin is shown on the row of the tradeindustry. For each study, the amount of basic inputs used for privateconsumption expenditure is shown in a separate table that describes thebridge between the input-output classification and the detailed categoriesof the final demand (Simon 1965; BE A 1970, 1974).

In particular, these tables display the contribution of each industry forthe category of meals and beverages. If we are ready to assume that themethod of production for private consumption is the same as for otherdestinations, we can then determine the amount of inputs used by eatingand drinking places. In these tables, the quantity corresponding with traderepresents the margin added in the preparation of the meal. If eatingand drinking places are represented separately, this margin must be de-composed between material inputs and value added. This is the secondstep of the transformation. Without additional information, one mustassume that this input structure is identical to that for trade. This leadsto an unavoidable distortion: oil products are a relatively large input ofthe trade industry because of the transport also carried by this industry,while this is hardly a characteristic of eating and drinking places.

A.3 Aggregations and further modifications

A.3.1 Main aggregationThe unpublished tables provided by Juillard for 1963,1967,1972,

and 1977 had 105 rows and 116 columns, while those for 1947 and 1958had 90 rows and 99 columns. In order to have all six tables with the samenumber of rows and columns - that is, 90 x 98 (later, 87 x 98) - an aggre-gation was done for the 1963, 1967, 1972, and 1977 tables. There weresome differences in the dummy-industry and final-demand columns be-tween the tables of 1947 and 1958 as compared to the later tables. The1947 and 1958 (90 x 99) matrices had to be made consistent with those ofthe later years. Table A.2 is a mapping of the correspondence between


Table A.2. Sectoral correspondence for thedifferent IO tables0

1963-77105x116

12345678910111213141516171819202122232425262728293031323334353637383940414243

1963-7787x98

12345678910111213131415161718181920212223242526272829303132333435363738383940

1947/5890x99

12345678910111213131415161718181920212223242526272829303132333435363738383940

Final82x88

111123456788991011121314141516171819202122232425262728293031323334343536


Table A.2 (cont.)

1963-77105x116

4445464748495051525354555657585960616263646566676869707172737475767778798081828384858687

1963-7787x98

4142434445464748495051525354555657585960616263646565656565656567666869746970707071717272

1947/5890x99

4142434445464748495051525354555657585960616263646565656565656567666869746970707071717272

Final82x88

3738394041424344454647484950515253545556575859606161616161616163626465656566666667676868


Table A.2 (cont.)

1963-77105x116

888990919293949596979899100101102103104105

1963-7787x98

737375767677777778798081828384858687

Final-demand columns104105106107108109110111112113114115116

86878889909192939495969798

1947/5890x99

737375767677777778798083848586878990

89929394959697979898989899

Final82x88

696970717172727273747576777879808182

—818283848586868787878788

a A listing of the final 82 x 88 IO sectors is provided in Table A.4.

the 105 x 116 sector matrix, the 87 x 98 matrix for the years 1963-77, the90 X 99 matrix for 1947/1958, and the final 82 x 88 table. For the aggrega-tion of the 1947 and 1958 tables, the procedure was slightly more compli-cated. In particular, sector 81 (unproductive real estate) had to be com-bined with sector 71 (productive real estate) so as to have one single sectoras in the other tables.


A.3.2 Force account construction, reverse adjustmentAccording to the Definitions and Conventions of the 1972 Input-

Output Study (BEA 1980):The output of the construction industries, whether new or maintenance orrepair, includes both construction work performed on a contract basis foran industry or for a final demand sector and work achieved through theutilization of the work force of the industry or the final demand sector(e.g., government). The construction work performed by the work forceof the consuming industry or final demand sector is called force accountconstruction. The estimate of the value of force account construction foreach industry which performs such work is summed by construction type(including maintenance and repair as well as new) and added to the out-put of the appropriate construction industry. The input side of the forceaccount construction activity is made up of employee compensation andthe various materials and services necessary to perform the work. (p. 46)

Thus, in order to reverse this redistribution of construction activity, theindividual imputations for each industry had to be transferred back tothe original industries, using table C of "imputations" for each individualindustry (BEA 1980, pp. 75-7). These were redistributed back to theiroriginal rows in two steps. The first step involved only the inner 79 (inter-mediate portion) of the 85-order industries; the second step was an ad-justment for the government final-demand sectors.

The imputations of force account construction (FAC) for the federaland state final-demand columns did not affect the inner 79 x 79 matrix,but rather the final demand and value added. The imputations involvedfor the federal and state final demand were assumed to derive predomi-nantly from the compensation of government employees, and were there-fore taken from the government-industry sector. The reasoning behindthis is that the majority of this imputation is from wage payments to gov-ernment employees. Therefore, the difference between the total compen-sation of general government as listed in NIPA and that listed in the IOtables corresponds to the imputations. These amounts were then trans-ferred from the construction to the government-industry row for the fed-eral and state final-demand columns. In order to have the constructionrow and column total match, the same amount was removed from thevalue-added element of construction (11th column) and placed in the valueadded of government industry (column 82). There is a certain portionof the total imputations that does not correspond to compensation, butsince this amount seems to be rather small, there was no point in adopt-ing an unclear, ad hoc procedure to transfer it (see BEA 1980, pp. 46-7).

In order to scale up the FAC vector for 1972 to reflect changes in out-put, the following formula was used:3

3 The BEA has the actual imputations, but we were not able to obtain them.


QXXFACXX = FAC72x

Q72 '

where XX denotes a given year. In addition, the value-added elementswere similarly scaled up or down in the case of construction, in order toreflect the reverse adjustment.

After aggregating agriculture, construction, and so on, we obtained the82 x 88 tables (see Table A.2). The second step of reverse FAC involvedthe final-demand government sectors, and was carried out in conjunctionwith the adjustment (mentioned previously) for the imputed rental. Theresulting tables were the final 82 x 88 tables.

A.3.3 Real estateA significant portion of the investment column element of the

construction industry row was shifted to the personal consumption expen-diture (PCE)-column element of the construction row, since purchasesof private homes had been treated as investment in the original IO tables.In those IO tables, the real estate sector has two components: one corre-sponds to the actual real estate industry; the other is the imputed portionwhich is based upon owner-occupied dwellings. This imputed portionalso can be broken down into two parts; one is fictitious and the other isreal. The real portion was shifted to the PCE column because it is com-posed of actual purchases by private individuals for repair and mainte-nance of their own homes. At an intermediate stage, the fictitious portionwas also included in the table. However, for the final version of the IOtables used for this database, the fictitious portion was removed from thePCE element of the row for real estate and rental, as was the value-addedelement of the PCE column, thereby eliminating the fictitious elemententirely.

A.3.4 Final aggregations to produce the 82 x 88 IO tablesAs shown in Table A.2, once the 87 x 98 tables were obtained,

the six government sectors had to be merged into two sectors in order tocarry out the second step of the reverse FAC adjustment. This was neces-sary also in order for the 1947 and 1958 tables to be rendered consistentwith the other tables. The resulting tables were then 87 x 94. The mappingfor this aggregation is shown in Table A.3.

The 87 x 94 tables were then used for the first stage of the reverse FACadjustment. The next required step was the final aggregation to 82x88.This involved three steps. (1) The first four (agricultural) sectors weremerged into one sector - as Ochoa (1984) had done - since there is onlyone sector for agriculture in the capital stock vector. (2) Likewise, sectors


Table A.3. Mapping of government sectors between the87 x 94 and 87x98 IO tables

87 x 94 IO table 87 x 98 IO table

92 Federal government 92 Federal government, defense93 Federal government, nondefense

93 State government 94 State government, education95 State government, health96 State government, safety97 State government, other

94 Row total 98 Row total

11 and 12 were also merged for the same reason. (3) Finally, sector 74 (eat-ing and drinking places) was merged into sector 69 (business services,research and development), since the treatment of eating and drinkingplaces changed for tables after 1972. In addition, column 86 was removedfrom the final-demand matrix because it consisted only of zeros. Theresulting 82 x 88 sectoral listing is reproduced here as Table A.4.

A.3.5 Aggregations from 82x88 to 6x9 tablesIn order to carry out our calculations, the 82 x 88 tables had to

be further aggregated to 6 x 9 tables. The first sector of this final aggrega-tion was that of production: sectors 1-64 were summed together with sec-tors 68 and 70-75. (The choice of sectors excluded will become clear asthe other sectors are described.) The second sector, total trade, consistedof sector 65 (wholesale and retail trade) and a portion of sector 67 (realestate and rental). A certain proportion (g) of the real estate sector (asground rent) was included in the royalties sector, and the remaining por-tion (1-g) was included in the trade sector (as building rent). For thepurpose of these tables, we used g = 0.25 throughout; a more detailedderivation of g for use with annual data is given in Appendix B. The thirdsector is that of royalties, which includes sector 66 (finance and insur-ance), the respective portion (g) of sector 67 (real estate), and sector 69(business services). The fourth sector is the household industry: sector 79from the 82 x 88 table. The fifth row is the sum of sectors 80 and 81 (in-ventory valuation adjustment and v&lue added). The sixth and final rowis the totals, which is the same as row 82.

The first four columns of the 6 x 9 table are the same as the first fourrows. The fifth column is sector 81 (personal consumption expenditure).The sixth column combined columns 80, 82, and 83: inventory valuation


Table A.4. Sectoral list for the 82 x 88IO table

1 Agriculture2 Iron mining3 Nonferrous metal mining4 Coal mining5 Crude petroleum and natural gas6 Stone and clay mining7 Chemical and fertilizers8 Construction9 Ordnance and accessories

10 Food and kindred products11 Tobacco12 Fabrics, yarn, and thread mills13 Miscellaneous textile goods and floor coverings14 Apparel15 Miscellaneous fabricated textile products16 Lumber and wood products17 Wooden containers18 Household furniture19 Other furniture and fixtures20 Paper and allied products21 Paper board, containers, and boxes22 Printing and publishing23 Chemicals and allied products24 Plastic and synthetic materials25 Drugs, cleaning, and toilet preparations26 Paints and allied products27 Petroleum refining28 Rubber and miscellaneous plastic products29 Leather tanning30 Footwear and other leather products31 Glass and glass products32 Stone and clay products33 Primary iron and steel manufacturing34 Primary nonferrous metals manufacturing35 Metal containers36 Heating and fabricating metal products37 Screw machine products38 Other fabricated metal products39 Engines and turbines40 Farm machinery and equipment41 Construction machinery and equipment42 Materials handling equipment43 Metalworking machinery and equipment44 Special industry machinery and equipment45 General industry machinery and equipment46 Machine shop products47 Office and computing machines


Table A

4849505152535455565758596061626364656667686970717273747576777879808182

.4 (cont.)

Service industry machinesElectric transmission equipmentHousehold appliancesElectrical wiring and lighting equipmentRadio, TV, and communication equipmentElectronic components and accessoriesMiscellaneous electrical machineryMotor vehiclesAircraft and partsOther transportation equipmentProfessional and scientific instrumentsPhotographic and optical goodsMiscellaneous manufacturingTransportationCommunications except broadcastingRadio and TV broadcastingPublic utilitiesWholesale and retail tradeFinance and insuranceReal estate and rentalHotels and repair places, except auto repairBusiness services, research and developmentAuto repair and servicesAmusementsMedical and educational servicesFederal governmentState governmentNoncomparable importsScrapGovernment industryRest-of-the-World industryHousehold industryInventory valuation adjustmentValue addedColumn totals

Final-demand columns8182838485868788

Personal consumption expenditure (PCE)Investment (INV)Change in business inventories (CBI)ExportsImportsFederal governmentState governmentRow totals


Table A.5. Sectoral list for the 6x9 IO table

Row and sector

1 Production2 Total trade3 Royalties4 Household industry5 Value added6 Gross output

Column and sector

1 Production2 Total trade3 Royalties4 Household industry5 Consumption6 Investment7 Net imports8 Government9 Gross product

Sectors from the 82 x 88 table

Manufacturing (1-64, 68, 70-74)Trade (65), part of Real estate (67)Finance (66), part of Real estate (67, 69)Household industry (79)IVA (80), Value added (81)Column totals (82)

Sectors from the 82 x 88 table

Manufacturing (1-64, 68, 70-74)Trade (65), part of Real estate (67)Finance (66), part of Real estate (67, 69)Household industry (79)Personal consumption expenditure (81)IVA (80), INV (82), CBI (83)Exports (84), Imports (85)State government (86), Federal government (87)Row totals (88)

adjustment, investment, and change in business inventories. The seventhcolumn combined columns 84 and 85, exports and imports, and is there-fore labeled net imports. The eighth column combined sectors 86 and 87,federal and state government. The last column (as with the last row) is thetotals, the same as column 88. For the full list of sectors, see Table A.5.

B

Operations on the real estate andfinance sectors

Companion text: Section 3.1.3; Sections 5.1-5.2

A. THEORETICAL CONSIDERATIONS

B.I The real estate-and-rentals sectorThe real estate-and-rentals sector consists of three basic types of

nonproduction activities: fictitious (imputed) rentals of owner-occupiedhousing; rental and sale of land; and rentals and sales of buildings andequipment.

From our point of view, the imputed portion is quite improper. IO-NIPA accounts treat homeowners who live in their own houses as if theywere businesses renting out their homes to themselves. To accommodatesuch a treatment, they create a set of fictitious rental flows. On the reve-nue side, home maintenance expenditures of private homeowners aretreated as the input costs Mir (ir stands for "imputed rental") of this im-puted owner-occupied rental sector, to which is added a wholly fictitiousvalue added VAir (composed of fictitious wages and profits Wir + Pir). Onthe use side, all the adjustments take place within the consumption col-umn. The home maintenance expenditures from which Mir is derived areshifted from the rows corresponding to the actual commodities purchased(paint, hardware, etc.) to the real estate row, to which is also added a fic-titious purchase of real estate services of magnitude VAir (BEA 1980, p.47). In actual IO tables, the sum of these fictitious entries virtually doublesthe gross output and gross product of the real estate sector.1

1 Imputed rentals comprise almost 45% of the whole rental sector's gross outputin 1972.

253


Production

Real Estate& Rentals

Wages

Profits

VA

GO

Production Real Estate& Rentals

XX XX |

XX XX

-

xx xx*'>ir

xx xx-VAy.

xx xx-GOi,.

Gross Final Demand

CON I

XX XX

Gross Product

GP

XX

n-GPj,.

Figure B.I. Removing imputed rentals.

The whole procedure is meaningless from our point of view. We musttherefore exactly reverse the imputations just described in order to re-capture the actual flows within the real estate-and-rental sector. This re-quires two operations: In the rental-sector column, we subtract Mir fromthe intermediate inputs, and Wir and Pir from the corresponding compo-nents of value added; in the consumption column, we subtract VAir =Wir + Pir from the rental row. In principle, we should also now shift Mir

from the rental row back to the various other rows that represent the ac-tual commodities used for home maintenance. But since this would changeonly the distribution of elements in the consumption column, not theirtotal, and since the necessary detailed data are unavailable, we do notundertake this step. Figure B.I summarizes the process of restoring therental-sector flows to their actual levels.2

Once we have reduced the rental sector to its actual rental flows, weneed to separate these flows into revenues derived (1) from the rental andsale of buildings and equipment, and (2) from the rental and sale of land.The former is a trading activity, and must be merged into the trade sec-tor. The latter is a royalty payment, and belongs under private royalties.

Building and equipment rentals are activities in which the use value ofa produced good such as a building is sold piecemeal ("rented") over itseconomic lifetime. As such, it must be merged into the overall trade sec-tor. But in order to do so, its row allocations must be unbundled, in thesame way as those of wholesale/retail trade. To recall how this works,

2 Figure B.I makes it clear that the total M is reduced by Mir, and that both VAand FD are reduced by VAir; hence both GO and GP are reduced by Mir + VAir.

Operations on the real estate and finance sectors 255

Production

Bldg. & Eq.Rentals

Wages

Profits

GVA

GO

Production

-

400

200

400

660

1000

Bldg.&Eq.Rentals

-

200

400

1400

1S00

2000

Gross Final Demand

CON IG

1000

1000 400

Gross Product

GP

1000

2000

Figure B.2. Rentals in input-output accounts.

first consider the case of a computer retailer. Suppose computer manu-facturers sell $1000 worth of computers to retailers, who in turn resellthem to businesses, households, or government for a total price of $2000.If we were to record both the sale of the computers to retailers ($1000)and also their subsequent resale by the retailers to their final users ($2000),we would be double counting the same product. Input-output tables getaround this difficulty by treating the final sales as if they were composedof two distinct elements: $1000 worth of computers sold directly to busi-nesses,3 households, and so on; and $1000 worth of trading services soldto the same final users. Only the latter $1000 enters into the input-outputmeasures of the gross output and gross product of the retail sector. Thisis the so-called unbundling of the $2000 total revenue of the retail sec-tor into its $1000 pass-through costs (costs of goods resold) and its $1000gross trading margin (which includes operating expenses and gross prof-its); see Figure 3.6.

The very same treatment should be accorded to building and equip-ment rentals. But it is not, because input-output and NIPA accounts treatrentals as a production (as opposed to a trading) activity. Consider thecase of a computer rental firm. Suppose the computer producer sells thesame $1000 worth of computers to a firm which in turn rents them out(instead of reselling them, as in the previous example) to final users forrental charges totaling $2000. As shown in Figure B.2, the original sale

3 Sales to business would show up as an entry in the investment column of thecomputer industry row, since computers are durable capital goods (which is theNIPA definition of fixed capital).


Production

Bldg. & Eq.Rentals

Wages

Profits

GVA

GO

Production

-

400

200

400

600

1000

Bldg.&Eq.Rentals

-

200

400

| 40ft=1400-A |

800

1000

Gross Final Demand

CON IG

- | QolOOO-A |

1000 400

Gross Product

GP

0

2000

Figure B.3. Rentals adjusted for pass-through costs (A = 1000).

of $1000 worth of computers shows up in the production-sector columnas the sum of costs (shown here as rental sector inputs of $400) and wagesand profits. In the production-sector row, the transaction is recorded inthe investment column since rental items are basically durable goods. Atthe same time, the $2000 revenue of the rental sector would also be re-corded, as a wholly new total product emanating from this sector. Thecolumn of the rental sector would show this amount as the sum of inter-mediate inputs, wages, and gross profits, the latter encompassing twokinds of depreciation: the depreciation of buildings and equipment usedto conduct rental activities; and the amortization A of computers rentedout (which we assume to equal $1000) .4 The rental-sector row then showsthe sources of rental-sector receipts, which is interpreted here as the dis-tribution of this sector's so-called product to various users. Note that inthis treatment the pass-through cost A (the cost of goods resold) has beencounted in both gross output (in gross profit of the rental sector) andgross product (in production-sector sales to gross investment IG).5 It isprecisely this cost which we must remove if we wish to make the treat-ment of computer rentals conform to that of any other trading activity.

4 If the stock of computers being rented out is constant, then the gross purchasesof computers to be rented out ($1000) will just equal the amortization A of com-puters currently being rented out.

5 In our theoretical analysis, we generally treat depreciation as part of intermediateinputs. But in Figures B.2-B.4 it is more convenient to adopt the actual input-output convention of leaving depreciation in gross profit on the revenue side andin gross investment on the use side. This makes it easier to explain the actualempirical procedures involved in treating building and equipment rentals as atrading activity.


Production

Rentals

Wages

GrossProfits

GVA

GO

Production

200

AMp-400

200200

400

600

1000

Rentals

100

r100

400

400

800

1000

Final Demand

CON

500

CON=1000

500

IG

200

\

1=400

200

Gross Product

GP

1000

1000

Figure B.4. Rentals treated as a trading activity.

To remove the pass-through cost A, we must subtract it from rental-sector gross profits on the revenue side and from gross investment on theuse side, as illustrated in Figure B.3. Then the remaining row elementsof the rental sector must be unbundled, in this case in the ratio 1:1 (sincethat is the ratio of pass-through costs A to the gross rental margin). Fig-ure B.4 shows the final result, which is identical to that of any other trad-ing activity (cf. Figure 3.6). This process applies to the building and equip-ment rental sector as a whole. We will call this the "ABR adjustment,"where ABR m amortization of buildings and equipment rented out by thereal estate sector to others.6 It involves two steps:

(1) The annual cost ABR of buildings and equipment rented out toothers must be unbundled into production and trade compo-nents, and these subtracted from the corresponding rows of theinvestment column.7 This reduces aggregate investment, final de-mand, and gross product by the amount of ABR. At the sametime, ABR must be subtracted from the gross value added of therental sector. This reduces rental-sector value added, aggregatevalue added, and aggregate gross output by the amount of ABR.

6 In IO-NIPA accounts, the gross trading margin of the building rental sector in-cludes both the depreciation of plant and equipment used by this sector in con-ducting business and the amortization of buildings rented out by this sector toothers. Our ABR adjustment automatically removes the latter, but it takes a sep-arate empirical step to remove the former also. See Section B.3 for details.

7 In an actual IO table, any purchase of computers will be split into its producer'sprice and gross trading margin, and these will be recorded in the production andtrade rows of the relevant column.


(2) The rental-row elements should be unbundled into their pass-through cost and their rental markups, and the pass-throughcomponents shifted back to the production-sector row.

In step (2) it is useful to note that since the unbundling of the rental-rowelements (including ABR) merely redistributes given sums between theproduction and trade rows, it has no effect on the overall sum. This is for-tunate, because unbundling is generally not feasible at the IO level owingto a lack of necessary detail. Therefore, in our empirical input-outputtables of Section 5.1 and Appendix C, the building-rental component ofthe total trade sector has been neither adjusted for ABR nor unbundled.However, the ABR adjustment is carried out for the final NIPA-basedestimates in Section B.3 and Appendix E.

B.2 The royalties sector

B.2.1 Royalty payments between businessesThis section details the treatment of royalty payments made by

the production and trade sectors to a royalties sector. We begin from ourusual numerical example, where a total product of $2000 is sold for $1000by the producing sector and then resold for $2000 by the trade sector. Butnow we also suppose that a portion ($250) of what was formerly produc-tion and trade profits is paid over in the form of business royalty pay-ments (RY) to a third, royalties-receiving (ry), sector: say, $100 from pro-duction (RYp = $100) and $150 from trade (RYt = $150).

On the revenue side, this is simply a transfer of $250 of value from theprimary sector to the secondary (ry) sector, which in turn splits these re-ceipts into intermediate inputs Mry = $50, wages Wry = $100, and grossprofits Pry = $100; see Figure B.5. It also makes it clear that since the roy-alty payments already appear as payments out of the total revenues of pro-duction and trade, we cannot then also count them in their re-appearanceas the receipts of the royalties sector. This is because the payments aretransfers of value rather than purchases of use values.

Figure B.5 can be used to derive the actual use-value flows, with ourusual conventions. Total intermediate use M now includes the interme-diate inputs Mry of the royalties sector, so that M = Mp + Mt + Mry =400 + 200 -h 50 = $650. Total consumption CON = $1025 is the sum ofworkers' consumption

CON W = CON Wp -|- CON Wt + CONWry

= wp+wt+wry

= $200+$400 + $100 = $700

and capitalist consumption


Royalties SectorReceipts

M=50

1

rI

\\

\ \

S*=1400

Total Value=2000

Figure B.5. Division of value: Business royalties payments.

CONC = = !/2(Pp + Pt + Pry)

= 1/2($300 + $250 + $100) = $325;

total intended and unintended investment I = ViP = $325 also. As always,the total use adds up to $2000. Figure B.6 summarizes these use-valueflows.

Our analysis of the effect of business royalty payments on the distribu-tion of value and use value does not depend on whether businesses treatthem as costs (e.g., ground rent or banking service charges) or disburse-ments from value added (e.g., net interest paid to business, households,or government). But this indifference to the form of royalty paymentsdoes not carry over to IO tables. In either case, if the production- andtrade-sector royalty payments are made to another business sector, thereceiving sector will be recorded as a royalties-sector (ry) column in thetables, with a gross output GOry divided into input costs Mry, wages Wry,and profits Pry.

When the royalty payments are treated as costs, we must also create anew row in which to register these intermediate inputs RYp and RYt. Therow sum of these costs is the gross product GPry of the royalties sector,which is of course equal to its receipts GOry (the column sum of its costs


Figure B.6. Use of product: Business royalties payments.

Production

Trade

Royalties(A* Cuts)

Production Trade Royalties G r o s s F i n a l D e m a n d

CONWD C-CONW.

Wages

Profits

* Total Product^TP*=2000(Within Dwhed Una)

Total Value=TV*=2000(Within Solid Lines}

Figure B.7. IO accounts and Marxian categories: Business royalties pay-ments as costs.

and profits). Thus, when royalty payments are recorded as costs, they in-flate both total gross product and total gross output by an amount equalto the sum of the royalty payments. As far as input-output accounts areconcerned, the treatment is consistent and the tables balance. Figure B.7illustrates this mapping from the value and use-value flows (see FiguresB.5 and B.6) to an input-output table in which the royalty payments arerecorded as costs.

The trouble begins when business royalty payments (such as net inter-est paid) are treated as disbursements from value added. As in the pre-vious case, the receipt by the royalties sector of these payments must be


Total Product=TP*=2000(Within Dashed Lines)

Total Value=TV*=2000(Within Solid Lines)

Total GO=2250

Figure B.8. Partial IO representation of business royalties payments asdisbursements from value added.

acknowledged through the creation of a royalties column, with gross out-put GOry equal in magnitude to the sum of the royalty payments RYp andRYt. But now, because the payments themselves are recorded in the value-added row of the productive and trade sectors, there is no correspondingseparate royalties row. Thus, whereas total gross output GO has been in-flated by GOry, no such addition has been made to total gross productGP. At this point, the tables would not balance. Figure B.8 depicts thisunhappy situation.

Within the logic of orthodox economics, in which all sectors are pro-ductive, the simplest way out of this dilemma is to define all royalty pay-ments made by businesses directly to the royalties sector as costs of "prod-ucts" purchased from the royalties sector, regardless of whether or notbusinesses treat them that way. Thus (say) net interest payments made bynonfinancial businesses to the banking sector would be treated in the sameway as banking service charges. In the present case, this means shiftingRYp and RYt out of the value-added row into a newly created royaltiesrow. This is the end result of the procedure followed in mput-output ac-counts.8 The resulting table is identical to Figure B.7; Table B.I providesan algebraic summary of the results.

8 Since royalty payments are transfer payments, it would be much more appro-priate to record them in the value-added row of the production and trade col-umns; net payments would be positive entries and net receipts would be negativeentries. This means that the value-added row in the royalties-sector column wouldcontain a negative entry equal in magnitude to the sum of all the royalty paymentsby the other sectors as well as positive entries for wages and profits. Gross outputof this sector would then be zero (which is correct since it is not a production sec-tor) and its total "value added" would be negative by the amount of Mry.


Table B.I. Marxian and IO measures: Business royalties payments



= 1000+1000

VA*=TV*-C* = 1= RYp + VAp + (GOt)= RYp + VAp + (Mt + RYt + VAt)= GOry + Mt + VAp + VAt

(since RYp + RYt = GOry)= VAp + VAt + VAry + Mt + Mry

(since GO,, = M^ + Wry + Pry)= 500+650+ 200+ (200+ 50)

S* = VA*-V* = 1400= Mt + Mry

+ VAp + VAt + VAry-Wp

= r p + Pt + r^+ (Mry + Wry) + (Mt + Wt)

= 300+250 + 100+ (50+100)+ (200+400)

SVV* = 1400/200 = 700%= [(Mry + Wry)

+ (Mt + Wt) + P]/Wp

B. Use sideTP*=GPp + GPt = 2000

U* = Mp=400

FP*=TP*-U* = 1600= Mt + Mry + CON + I= 200 + 50 + 1025 + 325

NP*=CONWP = 200

SP* = FP*-NP* = 1400= Mt + Mry + CON + I-CONWp

= Mt + Mry + CONWt + CONWry

+CONC+I= 200+50+400+100+325 + 325

GO = GOP + GOt + GOry = 2250= 1000+1000+250

M = (Mp + RYp) + (Mt + RYt) + Mry

= (400+100) + (200 +150) + 50 = 900

VA = G O - M = 1350= VAp + VAt + VAry

= 500 + 650 + 200

Wp + Wt + Wry = 700200+400+100

Pp + Pt + Pry = 650300+250 + 100

P/W = 650/700 = 93%= P/(Wp + Wt + Wry)

GP = GPP + GPt + GOry = 2250= 1000+1000+250

M = 900

FD = G P - M = 135O= CON + I = 1025 + 325




Table B.I bears out our earlier analysis (Sections 3.1.2 and 3.6) of thegeneral patterns in the mapping between Marxian and IO-NIPA catego-ries. The IO measure of gross output GO = $2250 now overstates totalTV* = $2000, because the $250 transferred from the primary sectors to theroyalty sector is counted in orthodox economics as a measure of the cor-responding amount of production by the royalties sector (since orthodoxeconomics treats all sectors as production sectors).9 Similarly, intermedi-ate inputs M = 900 and total wages W = 700 overstate (respectively) con-stant capital C* = 400 and variable capital V* = 200, because the conven-tional measures encompass all labor and all inputs, not only productiveones. On the other hand, total profit P = 650 considerably understates sur-plus value S* = 1400, because the former reflects only that portion of sur-plus value which takes the form of aggregate profit, and not the portionabsorbed in the costs of unproductive capitalist activities (compare the lastexpression for S* in Table B.I with the corresponding expression for P).As a result, the orthodox measure of the profit/wage ratio P/W = 93%greatly understates the rate of surplus value SVV* = 700% (and hencegreatly understates the true rate of exploitation of productive workers).

B.2.2 Royalty payments between businesses and householdsIn addition to making (net) royalty payments directly to the roy-

alties sector, businesses also make such payments to households. Theseare recorded as disbursements from value added, since they are not costsof operations. Households in turn make (net) payments to the royaltiessector. We will treat these two phases separately.

Ignoring (for the moment) their possible impact on the true wages ofproductive workers and hence on the magnitude of surplus value, busi-ness royalty payments to households merely bring about a different dis-tribution of surplus value and surplus product. Figure B.9 makes it clearthat we pick up these royalty payments in the value-added rows of theproduction and trade sectors. Figure B.10 shows the corresponding useside.

In this particular case, the input-output tables treat the issue in thesame way as we do. That is to say, business royalty payments to house-holds are picked up in the value-added rows of the production and tradesectors, and the corresponding distribution of the product shows up inthe final-demand columns. Figure B.ll shows the IO-Marxian mapping.The general patterns here are the same as before, with the exception that

9 Royalty payments can indeed be regarded as purchases of "services." But theseservices serve to redistribute wealth, not to add to it; they are therefore distribu-tive services, not productive ones.


lYf-30

Total Valuc=2000

Figure B.9. Revenue side: Business royalties payments to households.Note: Both Pp and Pt' are net of royalties.

\* M=600

400

^ J

m

- CON-1025 -

TotalUse Value

=2000

Figure B.10. Use side: Business royalties payments to households.

in this case total gross output GO = GOp + GOt equals total value TV*,because there is (as yet) no reflux of revenue to the royalties sector andhence no royalties-sector receipts GOry to be recorded.

Payments from households to the royalties sector are a bit more com-plicated. Because business accounts register the sources of household in-come (wages, salaries, royalties paid to households, etc.), they already


Production

Trade

Wages

Royalties

Profits

VA

GO

Trade

ill*

Final Demand

CON I FD GP

1000

1000

^ Total Product^TP*a2000(Within Dashed Lines)

• Total Value=TV*=2000(Within SoUdUno)

Total GO^2250

Figure B.ll. IO accounts and Marxian categories: Business royaltiespayments to households.

Workers IncomeBefore Royalties

W=600Wp=200

Wp400 " ^

Mp=400

Pp»40Q

Capitalists IncomeBefore Royalties

P=800

Pp=400

Pt=400

Mt=200

Wf=40ft

pt=40e

Total Value^2000

Figure B.12. Revenue side: Household payments to royalties sector.

M P400 200 toe

CON=1000

CONC* * * * *

300

Totaly UseValue

= 2000

Figure B.13. Use side: Household payments to royalties sector.

include that portion of value which households transfer back to the roy-alties sector. We therefore cannot also count the total revenue GOrv ofrythe royalties sector, which is merely the receipt of this same transfer. Onthe use side, these household royalty payments do not appear at all, sincethey are transfers rather than purchases of the product. Figures B.12 andB.13 illustrate these points.


Total Product=TP*=2000(Within Dvhed Una)

Tola] Valuc^TV*=2000(Within Solid Una)

Figure B.14. IO accounts and Marxian categories: Household paymentsto royalties sector.

In keeping with their theoretical premise that all sectors are productionsectors, IO tables treat the payment of royalties by households as pur-chases of the royalties-sector product (recorded in the royalties row of theconsumption column), and treat the receipt of these payments as the mea-sure of the gross output GOry of the royalties column. From our point ofview, this is a spurious inflation of the measures of total gross output andproduct, because it double counts already recorded revenues. The Marx-ian measures of total value (outlined in bold lines) and total product (indashed lines) therefore exclude these elements, as shown in Figure B.14.

Household payments of royalties introduce a new element into our gen-eral patterns. When we were dealing only with production and trade, theMarxian measure of value added VA* was larger than the correspondingorthodox measure VA, because VA* included the intermediate input ofthe trade sector Mt as the part of surplus value absorbed in the costs oftrading (see Table 3.6). The consideration of business payments to theroyalties sector further strengthened this inequality. The business royaltypayments RYp + RYt appeared as costs in IO-NIPA accounts, which ex-cluded them from the conventional measures of value added in the pro-duction and trade sectors. These same payments re-appear as the receipts(gross output GOry) of the royalties sector, but only a portion GOry —Mry = VAry enters into the value added of the royalties sector. Mry there-fore disappears from the orthodox measure of aggregate value added.Thus, when we consider business royalty payments in addition to pro-duction and trade, VA* exceeds VA by the amdlmt of Mt plus Mry (seeTable B.I).


In the case of household royalty payments, a reverse effect operates.Since households are the ones paying the royalties, the payments them-selves do not appear as business costs and hence do not reduce the con-ventional measures of production and trade value added (whose total inthis case equals the Marxian measure VA*). But the receipt of these pay-ments is still recorded as the gross output GOry of the royalties sector, aportion VAry of which enters into the royalties-sector value added andhence into aggregate value added VA. The net effect of household royaltypayments is to increase the conventional measure of aggregate value addedrelative to its Marxian counterpart, other things being equal. A similareffect will be found for household payments to the government, to the ex-tent that the government in turn transfers some of this revenue back tothe royalties sector (through net interest payments, etc.). Thus, we cannotsay a priori which of the two measures will be larger. Indeed, the empiri-cal evidence indicates that VA exceeds VA*, so that the effect just dis-cussed is apparently strong enough to predominate. Table B.2, based onFigure B.14, illustrates this new type of pattern.

The (direct or government-mediated) reflux of household income intothe royalties sector has the further effect of raising aggregate profits rela-tive to surplus value. The reasons are the same as before: Because thehousehold payments are not business costs, they do not reduce the aggre-gate profits of the production and trade sectors; however, a part of theirreceipt by the royalties sector shows up as its profits. The net effect is toraise aggregate profits, other things being equal.

B. EMPIRICAL CONSIDERATIONS

B.3 Removing imputed rentalsIO-NIPA accounts treat homeowners who live in their own houses

as if they were businesses renting out their homes to themselves. Accord-ingly, they create a set of fictitious rental flows. On the revenue side, a fic-titious gross output GOir (ir stands for "imputed rental") is created byadding together intermediate inputs Mir (which are the estimated homemaintenance expenditures of private homeowners) and a wholly fictitiousvalue added VAir. On the use side, a fictitious gross product GPir = GOir

is added within the cell at the intersection of the real estate row and the per-sonal consumption expenditure (PCE) column (BEA 1980, p. 47, A-22).

We reverse the process just described. This means transferring the inter-mediate input Mir back into the PCE column, removing GVAir from theGVA of the real estate-and-rental sector, and removing GPir = GOir =Mir + GVAir from the real estate-and-rental row of the PCE column (seeSection A.3.3).


Table B.2. Marxian and IO measures: Household payments to theroyalties sector

Marxian


= 1000+1000

C* = Mp=400

VA* = TV*-C* = 1600= VAp + VAt + Mt

= 600+800+200

V* = Wp = 200

S* = VA*-V* = 1400= VAp + VAt + M t -W p

= 400+400+(200+400)

SVV* = 1400/200 = 700^0= [(Mt + Wt) + P]/Wp

B. Use sideTP* = GPp+GPt = 2000

U* = Mp = 400

FP*=TP*-U* = 1600= Mt + Mry + CON* + I*= 200+100 + 950+350

NP* = CONWP = 200

SP* = FP*-NP* = 1400

Input-output

< GO = GOP + GO, + GO^ = 2450= 1000+1000+450

< M = Mp + Mt + Mry = 700= 400+200+100

< VA = G O - M = 1750= VAp + VAt + VAry

=600+800+350

< W = Wp + Wt + Wry = 85O=200+400+250

> P = Pp+Pt + Pry = 900= 400+400+100

» P/W = 900/850 = 106%= P/(Wp + Wt + Wry)

< GP = GPP + GPt + GOry = 2450= 1000+1000+450

< M = 700

< FD = G P - M = 1750= CON + I = 1400+350



B.4 Splitting nonimputed rentals into GOgr and GObr

Once we have recovered the actual rental-sector flows, we needto separate them into revenues GOgr derived from royalties (ground rent,dealers' commissions, and royalty payments) and revenues GObr derivedfrom the rental and sale of buildings and equipment. No direct estimatesare available for either component. In a telephone conversation, Mary W.Hook of the BEA has indicated that the rule of thumb in residential realestate is that land accounts for roughly one-third of total revenues. Ourcalculations yield somewhat smaller estimates, in the range of 25%-30%.


In what follows, we will estimate the royalties portion GOgr in twosteps. First, we estimate the sum of dealers' commissions GOrl and directpayments of land rent and royalties GOr2. Subtracting this from the totalrental sector output GOr yields an estimate of the combined total ofground and building rents. Of this total, the ground-rent component GOr3

is estimated by using the ratio of site price to the sales prices of homes.Total rental-sector royalties GOgr then consist of the sum GOgrl -I- GOgr2 +GOgr3, and the ratio of this to total nonimputed rental-sector gross out-put GOr gives us the proportion g that we seek. The various steps are de-tailed next for 1972 (all data are in millions of dollars).

Sample calculations of GOgr=gross output of the royalties sector: Let

GOre s GOgr + GObr = 99,015= gross output of the real estate and rental sector (from

the 1972 input-output table described in Appendix A);

GOgr m GOgrl + GOgr2 + GOgr3

= estimated gross output of the ground-rent sector= 29,000 (derived in what follows).

(1) GOgrl = dealers' commissions on real estate activities. Total deal-ers' commissions are available only for 1967,1972, and 1977.10 However,the great portion of this total is available for every IO year because it isexplicitly listed in the published tables, in the real estate-and-rental rowof the investment column (the rest being merged into the real estate inter-mediate output). For instance, for 1972 total dealers' commissions were$6444.3, of which $4432 are listed in the 1972 IO table (BEA 1979). Wetherefore use this latter number, since it is available throughout; GOgrl =4,432.

(2) GOgr2 = direct payments of royalties and land rent. We begin withthe sum of farmland rental and royalty payments (as available directlyfrom NIPA) and rescale it to input-output levels, because the rental-sectorvalue added is different in NIPA and IO tables for a given year (BEA1986, table 8.06).

Farms owned by non-operator landlords u $ 2,300Royalties 1,600GO;r2 (NIPA-based) 3,900(GVAre)IO (gross value added, real estate, IO) 76,030(GVAre)NIPA (gross value added, real estate, NIPA) 59,100GOgr2 = (GO;r2)[(GVAre)IO/(GVArc)NIPA] 5,017

10 We thank Nancy Simon of the BEA for making these data available.11 This is mostly land rent, according to Mary Hook of the BEA.


(3) GOgr3 = land-rent component of total rents paid. There are no directdata for this component. However, we thank Denise McBride of the BE Afor referring us to data on the proportion of land costs in residential homesales, as shown in the following tabulation (HUD 1979, p. 133, table 27).

New Existing Allhomes homes homes

Total sale price 24,788 19,769 44,557Total site price 5,420 4,306 9,726Site/sale price 0.2187 0.2178 0.2183

This proportion g3 - between land costs and total sale price of new andexisting homes - can be taken as a proxy for the ratio of land rents to totalrents, on the assumption that building and land prices are reflections oftheir respective rental values; g3 = 0.2183. GOgr3 is then calculated as theproduct of g3 and that portion of total rental-sector revenue not previ-ously captured in GOgrl and GOgr2:

GOgr3 - g3 • (GOgr - GOgrl - GOgr2)

= 0.218 • (99,015 -5,017-4,432) = 19,551.

(4) Combining the estimates for GOgrl and GOgr2, we obtain an esti-mate for GOgr and for our splitting proportion g = GOg r/GOr e:

GOgr a GOgrl + GOgr2 + GOgr3 = $29,000;

g = GOg r /GOr e = 0.293

= estimated land-rent proportion ofreal estate sector total revenue.

The estimates of g are calculated for all input-output years. Annualvalues of g are created by interpolating between input-output benchmarkestimates, as shown in Appendix D. These are used in Appendix E in theestimation of annual series for primary variables. Table B.3 summarizesthe procedure for all IO years.

B.4 ABR adjustment for building and equipment rentalsThe aim of this adjustment is to remove the pass-through cost

ABR 3 amortization of buildings and equipment rented out by the rentalsector to others. The calculation of ABR is explained in what follows; itsuse has already been treated in Section B.I. As noted there, this adjust-ment is not applied to the input-output tables of Appendix C owing tothe lack of necessary detail in the data. However, it is applied to the final

Table B.3. Calculation of the proportion of ground rent in real estate (g), benchmark years

Sources

18x21IO tables

IO tables

806 8"80610*1 8 x 2 1 1 0 tables

HUD (1979, table 27)

Variables

g = GOgr/GOre

GOre

GOgr = GOgrl + GOgr2 + GOgr3

GOgrl =real estate commissionsGOgr2 = royalties and rents

= GOgr2 x (GVAIO /GVANIPA)GOlrz^RIii + RI^

RIfl = rental income of farm landlordsRIry = royalties

GVAI0 (real estate)GVANIPA

GOgr3 = g 3 xGOr e l

g3 = site /sale priceNew homes, sales priceNew homes, site priceExisting homes, sales priceExisting homes, site priceAll homes, sales priceAll homes, site price

GOrel = GO r c -GO g r l -GO g r 2

1947

0.27916,1674,506

882

2,1451,8001,400

40013,10811,000

1,4790.113

9,7801,092

10,7771,222

20,5572,314

13,140

1958

0.252

33,9198,5431,209

2,5182,1001,1001,000

26,62022,200

4,8160.16014,2832,223

13,1332,150

27,4164,373

30,192

1963

0.26545,67812,103

1,224

2,8582,4001,4001,000

35,61129,900

8,0210.19315,8782,978

14,3462,850

30,2245,828

41,596

1967

0.27364,28317,5732,100

3,0612,4001,4001,000

49,99739,20012,4120.21018,6113,777

15,9333,475

34,5447,252

59,122

1972

0.29399,01529,000

4,432

5,0173,9002,3001,600

76,03059,10019,5510.21824,788

5,42019,7694,306

44,5579,726

89,566

1977

0.299166,46949,81910,747

9,4967,1002,6004,500

125,04993,50029,576

0.20236,5177,335

28,5615,828

65,07813,163

146,226

a From NIPA (e.g. BEA 1986), where the first three digits denote the relevant table number and subsequent digits the line numbers within those tables.

Table B.4. Annual estimates of ABR, 1947-90

Variables

DR'DRABR

DR'DRABR

DR'*DR*ABRC

1947

2,916437

2,479

1962

6,754835

5,919

1977

26,6371,711

24,926

1948

3,261488

2,774

1963

7,033872

6,161

1978

30,2502,007

28,243

1949

3,371480

2,891

1964

7,399896

6,504

1979

35,2812,408

32,873

1950

3,558486

3,073

1965

7,864913

6,951

1980

40,8422,903

37,939

1951

4,039549

3,490

1966

8,507939

7,568

1981

46,255—

29,451

1952

4,259566

3,693

1967

9,162972

8,190

1982

50,436—

31,773

1953

4,428569

3,859

1968

10,0101,0128,998

1983

53,059—

34,278

1954

4,596559

4,037

1969

11,2801,066

10,214

1984

57,455—

36,980

1955

4,871574

4,297

1970

12,3451,113

11,232

1985

61,320—

39,895

1956

5,282632

4,650

1971

13,6831,140

12,543

1986

—43,040

1957

5,599671

4,928

1972

15,1111,151

13,960

1987

—46,434

1958

5,758673

5,085

1973

16,9711,193

15,778

1988

—50,094

1959

5,982700

5,282

1974

19,5421,348

18,194

1989

—54,044

1960

6,257742

5,515

1975

22,1281,478

20,651

1990

—58,304

1961

6,481789

5,692

1976

23,9471,547

22,400

a DR' values for the period 1986-90 were not available.b DR values for the period 1981-90 were not available.c ABR values for the period 1981-90 were obtained by extrapolating In ABR.


calculations in Appendix E. The following steps detail the calculationof ABR.

(1) The BEA capital stock data are on an owner basis, so that the cor-responding total depreciation of the nonimputed real estate sector (DR')is the depreciation of all building and equipment owned by this sector(i.e., the sum of depreciation DR of stock used by this sector and ofamortization ABR of stock rented out to other sectors). We have

DR'=DR + ABR,

and we calculate DR' as

DR' = depreciation of fixed private nonresidential capital(BEA 1987, p. 97, table A2)

+ depreciation of fixed private residential capital(BEA 1987, pp. 260-2, table A16),

where the latter depreciation is calculated as total minus federal minusstate minus owner-occupied nonfarm minus owner-occupied farm depre-ciation. For 1972:

DR' = 7,796 + (26,007 -144 - 372 -17,222 - 954)

= 15,111.

(2) To complete this calculation we need to estimate DR, which is thedepreciation of the buildings and equipment used by the real estate sectorfor its own use. This can be calculated from the BIE capital stock data,which is on a use basis, so that its depreciation corresponds to the capitalused by each sector (U.S. Bureau of Interindustrial Economics 1983). For1972, DR = 1,150.

Given DR and DR', we can calculate ABR (for 1972) as:

ABR = DR'- DR = 15,111 -1,150 = 13,961.

Recall that all data are in millions of U.S. dollars.Table B.4 shows the annual estimates of ABR from 1947 to 1987. Be-

cause estimates of DR are available only through 1980, the values of ABRwere directly calculated for 1947-80 and extrapolated for 1981-87 via alinear regression on In ABR versus time (R2 = 0.962).

Summary input-output tables

Companion text: Section 3.6; Section 4.1; Section 5.1

Published input-output tables for the postwar period cover the years1947, 1958, 1963, 1967, 1972, and 1977. The summary tables that follow(Figures C.2-C.7) were generated from the published tables in the man-ner described in Appendix A. They are designed to conform to the gen-eral theoretical schema developed in the text. Also included is a generaltable (Figure C.I) with variable names in the relevant cells. All data arein millions of dollars.

PRODUCTION

TOTAL TRADE

ROVALT.ES

SECTORS Hs

RO

GROSS VALUE AD

GROSS OUTPUT

hid Ind

DED

PRODUCTION

l> -RYp

VAp

GOp

TOT TRADE

RYtt

VAtt

GOtt

V* •

ROYALTIES

RYry

VAry

GOry

DUMMY SECTORSGovt Hsehld ROW

« VAdy •

« GOdy •

CON

XX

RYcon

llllconROWcon

GROSS F

Ig

XX

RYi

IVA

NAL DEMANDX-IM

XX

R Y x , m

ROWx-im

G

XX

RYg

Wg

ROWg

GROSS PRODUCT

GPp

GPtt

GPry

tGPdy

tTP*

!

Figure C.I. 10 Accounts and Marxian Categories: Summary mapping

274

Summary input-output tables 275

1947

PRODUCTION

TOTAL TRADE

ROYALTIES

DUMMY Govt IndSECTORS Hsehld Ind

ROW Ind

GROSS VALUE ADDED

GROSS OUTPUT

PRODUCTION

163117.4

15705.2

6183.3

145354.2

330360.1

< TV

TOT TRADE ROYALTIES

15491.2

4471.3

3040.1

45317.5

68320.1

3010.7

990.5

2726.1

11186.1

17913.4

Govt

16220.6

16220.6

DUMMY SECTORSHsehld

2348.0

2348.0

ROW

824.0

824.0

CON

110254.8

42639.6

5721.4

2348.0-718.0

160245.9

Ig

20943.1

2569.2

45.7

-1527.9

22030.1

GROSS FINAL DEMANDX-IM

8438.4

1444.6

53.3

1592.0

11528.3

G

9104.4

499.8

143.5

16220.6

-50.0

25918.3

GROSS PRODUCT

330360.0

68320.1

17913.4

16220.62348.0824.0

219722.5

655708.7

tTP*

I

Figure C.2. 1947 IO Table

1958

PRODUCTION

TOTAL TRADE

ROYALTIES


ROW Ind

GROSS VALUE ADDED

GROSS OUTPUT

PRODUCTION

274137.6

32332.9 :

16506.2

255726.9

TOT TRADE ROYALTIES

• 24792.1

7625.5

7247.4

80799.3

578703.7 120464.2

7403.5

3273.3

7785.8

28566.4

47029.0

Govt

40693.8

40693.8

DUMMY SECTORSHsehld

3503.0

3503.0

ROW

2030.0

2030.0

CON

188816.9

69783.2

14046.9

3503.0-1152.8

274997.2

Ig

36215.0

4037.5

103.7

-622.0

39734.2


-3795.6

2216.2

295.6

3489.8

2206.0

G

51134.2

1195.7

1043.3

40693.8

-307.0

93760.1

GROSS PRODUCT

578703.7

120464.2

47029.0

40693.83503.02030.0

410697.5

1203121.2

tTP*

1



1963

PRODUCTION

TOTAL TRADE

ROYALTIES


ROW Ind

GROSS VALUE ADDED

GROSS OUTPUT

PRODUCTION

345475.4

38938.8

21665.1

332739.7

TOT TRADI

28535.6

11115.7

8203.0

105645.7

578703.7 120464.2

., TV* •

ROYALTIES

10712.1

4148.0

10476.8

39965.2

47029.0

Govt

57348.8

40693.8

DUMMYHsehld

3824.0

3503.0

SECTORSROW

3259.0

2030.0

CON

242326.2

89775.2

21067.4

3824.0-1381.9

274997.2

Ig

52613.6

5429.3

119.8

-1004.0

39734.2

GROSS FINAX-IM

-2712.7

2851.4

389.3

5284.0

2206.0

- DEMANDG

61868.8

1242.5

3380.6

57348.8

-643.1

93760.1

GROSS PRODUCT

738819.0

153501.0

65302.0

57348.83824.03259.0

541779.3

1563833.1

tTP*

1


1967

PRODUCTION

TOTAL TRADE

ROYALTIES


ROW Ind

GROSS VALUE ADDED

GROSS OUTPUT

PRODUCTION

437069,2"

52309.9 .

32979.7

434291.1

956649.8

4 TV

TOT TRADE ROYALTIES

.38120.3

15497.7

12181.8

141267.3

207067.1

15252.6

6075.7

16221.7

60946.7

98496.8

Govt

85083.0

85083.0

DUMMY SECTORSHsehld

4701.0

4701.0

ROW

4517.0

4517.0

CON

119316.8

31125.4

4701.0

452094.0

Ig

87022.4

7230.4

208.1

-3686.0

90774.9


-7378.6

4314.2

771.2

7425.3

5132.0

G

87564.7

2322.9

5009.3

85083.0

-860.9

179119.0

GROSS PRODUCT

956648.7

207067.6

98497.1

85083.04701.04517.0

727119.9

2083634.3

tTP*


Summary input-output tables 277

1972

PRODUCTION

TOTAL TRADE

ROYALTIES


ROW Ind

GROSS VALUE ADDED

GROSS OUTPUT

619148.1

78676.1

54094.4

620719.3

1372637.9

< TV

54809.2

22853.4

17524.9

218878.0

314065.5

22725.3

9696.4

28891.4

101902.4

163215.4

Govt

137400.0

137400.0

Hsehld

5349.0

5349.0

ROW

6918.1

6918.1

CON

468702.7

50171.5

5349.0-3524.4

702672.1

G

Ig

127993.8

10837.9

249.3

-15182.0

123899.0

X-IM

-22509.0

7046.5

1411.4

10645.8

-3405.3

G

101767.3

2982.2

10872.7

137400.0

-203.3

252819.0

GROSS PRODUCT

1372637.4

314065.8

163215.6

137400.05349.06918.1

1075984.7

3075570.7

tTP*

1


1977

PRODUCTION

TOTAL TRADE

ROYALTIES


ROW Ind

GROSS VALUE ADDED

GROSS OUTPUT

PRODUCTION

1178165.0

99881.2

999264.8

TOT TRADE

97257.3

37337.5

29973.2

345598.3

2407755.1 510166.3

ROYALTIES

44041.6

17270.6

54499.5

178308.4

294120.0

Govt

214465.1

214465.1

DUMMYHsehld

5930.0

5930.0

ROW

24084.8

24084.8

CON

771824.0

288053.6

80449.3

5930.0-7233.0

1139023.9

Ig

216650.2

19788.0

521.7

2021.6

238981.5


-52853.3

13640.5

3215.9

32015.6

-3981.4

G

154507.3

2362.0

23180.9

241465.1

-697.8

420817.5

GROSS PRODUCT

2409592.0

508896.4

291721.6

241465.15930.0

24084.8

1794841.6

5276531.5

tTP*

I

Figure C.7. 197710 Table

D

Interpolation of key input-output variables

Companion text: Section 5.2

The summary input-output tables of Appendix C provide benchmark-year estimates of Marxian variables and their orthodox counterparts. Inorder to convert these into annual estimates, we use annual NIPA data forvalue-added and final-demand quantities. But input-output variables suchas intermediate inputs M, royalties RY, and rest-of-world flows ROW areunavailable in NIPA. For these variables, we interpolate between input-output benchmark values in the following manner.

(1) In each input-output year, we calculate the ratio of the componentto either its using or receiving industry's gross value added. For materialinputs M' (and depreciation D later on), we utilize the using industry'sGVA. Thus for Mp we create the ratio xp = (Mp/GVAp)IO, where the sub-script IO indicates that both variables are from input-output tables. Forroyalties RY we use the receiving industry's GVA (i.e. GVAry) as the nu-meraire, as in Xj = (RYi/GVAry)Io. This is done because some royalties,such as RYj and RYx_im, appear (respectively) as components of the highlyunstable final-demand totals I and X - I M (see Figure C.I). Benchmarkcoefficients created by dividing these royalties by unstable totals are notvery useful. The same reasoning applies to the ROW entries in FigureC.I, which are divided by total ROW in order to form coefficients forextrapolation, as in xrOw = ROWg/ROW.

(2) All coefficients created as described in (1) are linearly interpolatedbetween benchmark (IO) years. The result is an annual series for each co-efficient, derived entirely from input-output data.

(3) The annual observation for each coefficient is multiplied by theNIPA measure of the relevant gross value added (or ROW, in the case of

278

Interpolation of key input-output variables 279

Table D.I. Interpolation ofM'p between 1963 and 1967

(MP)IO»(GVAP)IO»x p(GVAp)NIPA

c

1963

384.41332.75

1.155337.30389.68

1964

—1.148

359.10412.31

1965

—1.141

392.10447.41

1966

—1.134

426.60483.74

1967

489.38434.29

1.127444.30500.66

a Figures C.4 and C.5.b xp = (Mp/GVAp)IO for benchmark years 1963 and 1967 (linearly interpolated for 1964-66).c Table E.I.

rest-of-world coefficients) to create a NIPA-based estimate of the originalIO variable. Thus

p p p y , and

( R O W g ) N I P A HE xrOwg' ( R O W ) N I P A .

The resulting annual estimates are then used in all subsequent calcula-tions. Table D.I illustrates the procedure for Mp between the two bench-mark years 1963 and 1967.

The interpolation procedure generates annual estimates of the key in-put-output variables up to 1977, which is the last available input-outputtable. For 1978-87, we extrapolated all variables except M;y using the1977 values of their x-ratios along with relevant GVA's from NIPA. Mry

was estimated as a residual from a formula based on the equality of theidentities for the gross output GOry and gross product GPry of the royal-ties sector. This allowed us to preserve the balance of total value and totalproduct even in the extrapolated data. From Figure C.I we have:

GOry = M'ry + RYry + GVAry;

GOry = GPry.

Therefore,

The results are summarized in Table D.2. Note that

GP = M + GFD

00o

Table D.2. NIPA-based interpolations of key IO variables (billions of dollars)0

Variables

Mp

RYP

M;,RYH

RYC

RY4

RYC

RY.-,.DPDtt

DryROW™ROWx.ira

ROWC

Mry

GP

1947

173.226.53

19.923.216.050.050.150.067.930.980.43

-1 .052.32

-0 .074.23

445.20

1948

198.477.51

21.683.666.900.050.200.079.421.120.49

-1 .272.87

-0 .104.86

501.09

1949

189.068.21

21.363.967.480.060.250.099.291.160.52

-1 .142.65

-0 .115.31

491.85

1950

212.569.06

22.744.328.200.060.310.10

10.811.300.57

-1 .182.81

-0 .135.86

546.81

1951

244.5910.1024.734.779.070.070.390.12

12.851.480.62

-1 .523.71

-0 .196.54

628.80

1952

254.3511.2025.42

5.239.980.080.470.15

13.801.600.68

-1.614.04

- 0 . 2 27.25

660.15

1953

268.6612.5225.97

5.7911.070.080.570.17

15.041.710.75

-1 .483.81

-0 .238.10

698.29

1954

261.3613.5726.386.21

11.900.090.670.20

15.081.810.79

-1 .493.95

-0 .268.78

695.08

1955

287.1814.7328.436.67

12.820.100.780.23

17.072.040.84

-1 .694.62

-0 .339.53

759.29

1956

303.1116.1929.84

7.2613.990.100.910.26

18.542.230.91

-1 .875.27

-0 .4010.47

802.66

1957

314.6317.6131.18

7.8115.100.111.050.30

19.792.420.97

-2 .025.91

-0 .4911.39

841.93

1958

308.0019.0431.618.36

16.210.121.200.34

19.922.561.03

-1 .654.99

-0 .4412.32

845.30

1959

334.9320.8034.008.89

18.180.131.680.37

21.442.781.12

-1 .675.27

-0 .5013.61

918.12

1960

343.7221.8934.619.10

19.650.132.170.39

21.782.861.17

-1 .795.88

-0 .5914.49

949.79

1961

347.5423.0335.249.30

21.240.132.710.41

21.802.951.22

-1 .836.31

-0 .6815.42

975.53

Variables 1962 1963 1964 1965 1966 1967 1968 1969 1970 1971 1972 1973 1974 1975 1976

MP

RYpMiRYU

RYC

RYiRYG

RYx_iro

DPDH

DryR O W ^ROWx_im

ROWC

M;GP

371.4024.0737.27

9.4222.80

0.143.290.43

23.053.161.26

- 2 . 0 47.38

- 0 . 8 516.32

1044.76

389.6825.3138.59

9.5824.61

0.143.950.45

23.913.311.31

- 2 . 0 87.94

- 0 . 9 717.36

1099.77

412.3127.3942.0010.3126.44

0.164.250.53

25.053.461.38

- 2 . 3 38.79

- 1 . 0 618.52

1173.84

447.4130.0745.0311.2528.81

0.184.630.62

26.913.571.48

- 2 . 5 49.47

- 1 . 1 220.03

1273.88

483.7433.6048.4912.4931.950.215.140.74

28.793.681.61

-2 .509.17

-1.0822.06

1389.06

500.6637.1851.9413.7335.090.235.650.87

29.483.781.73

-2.729.86

-1.1424.05

1462.58

545.1440.6056.3014.6338.190.246.560.97

32.434.151.95

-3.1611.04

-1.0825.88

1595.80

586.5444.9360.1815.7942.110.257.701.10

35.264.502.23

-3.2410.89

-0.8628.21

1722.72

602.4748.3562.8016.5545.17

0.268.761.21

36.594.772.47

-3.5511.54

-0 .6929.91

1800.78

644.7052.9267.7117.6349.260.26

10.111.35

39.565.222.78

-4.6314.51

-0.5732.23

1945.90

714.3358.1573.2018.8453.940.27

11.691.52

44.275.723.15

-5.7117.23

-0.3334.86

2143.39

837.4065.0883.2920.7658.710.31

13.501.78

52.406.553.66

-7.5824.25

-0.4739.21

2440.00

926.5671.7191.9422.5362.900.35

15.332.05

58.507.274.19

-8 .3028.37

-0.5743.41

2667.47

1023.7878.69

103.2524.3467.100.39

17.322.35

65.178.214.76

-6 .7224.73

-0.5147.86

2919.00

1187.3389.45

115.6927.2574.140.46

20.232.78

76.189.245.59

-7 .2228.93

-0.6154.66

3305.49

282 Table D.2 (cont.)

Variables

RYP

M;RY,,RYC

RYiRYC

RYx.im

DpD,,DryROWcon

ROWx.im

ROWC

M -GP

1977

1367.27106.43131.3331.9485.720.56

24.703.43

88.3610.556.87

- 7 . 6 333.76

- 0 . 7 465.33

3750.53

1978

1545.89125.44147.8637.64

101.030.66

29.114.04

99.9011.878.09

- 9 . 1 640.54

- 0 . 8 873.99

4248.52

1979

1710.49143.45163.8243.05

115.540.75

33.294.62

110.5413.159.25

-13 .1558.22

- 1 . 2 784.61

4731.53

1980

1851.27160.92171.9448.29

129.620.84

37.355.18

119.6413.8110.38

-14 .2963.27

- 1 . 3 894.92

5146.84

1981

2078.34182.00194.3054.62

146.590.95

42.245.86

134.3115.6011.74

-15 .6569.26

-1 .51107.35

5768.06

1982

2114.61192.05203.79

57.63154.68

1.0044.57

6.18136.66

16.3612.39

-15 .3868.06

- 1 . 4 8113.28

5951.66

1983

2235.61224.32220.06

67.31180.68

1.1752.06

7.22144.48

17.6714.47

-14 .9966.33

- 1 . 4 5132.31

6407.16

1984

2497.25247.24248.59

74.19199.14

1.2957.38

7.96161.39

19.%15.95

-14 .2363.01

- 1 . 3 7145.83

7119.72

1985

2618.65284.63268.04

85.41229.25

1.4966.06

9.16169.2321.5218.36

- 1 2 . 2 254.10

- 1 . 1 8167.88

7594.93

1986

2664.48328.62284.68

98.62264.69

1.7276.2710.58

172.1922.8621.20

-10 .4846.39

-1 .01193.83

7974.71

1987

2808.66366.14303.10109.87294.91

1.9184.9811.79

181.5124.3423.62

- 8 . 8 639.21

- 0 . 8 5215.96

8510.87

1988

3122.99395.27320.09118.62318.37

2.0691.7412.73

201.8325.7025.50

-10 .0644.52

- 0 . 9 7233.15

9198.45

1989

3278.25434.22341.01130.30349.74

2.27100.78

13.98211.86

27.3828.01

-11 .2949.97

- 1 . 0 9256.12

9789.83

a All variables in this table refer to elements of IO tables in Appendix C.*For 1978-89, all variables were extrapolated, as explained in the text.c For 1978-89, M^ is calculated as a residual, as explained in the text.

E

Annual estimates of primary variables

Companion text: Section 4.2

Our previous IO benchmark estimates in Table 5.2 can be converted intoannual series by making use of annually available NIPA data for value-added and final-demand components, and of the interpolated values ofkey input-output variables (M, RY, ROW) generated in Appendix D.The basic formulas from Section 5.2 are reproduced here.

TV* = GOP + GOtt = total value,

whereGOP = Mp + RYp + GVAp and

tt + NIPAtt;

C*n = Mp = materials inputs into production;CJ = Dp = depreciation of productive fixed capital;C* = Mp + Dp = constant capital used up (flow);

GVA* s TV* - C* = Marxian gross value added;VA* = TV* - C* = GVA* - C* = Marxian (net) value added;

CON* = CON - GVAir - RYcon - HHcon - ROWcon;

= (X-IM)-RY x _ i m -ROW x _ i m ;G* = G-W G -ROW G .

Table E.I details annual TV* estimates; Table E.2 describes calcula-tions for annual TP*.

1 As noted in Section 5.1, the inventory valuation adjustment IVA was mergedinto value added on the revenue side, and hence into IJ on the use side.

283

Table E.I. Annual estimates of TV*, 1948-89 (billions of dollars)

12345

6789

10111213141516171819202122232425262728293031323334

35363738394041

42434445

Sources*

Table D.2Table D.2

60146017601 12601 1360137

601616016260164601656016660167601686017060171601 72

6017760180

Table D.2Table D.2

60150601 51

Table B.5

60158

809 86809 94Table B.6

60181

Table D.2

Variables

TV*=GO p + GOtt + S.D.GOP=MP+RY^+GVAP

M'P(=C*)RY;GVAP = {GVAagr + GVAmin + GVAcon + GVAman

+ GVAtut + GVAscrvp+GVAgovep)GVAagr

GVAmin

G V A ^GVAman

GVAtut

G V A ^Hotels and other lodging placesPersonal servicesAuto repair, services, and garagesMiscellaneous repair servicesMotion picturesAmusement and recreation servicesHealth servicesEducational servicesSocial services and membership organizationsMiscellaneous professional services

GVAgovep = total government enterprisesGovernment enterprises (federal)Government enterprises (state and local)

GO u = M;t + RYtt + GVA'tt

M;t

RYt'tGVA'tt = GVAw h t r +GVAr c t t r+GVA b r

GVAwhtr = wholesale trade.GVArcttr = retail tradeGVAbr = GVA' b r -ABR

GVA'br = ( l - g ) x G V A n i r

g = (GR/GO)GVAnir = nonimputed real estate

= G V A r e - G V A i r

GVAre = real estate = GVAir + GVAnir

GVAir = imputed r e n t = G H P n f + G H P f

GHP n f =gros s housing product (nonfarm)G H P f = g r o s s housing product (farm)

ABR[ G V A g r = g x G V A n i r ]

S .D. = statistical discrepancy

DP(=CJ)C* = M'P+DP

GVA*=TV*-C*VA* = TV* - C* = GVA* - CJ

1948

446.25367.68198.47

7.51

161.7024.009.40

11.5074.7023.7015.601.603.101.000.801.301.304.100.901.501.102.801.401.40

79.8621.68

3.6654.5318.3030.206.038.800.28

12.2020.608.407.401.002.773.40

-1.30

9.42207.89247.78238.35

1949

432.02351.67189.06

8.21

154.4019.508.10

11.5072.2023.9016.101.703.200.900.70

t

.30

.301.30.00

1.701.10UO1.501.60

79.5421.36

3.9654.2317.5030.506.239.120.28

12.6022.009.408.401.002.893.480.80

9.29198.36242.95233.66

a Unless otherwise indicated, all data come from NIPA (e.g. BEA 1986), where the first three digitsdenote the relevant table number and subsequent digits the line numbers within those tables.

284

1950

481.79395.62212.56

9.06

174.0020.809.30

13.2084.0026.6017.101.703.401.000.801.301.304.701.001.901.203.001.301.70

85.3722.744.32

58.3019.7031.806.809.880.27

13.6024.3010.709.601.103.073.720.80

10.81223.37269.23258.42

1951

551.61455.40244.59

10.10

200.7023.9010.2015.6099.0030.2018.401.803.601.100.901.301.305.201.102.101.503.401.501.90

93.5224.73

4.7764.0222.4034.407.22

10.710.27

14.7026.9012.2011.00

1.203.493.992.70

12.85257.45307.02294.17

1952

573.67474.7$254.35

11.20

209.2023.2010.2016.90

103.3032.2019.30

1.903.701.200.901.201.405.701.102.201.804.102.002.10

97.1225.42

5.2366.4622.6036.307.56

11.260.27

15.4029.4014.0012.80

1.203.694.141.80

13.80268.15319.32305.52

1953

605.61502.68268.66

12.52

221.5021.4010.7017.50

112.5034.2020.80

2.003.901.301.001.201.606.201.202.402.004.402.102.30

100.3325.975.79

68.5723.1037.30

8.1712.030.27

16.4032.3015.9014.70

1.203.864.372.60

15.04283.70336.95321.91

1954

596.59490.93261.36

13.57

216.0020.8011.0017.70

106.7033.8021.70

2.104.001.401.001.301.606.401.302.602.104.301.902.40

102.9626.386.21

70.3723.4038.208.77

12.800.26

17.4035.1017.7016.50

1.204.044.602.70

15.08276.44335.23320.15

1955

653.31539.80287.18

14.73

237.9020.0012.5019.10

121.3036.8024.00

2.204.201.601.001.301.707.701.402.902.404.201.502.70

111.7128.436.67

76.6126.5040.60

9.5113.810.26

18.7038.1019.4018.101.304.304.891.80

17.07304.24366.14349.07

1956

687.44570.99303.11

16.19

251.7019.8013.6021.30

127.2039.6026.10

2.304.601.901.201.301.908.201.603.102.904.101.202.90

118.3429.847.26

81.2428.8042.50

9.9414.590.26

19.7040.7021.0019.801.204.655.11

-1.90

18.54321.64384.33365.79

1957

717.68594.14314.63

17.61

261.9019.6013.7022.20

131.8041.7028.102.504.902.101.301.202.009.001.703.403.404.801.803.00

124.7431.187.81

85.7530.3044.7010.7515.680.26

21.1044.0022.9021.60

1.304.935.42

-1.20

19.79334.42403.05383.25

1958

711.79584.05308.00

19.04

257.0022.1012.6021.80

124.3041.9029.50

2.505.002.201.201.102.109.901.903.603.504.801.703.10

127.8431.618.36

87.8730.9045.5011.4716.550.25

22.2047.1024.9023.50

1.405.095.65

-0.10

19.92327.92403.79383.87

(more)

285


Table E.I (cont.)

1234567891011121314151617181920212223242526272829303132333435363738394041

42434445

1959

774.37637.23334.9320.80

281.5020.4012.5023.70141.8045.1032.102.705.202.401.201.102.4011.002.004.103.805.902.303.60

138.6434.008.89

95.7534.0049.3012.4517.730.25

23.7050.7027.0025.601.405.285.97

-1.50

21.44356.38439.44417.99

1960

796.20656.61343.7221.89

291.0021.7012.8024.30144.4047.3034.302.805.402.701.301.102.7011.502.204.604.006.202.204.00

142.3934.619.10

98.6735.1050.6012.9718.490.25

24.8054.1029.3027.801.505.526.31

-2.80

21.78365.51452.48430.69

1961

812.01666.98347.5423.03

296.4021.8012.9025.30145.0048.9036.502.905.702.801.401.202.8012.202.505.004.306.001.904.10

146.2335.249.30

101.7036.1051.9013.7019.390.26

26.1057.4031.3029.801.505.696.71

-1.20

21.80369.34464.47442.67

1962

870.18714.58371.4024.07319.1022.3013.1027.10158.6051.9039.403.106.003.201.401.203.0013.302.805.404.706.702.204.50

155.6037.279.42

108.9138.5055.6014.8120.730.26

28.0061.7033.7032.201.505.927.270.00

23.05394.45498.78475.73

1963

914.05752.28389.6825.31337.3022.3013.4028.90168.1054.8042.203.406.303.401.601.303.2014.203.105.705.007.602.704.90

162.3738.599.58

114.1940.2058.1015.8922.060.26

29.9065.6035.7034.101.606.167.84

-0.60

23.91413.59524.38500.46

1964

973.89798.80412.3127.39359.1021.4013.8031.60180.2058.3045.703.506.803.801.701.403.4015.703.406.005.608.102.905.20

176.5042.0010.31

124.1943.4063.7017.0923.590.2632.1069.8037.7036.101.606.508.51

-1.40

25.05437.36561.59536.54

1965

1057.74869.58447.4130.07392.1024.2014.0034.70198.4062.6049.303.907.104.001.801.603.6017.003.806.506.108.903.405.50

189.3645.0311.25

133.0946.8068.1018.1925.140.2734.3074.5040.2038.501.706.959.16

-1.20

26.91474.32610.33583.42

1966

1150.25943.94483.7433.60

426.6025.3014.6037.90

217.4067.4054.304.407.804.302.001.703.7018.904.307.207.009.703.905.80

204.2148.4912.49

143.2351.2073.0019.0326.600.2736.4079.4043.0041.201.807.579.802.10

28.79512.53666.51637.72

Annual estimates of primary variables 287

1967

1200.79982.14500.6637.18

444.3024.9015.2039.70

222.9070.7059.904.908.304.702.101.803.90

21.604.807.807.8011.005.006.00

219.0551.9413.73

153.3854.5078.5020.3828.570.2739.2084.9045.7043.901.808.1910.63-0.40

29.48530.13700.13670.66

1968

1307.971069.74545.1440.60

484.0025.7016.2043.50243.6076.4065.905.308.705.202.302.104.20

24.305.408.408.4012.706.206.50

239.3356.3014.63

168.3960.0086.8021.5930.590.27

42.1090.7048.6046.602.009.0011.51-1.10

32.43577.57762.83730.40

1969

1406.841152.47586.5444.93521.0028.6017.1048.70257.1082.6073.405.809.005.902.602.004.40

27.806.309.609.5013.506.507.00

258.2760.1815.79

182.3064.8094.4023.1033.320.28

46.1098.7052.6050.502.1010.2112.78-3.90

35.26621.80820.30785.04

1970

1457.171186.22602.4748.35535.4029.9018.7051.40

252.3088.4080.206.309.306.302.702.304.80

31.407.1010.0010.3014.506.807.70

272.0462.8016.55

192.6968.20100.5023.9935.220.28

49.00105.4056.4054.102.3011.2313.78-1.10

36.59639.06854.70818.11

1971

1568.481270.83644.7052.92

573.2032.2018.8056.50

265.7097.1087.306.809.407.202.902.205.10

34.708.0011.0011.2015.607.408.20

295.8567.7117.63

210.5174.00109.8026.7139.250.2954.90116.7061.8059.402.4012.5415.651.80

39.56684.26923.78884.22

1972

1728.881407.88714.3358.15

635.4037.4020.2063.00292.50108.0096.807.609.808.103.302.405.50

39.109.2011.8012.8017.508.608.90

322.6073.2018.84

230.5683.10119.4028.0642.020.2959.10126.1067.0064.402.6013.9617.08-1.60

44.27758.601014.55970.28

1973

1980.041623.58837.4065.08721.1056.2023.4070.40326.40118.70107.908.4010.309.403.702.706.40

43.9010.0013.1015.0018.108.209.90

360.7583.2920.76

256.7093.60132.0031.1046.880.2966.30139.5073.2070.302.9015.7819.42-4.30

52.40889.801142.641090.24

1974

2161.801771.47926.5671.71773.2055.0036.9074.50338.50129.10118.909.0010.9010.204.402.806.90

49.9010.6014.2016.7020.309.9010.40

392.0391.9422.53

211.51107.30138.7031.5749.760.2970.50151.1080.6077.203.4018.1920.74-1.70

58.50985.051235.251176.75

(more)


Table E.I (cont.)

1234567891011121314151617181920212223242526272829303132333435363738394041

42434445

1975

2366.721931.161023.7878.69

828.7056.3041.3076.50357.30141.70133.2010.1011.4011.204.603.107.7057.8011.4015.9018.8022.4011.0011.40

433.06103.2524.34305.47117.50156.2031.7752.420.3074.40161.8087.4083.603.80

20.6521.982.50

65.171088.951342.951277.77

1976

2691.952209.881187.3389.45

933.1055.7046.0086.20

409.30160.40149.7011.5012.8012.905.103.808.60

66.2011.7017.1020.3025.8013.8012.00

478.48115.6927.25335.53125.50174.2035.8358.230.3082.80178.5095.7091.304.40

22.4024.573.60

76.181263.511504.621428.45

1977

3054.582517.801367.27106.43

1044.1058.9050.2097.90

465.30178.90166.0012.7014.2014.805.904.209.8073.6012.1018.7023.8026.9014.2012.70

536.78131.3331.94

373.51139.80193.0040.7165.640.3093.50198.70105.20100.205.00

24.9327.860.00

88.361455.631687.311598.95

1978

3456.062851.831545.89125.44

1180.5070.1056.50115.60518.80201.00188.7015.4015.9017.506.905.6010.4082.6013.1021.3027.8029.8015.9013.90

606.13147.8737.64

420.63157.90215.5047.2375.470.30

107.70228.00120.30114.805.50

28.2432.23-1.90

99.901645.791910.171810.27

1979

3832.063160.151710.49143.45

1306.2083.1072.70131.40561.80216.10209.1017.4017.0019.607.605.0011.5093.1014.4023.5033.9032.0017.6014.40

672.91163.8343.05

466.03179.50236.3050.2383.110.30

118.60254.70136.10129.606.50

32.8735.49-1.00

110.541821.042121.562011.02

1980

4140.143425.891851.27160.92

1413.7077.20107.30137.70581.00240.80235.8018.9018.8021.109.205.0012.40

108.1016.0026.3039.6033.9018.6015.30

709.35171.9448.29

489.11193.90245.0050.2188.150.30

125.80281.50155.70148.107.60

37.9437.654.90

119.641970.912288.872169.23

1981

4653.193847.442078.34182.00

1587.1092.00143.70138.40643.10269.60262.3020.4019.5023.109.205.5014.00124.7017.5028.4047.5038.0021.9016.10

801.65194.3154.62

552.73214.00269.1069.6399.080.30

141.40318.70177.30168.109.20

29.4542.324.10

134.312212.652574.852440.54

1982

4762.473921.462114.61192.05

1614.8089.60132.10140.90634.60288.40289.1021.7021.3023.509.606.3015.10142.0019.1030.5045.7040.1022.2017.90

841.12203.7957.63579.70219.00287.5073.20104.970.30

149.80342.70192.90183.609.30

31.7744.83-0.10

136.662251.272647.862511.20

Annual estimates of primary variables 289

1983

5085.624167.122235.61224.311707.2074.30118.40149.60683.20320.00317.6024.3023.1026.1010.806.6016.80

156.1021.0032.8049.9044.1023.6020.50

913.30220.0667.31

625.92226.50316.4083.02117.300.30

167.40374.20206.80198.008.80

34.2850.105.20

144.482380.092850.012705.53

1984

5689.104653.802497.25247.241909.3092.90119.40171.50771.90354.40347.3027.0025.0029.2012.807.3017.80

169.0023.5035.7056.9051.9027.9024.00

1029.90248.5974.19

707.12263.10350.8093.22130.200.30

185.80409.10223.30214.50

8.8036.9855.605.40

161.392658.643191.853030.46

1985

6014.564901.132618.65285.001997.4892.01114.17186.57789.54374.10383.3030.3629.7033.2112.449.0219.91

184.5625.7538.3563.6257.8030.8027.00

1118.18268.6285.53

764.03280.84377.40105.78145.680.30

207.90449.00241.10233.20

7.9039.9062.22-4.75

169.232787.883395.913226.68

1986

6236.335067.022664.48328.55

2073.9993.6074.29

203.80832.42393.50416.3832.4331.8836.2813.6910.4822.08

200.3027.5741.6774.4360.0030.3029.70

1171.11279.0098.59793.51282.05400.54110.93153.970.30

219.73478.63258.90251.70

7.2043.0465.76-1.80

172.192836.673571.853399.66

1987

6614.455378.212808.66365.80

2203.75100.6776.84

219.17875.54408.20460.7436.0133.9938.1313.8412.5124.82

226.1429.5045.8183.6062.6030.3032.30

1246.83295.80109.77841.25294.77426.36120.12166.560.30

237.69517.29279.60272.10

7.5046.4371.13

-10.59

181.512990.173805.793624.28

1988

7223.855903.113122.99395.27

2384.84104.2680.02

237.40940.66444.30510.8241.2538.5040.5015.5913.5327.40

250.3032.4951.2493.9267.4032.7034.70

1348.98320.09118.62910.28317.38459.95132.96183.050.30

261.23561.63300.40292.80

7.6050.0978.18

-28.25

201.833324.824100.863899.03

1989

7639.866215.873278.25434.222503.40113.4880.25

247.72966.00460.90557.2444.4742.9943.5916.9414.7229.75

273.3135.5355.95104.9277.8039.7038.10

1441.03341.01130.30969.72339.47485.98144.28198.320.30

283.02607.12324.10316.30

7.8054.0484.70

-17.05

211.863490.114361.614149.75


Glossary of variables in Table EAABR Amortization of buildings and equipment rented out by the rental

sector to othersC* Constant capital used up (flow)Dp ( = CJ) Depreciation of productive fixed capitalg Estimated proportion of land rent in the total revenue of the real

estate sectorGHPf Gross housing product (imputed, farm)GHPn f Gross housing product (imputed, nonfarm)GOP Gross output of productive sectorsGOtt Gross output of trade sectorGVA'br Gross value added (or GNP, gross national product) of rental

sectorGVA* Marxian gross value addedGVAagr Gross value added (or GNP) by agriculture, forestry, and fisheriesGVAbr Gross value added (or GNP) of rental sector (net of ABR)GVAcon Gross value added (or GNP) by constructionGVAgovep Gross value added (or GNP) by government enterprises (federal,

state, local)GVAgr Ground rent (nonimputed)GVAir Gross housing product (imputed, farm and nonfarm)GVAman Gross value added (or GNP) by manufacturingGVAmin Gross value added (or GNP) by miningGVAnir Gross value added (or GNP) of rental sector (nonimputed)GVAp Gross value added (or GNP) by productive sectorsGVAre Gross value added (or GNP) of real estate-and-rental sector

(imputed and nonimputed)GVArettr Gross value added (or GNP) by retail tradeGVAservp Gross value added (or GNP) by productive subsectors of servicesGVA;t Gross value added (or GNP) by trade sector (wholesale and retail)GVAtut Gross value added (or GNP) by transportation and public utilitiesG V A w h t r Gross value added (or GNP) by wholesale tradeM P ( = Q i ) Materials inputs into productionM;t Intermediate inputs of trade sectorRYp Royalties of productive sectorsRYt't Royalties of trade sectorS.D. Statistical discrepancyTV* Total valueVA* Marxian net value added

o

1n

6nI

1^

oo

Noo

o —

•

I8IuIii

*

s

&

O

O

>

g J

K O

*T

3

IO

w1^

^ ^

(2(2

(2S

S

2^

2(2

Q Q

Q

_ .C

JD

^

£

M

2(2^2 g (2 g

291

w n

«

oe

i

O\

I s- <n

O

\ r

i 00

r»

' m

00

t^

fr»

oo

fo

-T

j-

©m

t-

~«

o0

»o O

\ vd

-m

vl 6

«

v) 1

00 ^f

t r

«o h-' ri 0 m

in m

-' t*-' vc5 0

«' ri

d1

00

©

^

^»

-«

H

»

vi

«

Tt 1

(S

©m

«s

00 t-; h; r

j -

^d

od

od

o\

dv

cr

<N

-H

' 00

in

1I

0

• 6\\^

<S

Q

ble Q

ble

HII «

Q

ble

ui

22

6

ble

Q

*

Q ui

« % S

2 (2 tS

^ Q^ S2 {2 I.Q

ble

H

QQ

g:oII

o'fcble

H

292

Sources0 Variables 1976 1977 1978 1979 1980 1981 1982 1983 1984 1985 1986 1987 1988 1989

Table D.2Table D.2Table D.2

1012Table E.ITable D.260173Table D.2

1016Table D.2Table E.I

101 15Table D.2Table D.2

3017Table D.23018Table D.2Table E.I

TP*M'P(=C*)MiM;y

GFP = T P * - C *CON*CONGVAir

RYcon

HHc o n

ROWcon

IG*IGRYi

ABR(X-IM)*X-IMRYx_im

ROWx_im

G*GRYG

Wc

ROWg

cd*FP* = G F P * - C J

2694.39

1187.33

115.69

54.66

1507.06

961.28

1129.30

95.70

74.14

5.40

- 7 . 2 2

254.84

277.70

0.46

22.40

-12 .91

18.80'

2.78

28.93

133.49

356.90

20.23

203.80

- 0 . 6 1

76.18*

1430.88

3058.10

1367.27

131.33

65.33

1690.83

1068.01

1257.20

105.20

85.72

5.90

- 7 . 6 3

318.62

344.10

0.56

24.93

- 3 5 . 2 9

1.90

3.43

33.76

142.84

387.30

24.70

220.50

- 0 . 7 4

88.36

1602.47

3456.76

1545.89

147.87

73.99

1910.87

1185.13

1403.50

120.30

101.03

6.20

- 9 . 1 6

387.90

416.80

0.66

28.24

- 4 0 . 4 8

4.10

4.04

40.54

156.47

425.20

29.11

240.50

- 0 . 8 8

99.90

1810.97

3833.25

1710.49

163.83

84.61

2122.76

1321.81

1566.80

136.10

115.54

6.50

-13 .15

421.18

454.80

0.75

32.87

- 4 4 . 0 4

18.80

4.62

58.22

175.38

467.80

33.29

260.40

- 1 . 2 7

110.54

2012.22

4141.10

1851.27

171.94

94.92

2289.84

1454.98

1732.60

155.70

129.62

6.60

- 14 .29

398.22

437.00

0.84

37.94

- 3 6 . 3 6

32.10

5.18

63.27

206.13

530.40

37.35

288.30

- 1 . 3 8

119.64

2170.20

4654.40

2078.34

194.31

107.35

2576.06

1599.86

1915.10

177.30

146.59

7.00

-15 .65

485.10

515.50

0.95

29.45

- 4 1 . 2 2

33.90

5.86

69.26

230.67

588.10

42.24

316.70

- 1 . 5 1

134.31

2441.75

4763.86

2114.61

203.79

113.28

2649.25

1710.89

2050.70

192.90

154.68

7.60

- 1 5 . 3 8

414.52

447.30

1.00

31.77

- 4 7 . 9 4

26.30

6.18

68.06254.71

641.70

44.57

343.90

- 1 . 4 8

136.66

2512.59

5086.97

2235.61

220.06

132.31

2851.36

1853.81

2234.50

206.80

180.67

8.20

- 1 4 . 9 9

466.85

502.30

1.17

34.28

-79 .65

- 6 . 1 0

7.22

66.33

257.99

675.00

52.06

366.40

- 1 . 4 5

144.48

2706.88

5691.02

2497.25

248.59

145.83

3193.77

2013.39

2430.50

223.30

199.14

8.90

- 1 4 . 2 3

626.53

664.80

1.29

36.98

-129 .87

- 5 8 . 9 0

7.96

63.01

289.29

735.90

57.38

390.60

- 1 . 3 7

161.39

3032.38

6014.18

2618.65

268.62

168.11

3395.53

2161.53

2629.00

241.10

229.56

9.03

- 1 2 . 2 2

601.72

643.10

1.49

39.90

-141 .28

- 7 8 . 0 0

9.18

54.10

336.83

820.80

66.15

419.00

- 1 . 1 8

169.23

3226.30

6224.47

2664.48

279.00

193.79

3559.99

2275.73

2797.40

258.90

264.63

9.08

- 1 0 . 9 3

614.64

659.40

1.72

43.04

-156.38

- 9 7 . 4 0

10.58

48.40

353.20

872.20

76.25

443.80

- 1 . 0 5

172.19

3387.80

6606.59

2808.66

295.80

215.76

3797.93

2434.73

3009.40

279.60

294.63

9.13

- 8 . 6 9

651.16

699.50

1.91

46.43

-164 .96

-114 .70

11.78

38.48

365.44

921.40

84.90

471.90

- 0 . 8 4

181.51

3616.42

7226.22

3122.99

320.09

233.15

4103.23

2619.76

3238.20

300.40

318.37

9.72

- 1 0 . 0 6

694.94

747.10

2.06

50.09

-131 .34

- 7 4 . 1 0

12.73

44.52

366.63

962.50

91.74

505.10

- 0 . 9 7

201.83

3901.40

7641.82

3278.25

341.01

256.12

4363.57

2777.29

3450.10

324.10

349.74

10.25

- 1 1 . 2 9

714.89

771.20

2.27

54.04

-110 .05

- 4 6 . 1 0

13.98

49.97

384.31

1025.60

100.78

541.60

- 1 . 0 9

211.86

4151.71

a Unless otherwise indicated, all data come from NIPA (e.g. BEA 1986), where the first three digits denote the relevant table number and subsequent digits the line numberswithin those tables.

tov©


Glossary of variables in Table E.2ABR Amortization of buildings and equipment rented out by the rental

sector to othersC O N Personal consumption expendituresCON* Marxian final personal consumption expendituresC* Depreciation of productive fixed capitalFP* Marxian final productG Government purchases of goods and servicesG* Marxian government purchases of goods and servicesGFP* Marxian gross final productGVAir Gross housing product (imputed, farm and nonfarm)HH c o n Consumer payments to household sectorIG Gross private domestic investmentIG* Marxian gross private domestic investmentM P ( = C£) Materials inputs into productionM'ry Intermediate inputs of royalties sectorM;t Intermediate inputs of trade sectorROWX _ im Trade sector's payments to rest-of-world sectorROWcon Consumer payments to rest-of-world sectorROWg Government payments to rest-of-world sectorR Y x- im Trade sector's payments to royalties sectorRYcon Consumer payments to royalties sectorRYg Government payments to royalties sectorRYj Business payments to royalties sectorTP* Marxian total productWg Government compensation of employeesX — IM Net export of goods and services(X - IM)* Marxian net export of goods and services

Productive and unproductive labor

Our primary database for employment comes from NIPA. For total em-ployment L we use persons engaged in production (PEP), since this in-cludes both employees and self-employed persons. We use BLS data tocalculate the ratios of production labor to total labor in each productionsector, which are then applied to relevant NIPA employment totals inorder to split them into comparable components.

Productive labor is the production labor employed in capitalist produc-tion sectors: agriculture, mining, construction, transportation and publicutilities, manufacturing, and productive services (defined as all servicesexcept business services, legal services, and private households; see TableE.I for a full listing of productive services). It excludes nonproductionlabor (sales etc.) employed in the production sectors, as well as all laborin nonproduction sectors such as trade or finance. Total productive laboris the sum of the production workers in each production sector. Total un-productive labor is the sum of nonproduction workers in the productionsectors and all workers in the nonproduction sectors.

Total employment in production nonservice sectors is directly availablefrom NIPA. But since we only count a portion of the service sector asproductive, we estimate the employment in productive services by calcu-lating the ratio of productive service sectors' GNP to total services' GNPand applying that ratio to the total employment in services (Tables E.Iand F.I). Listing the production sectors as j = 1,...,£ and the nonpro-duction sectors asy = £+l,...,A7, we have:

j = total employment in they th sector (from NIPA)= persons engaged in production (PE:)= full-time equivalent employees (FEE)

+ self-employed persons (SEP);

295


L = £ L, = total labor;

(Lp/L)j = ratio of production/total workers in they th productionsector,y = l , . . . ,

g

(GNPpr);

GNPC,LLa

pr/serv

(Lp)y = (Lp/L)j.(Ly)

= estimated production worker employment in they thproduction sector, j = 1,..., k\

Lp = S(Lp)y = total productive labor;

Lu = L — Lp = total unproductive labor.

Table F.I summarizes productive and unproductive labor for the years1948-89.

Glossary of variables in Table FAEstimated proportion of land rent in the total revenue of the realestate sectorTotal GNP produced by productive servicesTotal GNP produced by all servicesTotal employment in all sectorsTotal employment in agriculture, forestry, and fisheriesTotal employment in the building rental sectorTotal employment in constructionTotal employment in dummy sectors (government - federal, state,and local)Total employment in finance and insuranceTotal employment in finance, insurance, and real estateTotal employment in government enterprises (federal)Total employment in government enterprises (state and local)Total employment in government enterprises (federal, state, andlocal)Total employment in government (federal)Total employment in government (state and local)Total employment in the ground-rent sectorTotal employment in manufacturingTotal employment in miningEstimated total productive labor in all sectorsEstimated total productive labor in agriculture, forestry, andfisheriesEstimated total productive labor in constructionEstimated total productive labor in government enterprises(federal)Estimated total productive labor in government enterprises (stateand local)Estimated total productive labor in government enterprises(federal, state, and local)

Lgefed

^getotal

^govntfed

'-'govntsl

(Lp)agr

(L p ) c o n

(Lp

•^p/getotal

Productive and unproductive labor 297

(Lp)m a n Estimated total productive labor in manufacturing(Lp)min Estimated total productive labor in mining(Lp)Serv Estimated total productive labor in productive subsectors

of services(Lp)t u l Estimated total productive labor in transportation and

public utilities(Lp)Serv Total production workers in all services (BLS)(Lp)c o n Total production workers in construction (BLS)(Lp)man Total production workers in manufacturing (BLS)(Lp)min Total production workers in mining (BLS)(Lp)serv Estimated total productive labor in all services(Lp)tut Total production workers in transportation and public

utilities (BLS)L p / L Ratio of productive to total laborL p / L u Ratio of productive to unproductive laborLr Total employment in royalties sectorsLre Total employment in real estateLrettr Total employment in retail tradeLserv Total employment in all servicesLtut Total employment in transportation and public utilitiesLu Estimated total unproductive labor in all sectors(Lu)agr Estimated total unproductive labor in agriculture, forestry,

and fisheries(Lu)c o n Estimated total unproductive labor in construction(LJgetotai Estimated total unproductive labor in government

enterprises (federal, state, and local)(Lu)man Estimated total unproductive labor in manufacturing(Lu)m i n Estimated total unproductive labor in mining(Lu)serv Estimated total unproductive labor in all services(Lu)tut Estimated total unproductive labor in transportation and

public utilitiesL w h t r Total e m p l o y m e n t in wholesa le tradeL"erv Total workers in all services (BLS)LcOn Total workers in construct ion (BLS)L'man Total workers in manufacturing (BLS)L'min Total workers in mining (BLS)L[ut Total workers in transportat ion and public utilities (BLS)( G N P p r / G N P ) s e r v Rat io o f G N P produced by productive-subsectors o f

services to G N P produced by all services( L p / L ) n o n g o v t o t Rat io o f product ion to total workers in all

nongovernmenta l sectors (BLS)(L p /L)se r v Ratio o f product ion to total workers in all services (BLS)(Lp/L)c O n Rat io o f product ion to total workers in construct ion (BLS)( L p / L ) ' m a n Ratio of production to total workers in manufacturing

(BLS)(Lp/L)min Ratio of production to total workers in mining (BLS)(Lp/L),'ul Ratio of production to total workers in transportation and

public utilities (BLS)

Table F.I. Productive and unproductive labor, 1948-89

Sources"

610B 13SEHE*SEHE

610B7SEHESEHE

610B 12SEHESEHE

610B 37SEHEf

SEHE

6I0B60SEHEC

SEHE

60160

Sectors

PRODUCTION Lp

Manufacturing

Lman(Lp)m.n

(Lp/L)Jn,n

( L p ) m , n = ( L p / L ) n i , n x L m , n

(Lu)m.n = L m a n - ( L p ) m , n

MiningLm i n

(Lp ) m i n

(Lp/L)min(Lp)min = (L p /L) n l i n X Lm i n

(Lu)min = L m i n - ( L p ) m i n

Construction

Leon(L'p)conLeon( L p / L ) c o n

(Lp)Con = (L p /L) i o n X Lc o n

(Lu)con = Lc o n — (L p ) c o n

Transportation and public utilities

L,u.(Lp)tu.LJ U.(Lp /L)|u l

(Lp),ui = (Lp/L);ulxLtlI,(Lu) l u l = L l u , - (L p ) , u ,

Services*

Lserv

(Lp)serv

LJerv(Lp/LJ^v(Lp)SCTv = (L p /L)J e r v xLs e r v

(GNPprJjCTv >t

GNPjerv

(GNPpr /GNPJserv( L p ) ^ v = (GNPp r/GNP)$ e r v X (Lp)^ ,(Lu)serv = Ljd-v — (Lp)sCTv

Units

thousands

thousandsthousandsthousands

thousandsthousands


thousandsthousands


thousandsthousands


thousandsthousands


thousandsbillions of $billions of $

, thousandsthousands

1948

32,994

15,96112,91015,5820.829

13,2242,737

1,028906994

0.91193791

3,3051,9542,1980.8892,938

367

4,3183,9644,1890.9464,086

232

7,7074,8585,1810.9387,22715.621.90.7125,1482,559

1949

31,201

14,77711,79014,4410.816

12,0642,713

956839930

0.90286294

3,1551,9492,1940.8882,803

352

4,1353,7614,0010.9403,887

248

7,6884,9035,2400.9367,19416.122.60.7125,1252,563

1950

32.226

15.50812,52315,2410.822

12,7422,766

957816901

0.90686790

3,4152,1012,3640.8893.035

380

4,1723,7914,0340.9403,921

251

7,9114,9985,3570.9337,38117.124.20.7075.2152.696

1951

33,123

16,66513.36816,3930.815

13,5903,075

972840929

0.90487993

3,6282,3432.6370.8893,224

404

4,3773,9544,2260.9364,095

282

8,0335,1695,5470.9327,48618.426.40.6975.2172,816

1952

32,768

16,90413,35916,6320.803

13,5773,327

949801898

0.892846103

3,6012,3602,6680.8853,185

416

4,3903,9474,2480.9294,079

311

8,0065,2935,6990.9297,43619.328.10.6875,1072,899

1953

33,043

17,65214,05517,5940.799

14,1013,551

908765866

0.883802106

3,5282,3412,6590.8803,106

422

4.4383.9714.2900.9264.108

330

8.0975,4195,8350.9297,52020.830.20.6895,1792,918

1954

31,230

16,37812,81716,3140.786

12,8673,511

833686791

0.867722111

3,3942,3162,6460.8752,971

423

4,2263,7534,0840.9193,883

343

8,0195,5565,9690.9317,46421.731.60.6875,1262,893

1955

31,714

16,85213,28816.8820.787

13,2643.588

835680792

0.859717118

3.4632,4772,8390.8723,021

442

4,2833,7994,1410.9173,929

354

8,3825,8056,2400.9307,79824.035.10.6845.3323,050

1956

31.864

17.12113,43617,2430.779

13.3413.780

873702822

0.854746127

3.5802,6533,0390.8733.125

455

4.3893.8744,2440.9134,006

383

8,7206,0276,4970.9288,08926.138.70.6745,4553,265

1957

31.433

17,07713,18917,1740.768

13.1153.962

869695828

0.839729140

3,5252,5772,9620.8703.067

458

4,3773.8454.2410.9073.968

409

9.0066.2286,7080.9288,36228.141.70.6745,6353,371

1958

29,349

15,60611,99715,9450.752

11,7423,864

775611751

0.814631144

3,3972,420"i.8170.8592,918

479

4,0993,5773,9780.8993.686

413

9.1586,2896,7650.9308,51429.544.00.6705,7083,450

1959

30,020

16.37112,60316,6750.756

12,3733.998

742590732

0.806598144

3.5332,5773,0040.8583,031

502

4,0833,6044,0110.8993,669

414

9,4306,5677,0870.9278,73832.148.30.6655,8073,623

1960

30,047

16,49812,58616.7960.749

12,3634,135

721570712

0.801577144

3,4912.4972,9260.8532,979

512

4,1003.5804,0040.8943,666

434

9.8176.8257.3780.9259,08134.351.40.6676,0603,757

1961

29.363

16,07512,08316,2360.740

11.8974.178

685532672

0.792542143

3.4612,4262.8590.8492,937

524

3,9933.4693.9030.8893,549

444

10,0057,0417,6200.9249,24536.554.90.6656,1463,859

Agriculture'610B4

610B 81

610B86

6I0B50610B 51

610B 52610B 58

Table B.S

610B 78610B 83

l-agr(Lp/L)min(Lp>Mr = <LP/L>min * Ugr( Lu )agr = L«gr ~ (Lp)tgr

Government enterprises^Federal

Lfefed

(Lp/L)non,ovioi

SL * ^ a l l d l 0 C a '

(Lp/Dnongovto,(Lp>««l - (Lp/L) n o n g o v t o l X L ^ ,(Lp)tetocal = (Lp).efed + (Lp)«e*lLgetoul= Lgefed + Lie$ |(Lu)««oul = Lgetoul -(Lpjgwo,,!

TOTAL TRADE L,, = Lwhlr + Lreur

Wholesale trade Lwhtr = (Lu)w h l r

Retail trade Lret,r = (Lu)reUr

Building rent Lbr = Lr ( r-L, r

ROYALTIES Lr = Lfi + L,r

Finance and insuranceLflrsLfire-LreLfire = (Lu)fire

Lre=total real estateGround rent

L«r = L r e xg

g

DUMMY Ld = L,o v n t f e d + L,ovnl s l

GovernmentFederal = L, o v m f e d

State and local = LgovntS|

TOTALSLLp

LU = L - L P

Lp/LL p /L u

thousands

thousandsthousands

thousands

thousands

thousands

thousandsthousandsthousandsthousands


thousands


thousands

thousands

thousandsthousands


6,6250.9116,038

587

5380.831

447

2110.831

175623749126

10,6902,8397,851

435

1,420

1,2521,855

603

1680.28

6,063

2,9223,141

58,30132,99425,3070.5661.304

6,4400.9025,810

630

5700.822

469

2210.822

182650791141

10,6222,7837,839

415

1,453

1,2941,868

574

1590.28

6,487

3,1143,373

56,91931,20125,7180.5481.213

6,4020.9065,798

604

5530.823

455

2340.823

193648787139

10,7892,8187,971

424

1,517

1,3571,941

584

1600.27

6,718

3,2303,488

58,60032,22626,3740.5501.222

6,0220.9045,445

577

5780.817

472

2460.817

201674824150

11,2822,9808,302

437

1,608

1,4452,045

600

1630.27

8,518

4,9573,561

62,36633,12329,2430.5311.133

5,8790.8925,244

635

6200.806

500

2840.806

229729904175

11,4653,0568,409

443

1,698

1,5352,141

606

1630.27

9,218

5,5553,663

63,45732,76830,6890.5161.068

5,6%0.8835,032

664

5990.802

480

2920.802

234714891177

11,5863; 1038,483

453

1,794

1,6302,247

617

1640.27

9,204

5,3903,814

64,24733,04331,2040.5141.059

5,7130.8674.9SS

758

5990.792

474

2930.792

232706892186

11,4713,0928,379

466

1,883

1,7162,349

633

1670.26

9,049

5,0703,979

62,32431,23031,0940.5011.004

5,5250.8594,744

781

5970.788

471

3000.788

236707897190

11,7573.1648,593

476

1,957

1,7882,433

645

1690.26

8,939

4,7%4,143

63,36631,71431,6520.5001.002

5,2510.8544,484

767

6030.780

470

3020.780

236706905199

12,1273,3078,820

479

2,046

1,8792,525

646

1670.26

9,031

4,6674,364

64,52231,86432,6580.4940.976

5,0100.8394,205

805

6220.771

479

3050.771

235714927213

12,1853,3188,867

463

2,131

1,9712,594

623

1600.26

9,209

4,6414,568

64,77931,43333,3460.4850.943

4,8480.8143,944

904

6330.756

478

3200.756

242720953233

12,0703,2958,775

456

2,172

2,0172,628

611

1550.25

9,231

4,4294,802

62,76529,34933,4160.4680.878

4,7040.8063,791

913

6450.753

486

3520.753

265751997246

12,2623,3518,911

460

2,208

2,0532,668

615

1550.25

9,309

4,3654,944

64,09930,02034,0790.4680.881

4,5310.8013,627

904

6640.748

4%

3720.748

278774

1,036262

12,4%3,4219,075

458

2,2%

2,1392,754

615

1570.25

9,545

4,3915,154

64,98930,04734,9420.4620.860

4,4420.7923,517

925

6800.739

503

3680.739

272775

1,048273

12,3533,4198,934

448

2,336

2,1812,784

603

1550.26

9,894

4,4775,417

64,74029,36335,3770.4540.830

g Table F.I fcont.)

Sources"

610B 13SEHE*SEHE

610B7SEHESEHE

610B 12SEHESEHE

610B 37SEHEf

SEHE

610B60SEHEf

SEHE

60160

Sectors

PRODUCTION Lp

Manufacturing

Lman(Lp)m.nLman( L p / L ) m a n

(Lp )m a n = ( L P / L ) m a n x Lm a n

(Lu)man = L,n an-(Lp) m a n

Mining

Lmin(Lp)min

L'min

( L u ) Z = LmP

in-(Tp)minmn

Construction

Leon(L'p)eonLeon

(Lp)C On=n (Lp/L) c o nxLc o n

(Lu)con = LCon ~ (Lp)ConTransportation and public utilities

L,u,(L'p),u,L',m(L p /L) | u l

(Lp)iui=(Lp/L)JH,xL,HI

(Lu)(ut = Lt u l — (Lp)tutServices''

Lserv(Lp)servLirv

(L p)$ e r v = (Lp /L) i r v X Ljerv(GNPprJserv rf

GNPjerv(GNPpr /GNPJjerv(Lp)^v = (GNP p r/GNP)i e r v X ( L p ) ^(L u )K r v = L $ e r v - (L p ) $ e r v

Units

thousands


thousandsthousands


U1V/U9A1IU3

thousands


thousandsthousands


thousandsthousands


thousandsbillions of $billions of $

, thousandsthousands

1962

29,937

16,65812,48816,8530.741

12,3444,314

666512650

0.788525141

3,5412,5002,9480.8483,003

538

3,9893,4653,9060.8873,539

450

10,3107,3697,9820.9239,51839.459.20.6666,3353,975

1963

30,013

16,77612,55516,9950.739

12,3934,383

647498635

0.784507140

3,6192,5623,0100.8513,080

539

3,9763,4513,9030.8843,516

460

10,5977,6318,2770.9229,77042.263.30.6676,5134,084

1964

30,280

17,00612,78117,2740.740

12,5834,423

642497634

0.784503139

3,7282,6373,0970.8513,174

554

4,0083,4903,9510.8833,540

468

10,9207,9398,6600.917

10,01145.769.00.6626,6304,290

1965

31,365

17,90213,43418,0620.744

13,3154,587

644494632

0.782503141

3,9032,7493,2320.8513,320

583

4,1083,5614,0360.8823,625

483

11,3068,2959,0360.918

10,37949.374.60.6616,8594,447

1966

32,566

19,11214,29619,2140.744

14,2204,892

640487627

0.777497143

3,9852,8183,3170.8503,386

599

4,2403,6384,1580.8753,710

530

11,8748,7499,4980.921

10,93854.382.50.6587,1994,675

1967

32,856

19,33514,30819,4470.736

14,2265,109

624469613

0.765477147

3,9652,7413,2480.8443,346

619

4,3303,7184,2680.8713,772

558

12,4439,246

10,0450.920

11,45359.990.60.6617,5724.871

1968

33,445

19,64214,51419,7810.734

14,4125,230

618461606

0.761470148

4,0842,8223,3500.8423,440

644

4,3943,7574,3180.8703,823

571

12,8219,727

10,5670.921

11,80265.999.10.6657,8484,973

1969

34,125

20,05714,76720,1670.732

14,6865,371

626472619

0.763477149

4,2563,0123,5750.8433,586

670

4,4883,8634,4420.8703,903

585

13,31310,20511,1690.914

12,16473.4

110.50.6648.0805.233

1970

33,247

19,17714,04419,3670.725

13,9065,271

629473623

0.759478151

4,1792,9903,5880.8333,483

697

4,5303,9144,5150.8673,927

603

13,38010,48111.5480.908

12.14480.2

121.20.6678.1035,277

1971

32,727

18,33613,54418,6230.727

13,3355,001

617455609

0.747461156

4,2613,0713,7040.8293,533

728

4,4983,8724,4760.8653,891

607

13,57710,65511,7970.903

12,26387.3

130.20.6718,2225,355

1972

33,896

18,81914,04519,1510.733

13,8025,017

625475628

0.756473152

4,4993,2573,8890.8373,768

731

4,5463,9434,5410.8683,947

599

14,20011,05912,2760.901

12,79296.8

144.60.6698,5645,636

1973

35,462

19,87114,83420,1540.736

14,6265,245

641486642

0.757485156

4,8353,4054,0970.8314,018

817

4,6704,0344,6560.8664,046

624

14,87911,60612,8570.903

13,431107.9163.20.6618.8805,999

1974

35,657

19,80414,63820,0770.729

14,4395,365

701530697

0.760533168

4,8163,2944,0200.8193,946

870

4,7444,0794,7250.8634,095

649

15,31312,10013,4410.900

13,785118.9179.40.6639,1366,177

1975

33,615

18,06213,04318,3230.712

12,8575,205

755571752

0.759573182

4,2962,8083,5250.7973,422

874

4,5843,8944,5420.8573,930

654

15,65012,47913,8920.898

14,058133.2199.80.6679,3726,278

Agriculture'610B4

610B81

610B86

61OB5O610B51

610B 52610B 58

Table B.5

610B 78610B 83

L«gr(Lp/LJInjj,(Lp)a g r = ( L p / L ) ^ i n x L t g r

(L u ) M r = L, g r - (Lp) a g r

Government enterprises'Federal

Lgcfcd(L p /L) n o n g o v t o l

(Lp)gef«j = (L p/L) n o n g o v t o t X Lg e f e d

St&tc &ncS Ioc&i

Lgcsl(L p/L) n o n g o v t o t

(Lp)ge»l = (Lp/L)n o n g o v t o t X Lge$)

(Lp)g«oi«l=(Lp)gefed + (Lp)geslLgetoul = Lgefed + Lge$l(Lu)getoi»l = L g e t 0 U | - (Lp ) g e l 0 U |

TOTAL TRADE L u = Lwhtr + LreUr

Wholesale trade Lwhtr = (Lu)w h t r

Retail trade Lr e u r = (Lu)r e u r

Building rent Lbr = Lre - Lgr

ROYALTIES Lr = Lfi + Lgr

Finance and insuranceLfl = L f i r e - L r e

Lf i r e=(Lu)f i r e

Lre = total real estateGround rent

i = Lre x gg

DUMMY Ld = Lg o v M f e d + Lg o v m $ l

GovernmentFederal = LgOvmfedState and local = Lg0VMsl

TOTALSLLp

LU = L - L p

Lp/LL n/L. .

thousands

thousandsthousands

thousands

thousands

thousands



thousands


thousands

thousands

thousandsthousands


4,3100.7883,395

915

6910.738

510

3890.738

287797

1,080283

12.4333,4488,985

456

2.380

2,2202.836

616

1600.26

10.268

4.7185,550

66,09129,93736,1540.4530.828

4,0790.7843,199

880

6940.736

511

3990.736

294804

1,093289

12.4993.4809.019

464

2.445

2,2802,909

629

1650.26

10,460

4,6575,803

66,65530,01336,6420.4500.819

3,8620.7843,027

835

7000.733

513

4200.733

308821

1,120299

12,8493,5559,294

465

2,504

2,3372,969

632

1670.26

10,770

4,6606,110

67,87430,28037,5940.4460.805

3,7130.7822,902

811

7180.734

527

4280.734

314841

1,146305

13,2133,6489,565

478

2,597

2,4233,075

652

1740.27

11,118

4,6716,447

70,12831,36538,7630.4470.809

3,4320.7772,666

766

7850.732

575

4290.732

314888

1,214326

13,6153,7829,833

490

2,676

2,4963,166

670

1800.27

12,023

5,2036,820

73,30132.56640,7350.4440.799

3,3380.7652,554

784

8240.725

598

4290.725

311909

1,253344

13,8223,8499,973

503

2,829

2,6423,332

690

1870.27

12,695

5,6267,069

75,13732,85642,281

0.4370.777

3,3030.7612,513

790

8350.725

605

4610.725

334939

1,296357

14,1793,920

10,259523

2,970

2,7733,493

720

1970.27

13,099

5,6967,403

76,92933,44543.4840.4350.769

3.1930.7632.435

758

8480.722

612

4790.722

346958

1,327369

14,6374,041

10,596539

3,114

2,9073.653

746

2070.28

13.325

5,6367,689

78,87534.12544,750

0.4330.763

3,1180.7592,367

751

8660.717

621

5070.717

363984

1,373389

14,8894,123

10,766559

3,190

2,9723,749

777

2180.28

13,251

5,2288,023

78,27533,24745,028

0.4250.738

3,0650.7472,290

775

8700.715

622

5210.715

373995

1.391396

15.1584.154

11.004596

3.240

3,0033,836

833

2370.29

13.198

4,8458,353

77,93732,72745,210

0.4200.724

3,1160.7562,357

759

8430.718

606

5300.718

381986

1,373387

15.4884,252

11,236619

3.340

3.0893.959

870

2510.29

13.231

4.5018,730

79,85633,89645,9600.4240.738

3,1810.7572,408

773

8380.717

601

5550.717

398999

1,393394

16,2094,492

11,717680

3,522

3,2404.202

962

2820.29

13.418

4,3569,062

83,29935.46247.8370.4260.741

3,2550.7602,475

780

8540.712

608

5960.712

4241,0321,450

418

16,5654,617

11,948697

3,637

3,3474,334

987

2900.29

13,630

4,3079,323

84,61235,65748,955

0.4210.728

3,1910.7592,423

768

8380.700

587

6440.700

4511,0371,482

445

16,5004,521

11,979695

3,710

3,4184.405

987

2920.30

13,902

4,2789.624

82.82733,61549.2120.4060.683

S?

2

>© V * d m"

-

« tw

> s s. ~ 2 5 § s

538,344 40229 38,312 39872 38088 37203 3636

361221350

,969 19,995 13,065 19

124 18,876 18092 12,877 12260 18,965 19

316 19,255 19530 13,285 13,434 19,378 19

607 18742 12781 18

OO

(S

0

0

683229132

.682 0,930 13,039 6

680 0.679 0000 12,817 12124 6,059 6

680 0.686 0450 13,201 13866 6,054 6

©

<s

«•>

733512713718526207

722515721.714 0516206

925 782658 545927 777710 0.701 0657 549268 233

960 975673 686952 966707 0.710 0679 692281 283

_ —

d

,377,990,110781

,167 6,902 3,998 5.781 0

043 6775 3816 4784 0

831 6659 3,673 4783 0

499 5406 3383 4777 0

8§S2

862 4998 3905 3768 0

•* <S

f>

©

,815 4,352 1

737 4306 1

566 4265 1

273 4226 1

807 4149 1

733 3129 1

•n

—

,615,574

,464 5,464 4

337 5345 4

,306 5,339 4

248 5261 4

,077 5074 4

136 5190 4

,385 5.829 0,529 4935

255 5827 0413 4924

,238 5828 0,395 4911

,129 5831 0360 4888

,954 5822 0175 4902

iSS

i«n

©

•

*

***S8

Ss

ss

ss

§S

§li

a 2* a ° a"

729 21880 17036 19887 0381 19

C5

«2

JO

«

0.85.2577386558

0.7 513.5 88.581 0,300 13.846 13

3.3 416.4 468.1 716.3 79591 0.581 0459 12,655 13470 12,132 12

7.3 380.2 64599 0134 12761 11

7.6 345.5 58616 0779 12792 10

--39

S00

£ ©

—

»

-r

~

o

« ^ OO Os O ^

00 f) <^

9\ h

^

i s 2 £ s s a. a 2 s a 8

* rn

•* © •* —

v-T V

«n © i/

wi m ^ O t -

v •*

«r> © *•

O\ir>^dr~»*}r--©©00

2" 2 E; « s: 8 S « 2

fl

« © © r- ©

*«o «•*

••

d •* -

<o* -»

vC © TT"

9i m is » vi

« <o

w — —

oor---vo*c

oo 2 * r-"

d « § S d o o

^

«r>" * d

^r -

«

-. •

«-. ©

*

r"d <•

2°, = 2

to is

-

!• 8 8

t«

e

m oo

S

e o r

S

2 2 2 ° 2!

'8 2 }S SS

{* « ^. -

!-

!•

!-!-!

P2 d 2 S 3 d

111

>gJJdJd^iJdJddd,

jX

i-r Z

)r/GNl

Ou

•j

Jij

1~* UJ

UJ

S X X

2 UJ UJ

o to co

g X X

2 uj

uj«

co cog X X

2 UJ w

« co co

*** W W

g x x

2 w UJ

VO CO tO

302

Agriculture'610B4

610B 81

610B86

610B SO6IOB51

610B 52610B 58

Table B.5

610B 78610B 83

L»gr(Lp/L)mjn

(Lp)agr = (Lp/L)min X La g r

(Lu)Mr = L M r - ( L p ) a g r

Government enterprises-^Federal

Lgefed(L p /L) n o n g o v t o l

(Lp)gefed — (Lp / L) n o n g o v t o t X Lgjf^State and local

Lgesl(Lp/L)nongovto<(Lp)gesl = (L p /L) n o n g o v t o ,xL g e $ 1

(Lp)getoial = (Lp)gefed + (Lpjgesl

(Lu)getotal= Lgetotal ~ (Lp)getotal

TOTAL TRADE L u = Lwhtr + LreItr

Wholesale trade L w h u = (L u) w h l I

Retail trade L r e u r =(L u) r e U r

Building rent Lbr = L r e - L g r

ROYALTIES Lr = Lfi + Lgr

Finance and insuranceLfi = L f i r e - L r e

Lflre = (Lu)fireL r e=total real estate

Ground rentL r = L r e X gg

DUMMY L d = L g o v m f e d + Lg o v M s ,Government

Federal = Lgovmfed

State and local = L g o v m s l

TOTALSLLPLU = L - L p

Lp/LL p / L u

thousands

thousandsthousands

thousands

thousands

thousands



thousands


thousands

thousands

thousandsthousands


3,2100.7602,439

771

8190.700

573

6450.700

4511,0251,464

439

17,0974,690

12,407718

3,789

3,4864,5071,021

3030.30

13,997

4,2489,749

85,15134,67750,4740.4070.687

3,1050.7602,360

745

8130.696

566

6500.696

4521,0181,463

445

17,8404,832

13,008757

3,951

3,6294,7081,079

3220.30

14,125

4,2349,891

88,11635,79852,3180.4060.684

3,1870.7502,389

798

8210.693

569

6800.693

4711,0401,501

461

18,8125,072

13,740822

4,196

3,8455,0181,173

3510.30

14,447

4,24410,203

92,53937,61054,9290.4060.685

3,1610.7512,372

789

8380.686

575

7000.686

4811,0561,538

482

19,4255,339

14,086885

4,420

4,0425,3051,263

3780.30

14,568

4,21110,357

95,52538,59856,9270.4040.678

3,2120.7422,383

829

8460.675

571

7300.675

4931,0641,576

512

19,3955,3%

13,999901

4,580

4,1955,4811,286

3850.30

14,774

4,26810,506

95,73437,86357,8710.3%0.654

3,1220.7382,305

817

8520.667

568

7270.667

4851,0531,579

526

19,6045,522

14,082882

4,740

4,3635,6221,259

3770.30

14,741

4,28510,456

96,58237,73858,844

0.3910.641

3,1570.7282,298

859

8360.656

548

7280.656

4781,0261,564

538

19,4195,409

14,010892

4,833

4,4525,7251,273

3810.30

14,657

4,30710,350

94,99036,20358,7870.3810.616

3,0740.7072,173

901

8340.650

542

7430.650

4831,0251,577

552

19,8155,409

14,406942

4,%7

4,5655,9091,344

4020.30

14,697

4,34010,357

95,95236,08859,8640.3760.603

3,0520.7102,167

885

8540.647

553

7600.647

4921,0441,614

570

21,0385,697

15,341986

5,151

4,7306,1371,407

4210.30

14,894

4,39510,499

100,60737,87262,735

0.3760.604

2,9530.7102,0%

857

8600.640

551

7910.640

5061,0571,651

594

21,7475,804

15,9431,029

5,334

4,8946,3631,469

4400.30

15,202

4,43810,764

103,03138,22964,8020.3710.590

2,9640.7012,079

885

8560.634

542

8220.634

5211,0631,678

615

22,2155,834

16,3811,057

5,609

5,1576,6661,509

4520.30

15,483

4,44011,043

104,83138.31266,519

0.3650.576

3,0380.7142,170

868

8810.632

557

8330.632

5271,0841,714

630

22,9435,991

16.9521,111

5,849

5,3746,6901,586

4750.30

15,768

4,48311,285

107,89139,34468,5470.3650.574

3,0680.7182,216

870

90S0.630

570

8480.630

5341,1051,753

648

23,5586,149

17,4091,157

5,925

5,4317,0821,651

4940.30

16,003

4,48311,520

110,96240,53870,4240.36S0.576

3,0420.7132,169

873

9170.626

574

8680.626

5441,1181,785

667

24,3756,399

17,9761,168

5,955

5,4567,1231,667

4990.30

16,324

4,50411,820

113,51141,14872,3630.3630.569

s

" Unless otherwise indicated, all data come from NIPA (e.g. BEA 1986), where the first three digits (and following letter, if any) denote the relevant table number and subsequent digits the line numbers within those tables.* Supplement to Employment, Hours, and Earnings, United States, 1909-84 (BLS 1989). SEHE and its subsequent editions are the main source of Lp and L' of all sectors except agriculture, services, and government enterprises.c For the period 1948-63, the data on L'p and L' of transportation and services were not available in SEHE. Hence, for the period in question the data were obtained by extrapolation.' T o determine the share of production workers in the productive subsectors of services (BEA 1986, table 610B, lines 61, 62, 64-68, 70-73), we used the GNP share of those subsectors as a proxy.' For the ratio of production to total workers in agriculture, we used the mining sector's ratio, owing to the lack of appropriate data.' F o r the ratio of production to total workers in the government enterprises, we used the average ratio based on private sectors.

Wages and variable capital

Our primary database for wages comes from NIPA. We use employeecompensation (EC) because it includes wages and salaries of employeesas well as employer contributions to social security. This is the appropri-ate base for estimates of variable capital, since it represents the total costof labor power to the capitalist.

A combination of BLS and NIPA data is used to estimate the wage perproduction worker. This is then applied to the estimate of the number ofproductive workers from Appendix F to derive the total wage bill of pro-ductive labor (variable capital). The wage bill of unproductive workers isderived as the difference between total NIPA wages and total variablecapital. The basic steps involved will now be outlined.

Starting with the NIPA measure of employee compensation EC, wemake two adjustments. First, because EC covers only employees whereasour measure of total employment L includes both employees and self-employed persons, we need to make some estimate of the wage equivalentof self-employed persons. Second, we must split the resulting measure oftotal wages into wages of productive and unproductive workers. Let

EC, = total employee compensation in they th sector (NIPA);

FEE, = total full-time equivalent employees in they th sector (NIPA);

ecy = (EC/FEE)y = employee compensation per full-time equivalentemployee;

W, = ecy • L, = estimated total wage

= employee compensation and wage equivalent of self-employed persons in they th sector;

W = 2 W, = aggregate total wage (including wage equivalent).

304

Wages and variable capital 305

See Table G.I.Having expanded our measure of wages to encompass the wage equiva-

lent of self-employed persons, we turn to its division into the wages ofproductive and unproductive workers.1 The first step is to derive an esti-mate of the unit employee compensation of productive workers (ecp).We have:

(wp)j = unit wage of production workers in they th production sector,y = l,...,A:(fromBLS);

Xj B (EC/WS)y = ratio of employee compensation to wages andsalaries in the j th production sector, j = 1,..., k(from NIPA);

(ecp)y B (wp)y • (x7) = estimated employee compensation of productionworkers in they th production sector.

For services, long-term data on wp and x were unavailable, so we assumedproductive workers in services had the same wage as the average serviceworker: (ecp)serv = ecserv.

Given W and the various (ecp)7 just derived, together with the datafrom Appendix F on the numbers of productive and unproductive work-ers (Lp,Lu), we can derive the wage bill of productive workers (W p seCp-Lp) as well as the wage bill and wage rate of unproductive workers(Wu = W-Wp, ecu = Wu/Lu).2 We have:

Wj s (ecp)y • (Lp)y s (Wp)y = variable capital in the j th production sector;

V* s Wp = S ( Wp)y = total variable capital;

Wu B W - V* = total wages of unproductive workers in all sectors;

ecp = Wp/Lp = average wage of productive workers;

ecu = Wu / L u = average wage of unproductive workers.

See Table G.2.Finally, there are two implicit aspects of our procedure upon which we

can cast some empirical light; both relate to our use of employee compen-sation as the base for wages and salaries. Employee compensation in-cludes corporate officers' salaries (COS). These should be excluded fromvariable capital because they actually represent income of capitalists, notwages of workers (Mage 1963, pp. 188-9). Indeed, our method effectively

1 If we could safely assume that production and nonproduction workers have thesame wage, then we could use the ratio Lp/L to split total wages W. But we shallsee that wp is not the same as wu, which is why we adopt our own procedure.

2 The BLS does not publish data on the wage rates of nonproduction workers.

306

SS

33

81

R

R£

S*

.|

5

I^

m vp M

^

O

r<i

<s3 £

8*

8

8 *

£«

•»

-«

••

• « -

v»

^ to

oo

^ ^

<> ^

io o

^

*o

v> v* t-

r- •**

v» v» «

?** *r\ *f Q

s

SS

2$

1

25

9.

2S

S 8

SS

5 S

I

S 2 K

K

88

?

- N *

"*

S

JQ

"»* * * 8

5

°°* "

* 8

"»

-*

« "

• °*

"»* -

•»

I||SI

5.SSSS. 8.8581

S-S^|5

llili«r*

\©

*r» s©

t* *

•

NO

^

N©

<s *o

m ©

^

m

^ ^

^

oo h

o

O

i ^

Sasls

ggSES Sg|S|

S.|S|8 =S.2S|

S2

"2

"

**

"*

"*

>

Qis<

r>

«n

o»

N m

«i •

• m

v

or

^m

Os

ri

O

so «n

hs§6.aa

22

25

5 la

.ns

^SS

.v

Tis

v^

co

oT

w

* »n ^

jt

j* h-" n

ov O

c

n~

«*

^ r*«*

••

c*> »

o

ON

•*>

ON

O

^*

^

vr

tm

OS

"-

* ^

h

9

«

O

oo

O

N O

N O

N

•*

oo

O

N O

O

N

Sa

2.

5S

o

ss

aS

fs

la

ss

s I

ss

SI

. q

js

ss

aa

s§

8

* "

"

"•

2

**•" **

™ 2

s

^* "°*

* a"

a

•*"" ^

°°"

a*

*•* ~

™

^* *

N"

~ w

"

| r

r:- I

SS2 g

S21S

S*n

V

•*

rj ^

"""

™

2*

2* "*

"* "*

3s3SS

jo

t~* •» r£

oo*

5 Sai^g SSliS SSIIS 8S2

" * 2

* •* "*

"* 9

oo*

vo" is

oo* is*

r»" —

* —

* *S ©C

is* —

«n*

111-11 W35!

- n

«

no

»

m _

IA

Z

« r<

o^ 35 f

i

8

!£

m*

-" S

os in

to h

oo

N

V*>

©

—

I-

OO

- 35

*

<K

vo K

-

- -_

n

q•**

O «

s en

tn V

j£

'*"'»*

"*" «*

o* o* n

-

- «

O

IS

* is"

3°, p s =

I' m

rS «

o

«n

IN r

; «ni~

*^

*n

'»"

oo

f»*

— r;

KI »

vo

—

*f»

*o

< n

«

*

. !

. .

1-

is m

f> o

§S

»2

5;

KP

SS

=

2p

H»

2

JS S

2

"*. -

. *l

"1 -

. -

. -. -

. •*•. ""1

w

. 9

. *

. «.

«.

«.

3 «1

2

"* ^

* 2

2 *

N ^

2

«n

is -

«O

O

- is

ra1)

Hill Hill llill Hill Hill Hill 111

^ is

SS

3

ea en

ea

6O4B506O7B5O

610B 50

6O4B5I6O7B51

6IOB51

6O4B52

6O7B52

61OB 52

604B586O7B58

610B 58

Table B.5

6O4B786O4B83

TOTAL TRADEWholesale trade

ECwhtr

FEEwhlr

ecw h l r=(EC/FEE)w h t r

LwhirW w h , r = e c w h C r x L w h t r

Retail tradeECr e M r

FEEre,,r

ecreUr = (EC/FEE)r e U r

LrcrW r e , ,r=ec r e t l r xLr e U r

Building rental

wbr=wre-w,rROYALTIESFinance and insurance

ECfi = E C f i r e - E C r e

ECB r e

FEEfi = F E E f i r e - F E E r e

FEEfire

ecfi = (EC/FEE)fiLfi = L f l r e - L r e

Lfire

Wf i=ec f i xL f i

Ground rentEC r e

FEEr e

ecr e = (EC/FEE) r e

W r e = e c r e x L r e

gW g r = W r e x g

DUMMYGovernment"

E C g o v f e d

EC,OV$1

W , o v t « = E C , o v f e d + EC,OV$I

W=Tota l EC and WEQ

millions of $thousandsdollarsthousandsmillions of $

millions of Sthousandsdollarsthousandsmillions of $

millions of S

millions of Smillions of Sthousandsthousandsdollarsthousandsthousandsmillions of S


millions of S

millions of Smillions of $millions of $millions of $

9,5682,5863,7002,839

10,504

15,1705,8522,5927,851

20,352

1,083

4,0335,1861,1721,6353,4411,2521,8554,308

1,153463

2,490603

1,5020.28

419

9,5568,521

18,077164,763

9,4312,5283,7312,783

10,382

15,5%5,8052,6877,839

21,061

1,039

4,3255,4481,2141,6633,5631,2941,8684,610

1,123449

2,501574

1,4360.28

397

10,6799,442

20,121164,753

10,0862,5593,9412,818

11,107

16,7515,9422,8197,971

22,471

1,136

4,7786,0291,2751,7423,7471,3571,9415,085

1,251467

2,679584

1,5640.27

428

11,09510,14521,240

178,761

11,3542,7154,1822,980

12,462

18,1756,2752,8%8,302

24,406

1,238

5,3126,6401,3571,8263,9151,4452,0455,656

1,328469

2.832600

1,6990.27

461

16,58211.15927,741

206,232

11,9362,7844,2873,056

13,102

19,1766,3843,0048,409

25,259

1,298

5,8477,2071,4381,9024,0661,5352,1416,241

1,360464

2,931606

1,7760.27

478

19,27512,25231,527

222,097

12,6652.8304,4753,103

13.887

20,4346,4823,1528,483

26,742

1,401

6,4407,8701,5241,9864,2261,6302,2476,888

1,430462

3,095617

1,9100.27

509

19.07513.33432,409

236,846

13,0292,8214,6193.092

14,281

20,9296,4053.2688,379

27,379

1,534

7,0308,5711,5922,0604,4161,7162,3497,578

1,541468

3,293633

2,0840.26

550

18,34614,69833,044

235,670

13,9192,8914,8153,164

15,233

22,3926,5703,4088,593

29,287

1,655

7,6069,3091,6732,1634,5461,7882,4338,129

1,703490

3,476645

2,2420.26

587

18,95815,83834,7%

252.731

15.4483.0315,0973,307

16,855

23,9086,7813,5268,820

31,097

1,771

8,33110,178

1,7692,2684,7091,8792,5258,849

1,847499

3,701646

2.3910.26

620

19,60417,62037,224

272,671

16,3273,0415,3693,318

17,814

25,1296,8113.6898,867

32,715

1,782

9,05610,8%

1,8612,3394,8661,9712,5949,591

1,840478

3,849623

2,3980.26

616

20,22719,55639,783

286,751

16,7893,0175,5653.295

18,336

25,5616,6983,8168,775

33,487

1,777

9,84011,669

1,9082,3775,1572,0172,628

10,402

1,829469

3,900611

2,3830.25

606

21,32521,57842,903

289,269

18,0743,0695,8893,351

19,735

27,6266,9004,0048,911

35,678

1,908

10,71312,704

1,9462.4265,5052,0532,668

11,302

1,991480

4,148615

2,5510.25

642

21,71423,13344,847

311,712

19,1723,1326,1213,421

20,941

29,5537,1004,1629,075

37,774

1,937

11,49113,5192,0312,5115,6582,1392.754

12.102

2,028480

4,225615

2,5980.25

661

22,58825,47048,058

328,351

19,7813,1306,3203,419

21,607

30,1027,0404,2768,934

38,200

2,002

12,39414,4862,0732,5415,9792,1812,784

13,040

2,092468

4,470603

2,6950.26

693

23.64027,93451,574

338,075

3

00Table G.I (cont.)

Sources"

604B13607B13

610B 13

604B7607B7

610B7

6O4B12607B12

610B 12

6O4B37607B37

610B 37

604B60607B60

610B60

604B4607B4

610B4

6O4B81604B86

Sectors

PRODUCTIONManufacturing

E C ^ nFEE,™ccI M n = (EC/FEE)m a n

Lm«nWmmn=CCmanXLnian

MiningECm i n

FEEmin

ecm i n = (EC/FEE)n i i n

LminWmjn=ecmjn x L m i n

ConstructionECco,,FEEcon

ec c o n =(EC/FEE)c o n

Lc o n

WCoo=ecc o l ,xLc o n

Transportation and public utilitiesECtu,FEEtu,ectu, = (EC/FEE),u,L,u,W, u t =ec t u t xL , u l

ServicesE C ™FEE™ecseTV=(EC/FEE)™L ™W$ e r v=ec $ e r vxLj e r v

AgricultureECM r

FEE^re c n r = ( E C / F E E ) M r

L v

W v = e c M r x L a g r

Government enterprises*ECvM

EC^,,W^oul=EC i e f e d + EC«$l

Units

millions of $thousandsdollarsthousandsmillions of S


millions of Sthousandsdollarsthousandsmillions of S




millions of Smillions of $millions of S

1962

107,92816,3606,597

16,658109,894

4,429640

6,920666

4,609

18,9692,8556,6443,541

23,527

26,4773,8076,9553.989

27,743

35,6898,3984,250

10,31043.814

4,0571,7232,3554,310

10,148

3,9682.1926,160

1963

112,50316,4846.825

16,776114,496

4,462623

7,162647

4,634

20,2792,9396,9003,619

24,971

27,4363,7957,2303,976

28,745

38,2318.6394,425

10,59746,896

4,2021,6772,5064,079

10,221

4,3112,3256,636

1964

119,95516,7227,173

17,006121,992

4,652619

7,515642

4,825

22.1163.0497,2543.728

27,041

29,2213,8277,6354.008

30.603

41,4558,9234,646

10,92050,733

4,3271.5522,7883,862

10,767

4,5862,5747,160

1965

129,48417,6247,347

17,902131,526

4,859624

7,787644

5,015

24,1673,2217,5033,903

29,284

31,1233,9267,9274,108

32,566

45,0899,3174,839

11.30654.715

4,5291,4763,0683,713

11,393

4,9142,7777,691

1966

144,51518,8527,666

19,112146,508

5,135621

8,269640

5,292

26,6753,3278.0183.985

31,951

33,7004,0638,2944,240

35,168

50,2089,8225,112

11,87460,697

4,6851.3823.3903,432

11.635

5.4013,0008,401

1967

151,42919,0687,942

19,335153,549

5,303604

8,780624

5,479

27,8003,3018.4223,965

33,392

35,8864,1458,6584,330

37,488

55,55110,3695,357

12,44366,662

4,7721,3143,6323,338

12,122

5,7913,2279,018

1968

165.42719,3868,533

19,642167,612

5,569599

9,297618

5,746

31,1363,4189,1094,084

37,203

39,0604,2099,2804,394

40,777

61,80610,7415,754

12,82173,775

5,0491,2983,8903,303

12,848

6,4593,658

10,117

1969

179,75619,7899,084

20,057182,190

6,176611

10,108626

6,328

35,1653,5629,8724,256

42,016

42,7594,3039,9374,488

44,597

70,36011,1366,318

13,31384,115

5,4551,2744,2823.193

13,672

7,0764,094

11,170

1970

181,13518,9069,581

19,177183,731

6,704615

10,901629

6,857

37,4693,481

10,7644,179

44,982

46,9984,341

10,8274,530

49,044

77,66911,2476,906

13,38092,399

5,7641,2804,5033,118

14,041

8,3774,597

12,974

1971

185,22418,08710,24118,336

187,774

6,982602

11,598617

7,156

40,7483,538

11,5174,261

49,075

50,9994,2%

11,8714,498

53,397

84,74311,4287,415

13,577100,679

5,9001,2764,6243,065

14,172

8.8295.140

13,969

1972

203,87618,57110,97818,819

206,599

7,715612

12,606625

7,879

44,4743,739

11,8954,499

53,514

56,4294,339

13,0054,546

59,121

95,04612.0037,919

14,200112,443

6,2601,2934,8413,116

15,086

9,5905,606

15,196

1973

230,71619,60511,76819,871

233,846

8,595626

13,730641

8,801

50,5604,011

12,6054,835

60.947

63,0884,475

14,0984,670

65,837

107,83912,6808,505

14,879126,541

7,4661.3685.4583,181

17,361

10,4246,433

16,857

1974

250.65419.53812,82919,804

254.067

10.457685

15,266701

10,701

53,9853,928

13.7444,816

66.189

68.9284.524

15.2364,744

72,280

120,64213,0459,248

15,313141,617

8.6111.4585,9063,255

19,224

11,8247,352

19,176

1975

252,54017,78314,20118,062

256.502

12.923739

17,487755

13,203

52,8603,442

15,3574,296

65,975

72,9134,357

16,7354,584

76,712

133,80513,35110,02215,650

156,846

9,2131,4406,3983.191

20.416

12,9768,502

21,478

6O4B50607B50

610B 50

6O4B51607B51

610BS1

6O4B52

607B52

610B 32

6O4B586O7B58

610B 58

Table B.5

604B786O4B83

TOTALTRADEWholesale trade

ECw h l r

FEEwhtr

ecw h l r = (EC/FEE)w h l r

LwhtrWwhir = eCwhtrXLwhtr

Retail tradeECrettr

FEEreUr

ecrettr = (EC/FEE)ret tr

Lr e u r

W r e u r =ecr e U r xL r e U r

Building rental

wb r=wr e-wg rROYALTIESFinance and insurance

ECfi = EC f i r e -EC r e

ECfire

FEEfi = FEEf i r e -FEEr e

FEEfire

ecfi = (EC/FEE)fi

Lfi = L f i r e - L r e

LftreWf i=ecf ixLfi

Ground rentECre

FEEre

ecre = (EC/FEE)r e

Wre = e c r e x L r e

gW v = W r e x g

DUMMYGovernment*

EC g o v f e d

ECgov$1

Wgovto. = ECg o v f e d + ECg o v s ,W=Total EC and WEQ



millions of S

millions of Smillions of $thousandsthousandsdollarsthousandsthousandsmillions of $

millions of Sthousandsdollarsthousandsmillions of S

millions of S

millions of $millions of $millions of $millions of $

20,8753,1616,6043,448

22,770

32,1757,1984,4708,985

40,163

2,114

13,09515,3202,1122,5926,2002,2202,836

13,765

2,225480

4,635616

2,8550.26

742

25,19430,24355,437

360,886

21,9883,1936,8863,480

23,964

34,1827,3644,6429,019

41,864

2,246

13,95316,3392,1732,6666,4212,2802,909

14,640

2,386493

4,840629

3,0440.26

799

26,46432,85759,321

379,432

23,4963,2687,1903,555

25.559

36,7027,6434,8029,294

44,630

2,365

15,03417,5692,2312,7296,7392,3372,969

15,748

2,535498

5,090632

3,2170.26

852

28,51335,87364,386

406,662

25,2643,3727,4923,648

27,332

39,5007,9414,9749,565

47,578

2,501

16,13018,8512,3172,8376,9622,4233,075

16,868

2,721520

5,233652

3,4120.27

911

29,96239,29469,256

436,635

27,8383,5017,9513,782

30,072

42,8798,3015,1669,833

50,793

2,691

17,54620,497

2,3872,9247,3512,4963,166

18,347

2,951537

5.495670

3,6820.27

991

34,27944,11578,394

480,940

29,8493,5858,3263,849

32,047

45,9668,5415,3829,973

53,673

2,819

19,45722,5352,5253,0747,7062,6423,332

20,359

3,078549

5,607690

3,8690.271,049

37,84749,53087,377

515,034

32,4793,6688,8553,920

34,710

50,7658,8675,725

10,25958,734

3,1%

22,01125,530

2,6573,2338,2842,7733,493

22,972

3,519576

6,109720

4,3990.271,202

41,87155,89897,769

566,661

35,8873,7829,4894,041

38,345

55,9279,1806,092

10,59664,554

3.587

24,19828,210

2,7843,3878,6922,9073,653

25,267

4,012603

6,653746

4,9630.281,376

44,88062,601

107,481624,698

38,9043,864

10,0684,123

41,512

60,2509,3296,458

10,76669.531

4.044

26,36830,9222,8623,4919,2132,9723,749

27,381

4,554629

7,240777

5,6260.281,582

48,40771,067

119,474667,551

41,4603,891

10,6554,154

44,262

65,0409,5246,829

11,00475,147

4,616

28,79433,956

2,8983,5649,9363,0033,836

29,837

5,162666

7,751833

6,4560.291,841

51,06779,255

130,322712,247

45,6294,005

11,3934,252

48,443

71,2509,7647,297

11,23681,991

5,254

31,80337,7742,9893,692

10,6403,0893,959

32,867

5,971703

8,494870

7,3890.292,135

54,85887,732

142,590783,118

51,5874,230

12.1964,492

54,782

79,09710,2817,694

11,71790,145

6,173

34,94241,993

3,1193,896

11,2033,2404,202

36,298

7,051in

9,075962

8,7300.292,557

57,10897,933

155,041875,185

57,9024,342

13,3354,617

61,569

86,22810,4658,240

11,94898,447

6,611

38,62846,020

3,2414,020

11,9193.3474,334

39,891

7,392779

9,489987

9,3660.292,755

61,052107,647168,699961,227

61,3904,260

14,4114,521

65,151

93,00710,5018,857

11,979106,098

6,824

43,34950,934

3,2914,064

13,1723,4184,405

45,022

7,585773

9,812987

9,6850.302,861

66,542121,109187,651

1,024,738

8

1-I-IIia IP|3S.

i.H.

S

00

O

^K

C* 1!

^K

C

*l C

9

^fr

^fr

^*

^O

^

^

^D

*O

P

** 'O

C

O

*^

C

O

V>

t*""

CM

C

O

*^

C

O

CO

C

O)

«

m

^

«n

<N

^t

co

*r\ m

O

N

O

m

—

a

(S

<N

N

Os

<

N

—

^t

| ^

* f^

^

^

^f

f>|

i/^ ^

*

^s| f*»

••«

^5

K

t*

'O

F"*

00

*^

^

f G

>

fO

t"** I*"*

V©

^*

00

^

* O

p

00

*O

>O

vt

^~

«

Ot

N

N

t 3

56

ON

vo

I—

00

N

«o

^

r-

^

n

X

* J

O\

«

O

m

^5

'O

—

^

^

^^

^r

^"

>

^t

**

r"

**

i^

i^

' ^

^^

oo

^<

*>

o

v>

ii

i-

«^

w

«

A

h

o

%•

SM

rn

SS

S

S

?

«N

f «N

S

S

^r

o^

O

ro

«s

f5

<S

^

^

"" 2

w

^

88

iq

SS

.aSS

^21.85

iss

i.S

81.85.5. g.SJ

, ^ -

--

2* M" R R* a* R

SE8.38 SiSsI

SSsss SSSSS SS.S

ESIa" s 5

£ 8 £ i

« « M

*0ri»>oo

^ r>

o* i-T

r~*

oo*

©

f"

«n

* — <N — O

ft

rn

S^

9

O r4 h ^

t O O> (S

m^^t^<so

N oo *o N

S88R 52323 ??2SS SS8.2S

2* a" 2 §

p; -

s - R

s; w* a*

* g | * s

§

J S 8

13 B

Ia 2 a

r»> O «*>*«-<

o w-i ec — —

o <> «n » I

SP882 S2S!2S S3 SR

5 as

a | S-S-R r'r'

I

N.

*T. "

. "T. °°. a.

«

5^

5,

I-; -

. IO

1112P.S

Ei.5|a S.2as|

a-a-R s^

88.SI.5

PSESS

§|82 8j a" a* s"

s

5s

s«

s $

2:g

a?

PS

SS

SJ

J2

R

S1111 |5

2.S| H

I32

li

m

8.8.§|| g§31S

?3

°>

£i

m

a

=

!o

m?

o

™R

££

§

SJ *

- ^

o7

Sm

£ ^

S

* o

I^

- ?5

!*N

N

«

«

i in

o?

oo

oo

ooI m

f^

K

—

. •*-. *i.

«N *

N

r; i~

r5

«o

K

©

©

»s *

>o

S

•* »

oo

^

a

2 • s

S5883

--

^v

er

rj

s s

V-

^j

g $

22

2j

c o

-T

,2"

a

12 21 12 2

i! lllll lII

iliil11

llill

2 "o

'Z "o ^

IO

i JJ

i §

=t

3 j

.Y fl

.1 fl

S «

>l

i ifX

g

ye

-di I

co

co

co

co

n

d

co

co

co

co

co

co

co

co

es

CO

OQ

OQ

CO

CO

gr

»©

S&

° S

S°

SS

° S

1"

*0

SS

° s

x

604B50607B50

610B 50

604B516O7B51

61OB51

604B52

607B52

610B 52

604B58607B58

610B 58

Table B.5

604B786O4B83

TOTAL TRADEWholesale trade

EC w h ( r

FEEw h l r

e c w h l r = ( E C / F E E ) w h l r

Lwh.rW w h l r = e c w h l r x L w h t r

Retail tradeECreMr

FEEreHr

ecr e U r = (EC/FEE) r e U r

LrcrW r e M r =ec r e l , r xL r e u r

Building rental

ROYALTIESFinance and insurance

ECfi = ECfire - ECr e

ECfire

FEEfi = FEEfire - FEEr

FEEfire

ec f i =(EC/FEE) f i

Lfire Bre

W f i =ec f i xL f i

Ground rentECr e

FEEree c r e = ( E C / F E E ) r e

LreW r e = e c r e x L r e

gW,r = W r eXg

DUMMYGovernment*

ECfOvfedEC™.W g ov ,oc=EC, o v W +EC, O V f l

W=Total EC and WEQ



millions of S

millions of $millions of $thousandsthousandsdollarsthousandsthousandsmillions of S


millions of S

millions of $millions of $millions of $millions of S

68.3564,408

15.5074.690

72.729

104.14510,9759,489

12,407117,734

7,634

48,36156,9513,3704,178

14,3503,4864,507

50,026

8,590808

10,6311,021

10,8540.303,221

70,871132,947203,818

1,140,356

75,9094,574

16,5964,832

80,191

115,07111,48110,02313,008

130,376

8,809

53,98363,857

3,5124,361

15,3713,6294,708

55,781

9,874849

11,6301,079

12,5490.303,739

75.528144.970220.498

1,268.469

86,5634,824

17,9445,072

91,013

129,90012,19510,65213,740

146,357

10,616

61,39973,101

3,7044,610

16,5763,8455,018

63,736

11,702906

12,9161,173

15,1510.304,534

81,685158,857240,542

1,433,637

99,0785,059

19,5855,339

104.562

143,47912,48911,48814,086

161,826

12,736

69,68783,222

3,9014,854

17,8644,0425,305

72,206

13,535953

14,2031,263

17,9380.295,202

86,918173,526260,444

1,610,759

110,1935.102

21,5985,3%

116,543

154,51512,37112,49013,999

174,849

14,045

80,25995,180

4,0485,018

19,8274,1955,481

83,174

14,921970

15,3821,286

19,7820.295,737

96,099192,154288.253

1.773.254

121.7805,225

23,3075,522

128,702

166,75812,47012,37314,082

188,315

14,950

90,236106,576

4,1895,166

21,5414,3635,622

93,984

16,340977

16,7251,259

21,0560.296,106

107,424209,314316,738

1.956,867

128,3045,125

25,0355,409

135,414

175,64912,40014,16514,010

198,455

16,080

101,325118,707

4,2525,229

23,8304,4525,725

106,091

17,382977

17,7911,273

22,6480.296,568

117,022226,877343,899

2,071,620

133,0665.089

26,1485,409

141,433

189,86712,72214,86614,406

214,158

18,353

113,703133,071

4,3635,370

26,0614,5655,909

118,967

19,3681,007

19,2331,344

25,8500.297,496

124,695241,695366,390

2,199,810

148,5265,371

27,6535,697

157,541

209,71613,72915,27515,341

234,340

21,067

123,984146,443

4,5225,587

27,4184,7306,137

129,687

22,4591,065

21,0881,407

29,6710.298,605

132,005258,885390,890

2,404,596

158,5775,496

28,8535,804

167,464

225,68914,44415,62515,943

249,111

23,542

137,267162.480

4,6835,800

29,3124,8946,363

143,452

25,2131,117

22,5721,469

33,1580.299,616

140,223278,752418,975

2,565,699

167,0565,537

30,1715,834

176,017

242,06614,86916,28016,381

266,681

25,506

157,281185,182

4,9376,109

31,8585,1576,666

164,290

27,9011,172

23,8061,509

35,9240.29

10,418

143,539300,260443,799

2,719,892

178,1935,676

31,3945.991

188,082

258,44215,40316,77916,952

284,432

28,485

175,194205,979

5,1456,362

34,0515,3746,960

182,992

30,7851.217

25.2961,586

40,1190.29

11,635

150,869322,081472,950

2,913,089

195,4865,812

33,6356,149

206,821

277,71415.91117,45417,409

303,861

32.136

188.986223,446

5.2016,458

36,3365,4317,082

197,343

34,4601,257

27,4141,651

45,2610.29,

13,126

159,313346,466505,779

3,152,110

209,7746,050

34,6736,399

221,875

293,38716.42817,85917,976

321,033

33,283

194,587230,329

5,2316,502

37,1995,4567,123

202,957

35,7421,271

28,1211,667

46,8780.29

13,595

168,550373.005541,555

3,337,038

' Unless otherwise indicated, all data come from NIPA (e.g. BEA 1986), where the first three digits (and following letter, if any) denote the relevant table number and subsequent digits the line numbers within those tables.* There are no self-employed persons in government, so the total wage of this sector is total employee compensation.


Glossary of variables in Table G.IECa g r Total employee compensation in agriculture, forestry, and fisheriesecagr Employee compensation per full-time equivalent employee (FEE) in

agriculture, forestry, and fisheriesEC c o n Total employee compensation in constructionecc o n Employee compensation per FEE in constructionECfire Total employee compensation in finance, insurance, and real estateECfi Total employee compensation in finance and insuranceecfi Employee compensation per FEE in finance and insuranceECg e f e d Total employee compensation in government enterprises (federal)ECgesi Total employee compensation in government enterprises (state and

local)ECg o v f e d Total employee compensation in government (federal)E C g o v s I Total employee compensation in government (state and local)ECman Total employee compensation in manufacturingecm a n Employee compensation per FEE in manufacturingEC m i n Total employee compensation in miningecmin Employee compensation per FEE in miningECr e Total employee compensation in real estateECrettr Total employee compensation in retail tradeecrcttr Employee compensation per FEE in retail tradeecre Employee compensation per FEE in real estateEC*™ Total employee compensation in serviceseCserv Employee compensation per FEE in servicesECt u t Total employee compensation in transportation and public utilitiesectut Employee compensation per FEE in transportation and public

utilitiesECw h t r Total employee compensation in wholesale tradeecwhtr Employee compensation per FEE in wholesale tradeFEEagr Total full-time equivalent employees in agriculture, forestry, and

fisheriesFEEc o n Total full-time equivalent employees in constructionFEEfire Total full-time equivalent employees in finance, insurance, and real

estateFEEfi Total full-time equivalent employees in finance and insuranceFEEm a n Total full-time equivalent employees in manufacturingFEEm i n Total full-time equivalent employees in miningFEEre Total full-time equivalent employees in real estateFEErcttr Total full-time equivalent employees in retail tradeFEEjerv Total full-time equivalent employees in servicesFEEtut Total full-time equivalent employees in transportation and public

utilitiesFEEwhtr Total full-time equivalent employees in wholesale trade


g Estimated proportion of land rent in the total revenue of the real estatesector

Lagr Total employment in agriculture, forestry, and fisheriesLc o n Total employment in constructionLfire Total employment in finance, insurance, and real estateLfi Total employment in finance and insuranceLman Total employment in manufacturingLmin Total employment in miningLre Total employment in real estateLrettr Total employment in retail tradeLserv Total employment in servicesLtut Total employment in transportation and public utilitiesLWhtr Total employment in wholesale tradeW Total employee compensation (including wage equivalent and COS,

corporate officers' salaries) in all sectorsWagr Total employee compensation (including wage equivalent and COS)

in agriculture, forestry, and fisheriesWbr Total employee compensation (including wage equivalent and COS)

in building rentalWcon Total employee compensation (including wage equivalent and COS)

in constructionWfi Total employee compensation (including wage equivalent and COS)

in finance and insurancewgetotai T o t ^ employee compensation in government enterprises (federal,

state, and local)Wgovtot Total employee compensation in government (federal, state, and local)Wgr Total employee compensation (including wage equivalent and COS)

in ground rentWman Total employee compensation (including wage equivalent and COS)

in manufacturingWmin Total employee compensation (including wage equivalent and COS)

in miningWrettr Total employee compensation (including wage equivalent and COS)

in retail tradeWre Total employee compensation (including wage equivalent and COS)

in real estateW^v Total employee compensation (including wage equivalent and COS)

in servicesWtut Total employee compensation (including wage equivalent and COS)

in transportation and public utilitieswwhtr Total employee compensation (including wage equivalent and COS)

in wholesale trade

£ Table G.2. Total variable capital and total wages of unproductive workers, 1948-89

Sources"

SEHE604B136O5B13

Table F.I

SEHE604B7605B7

Table F.I

SEHE604B 126O5B12

Table F.I

SEHE6O4B376O5B37

Table F.I

Table G.I607B60604B60Table F.I

Sectors

PRODUCTION = Wp = VManufacturing

(Wp)manECnun

ws,™Xm.n = (EC/WS) m , n

(Lp)m«n

(ecpinun = (WpJm.n X x m , n X 52Vm , n = (ec p ) m , n X ( L p ) m . n = (W p ) m a n

Mining(wp)m i n

EC m i n

w s m i nXmin = (EC/WS)m i n

(L p ) m i n

( ecp) m i n = (w p ) i n i n xx i n i n x52Vmin = (ecp)m i n X (L p ) m i n = (Wp )m i n

f/\nct nirt i t\n

(wp)conEC c o n

WSco,,Xcon = (EC/WS) c o n

(Lp)con(ec p)c o n = (Wp) c o n xx c o n x52Vcon = (ecp)con X (L p ) c o n = (Wp ) c o n

Transportation and public utilities(Wp)tut (railroads wages)ECt u,

wstu,x,u, = (EC/WS),m

(ecp ) l u ,=(wp) t u lxxt u lx52

(Lp)tutV,u« = (eCp),utx(Lp),ut=(Wp),u,

Services(WpJserv = ( E C / F E E ) ^ = (eCp)^FEE^vE C , ^(Lp)™V ^ = ( e c p ) ^ x ( L p ) ^ = ( W p ) ^

Units

millions of S

S/worker/weekmillions of Smillions of S

thousands$/worker/yearmillions

S/worker/weekmillions of $millions of S

thousandsS/worker/yearmillions

S/worker/weekmillions of Smillions of S

thousandsS/worker/yearmillions

S/worker/weekmillions of Smillions of $


S/worker/yearthousandsmillions of Sthousandsmillions of S

1948

88,410

53.0849,45447,145

1.04913,2242,895

38,288

65.523,5973.3721.067

9373,6343,405

65.237,6627,2521.0572,9383,584

10,259

60.1114,49813,587

1.0673,3354,086

13,628

2,1296,177

13,1535,148

10,961

1949

85,021

53.8047,05944,638

1.05412,0642,949

35,582

62.333,1822,9671.072

8623,4762,998

67.567,4907,0851.0572,8033,714

10,409

62.3614,33313,3851.0713,4723,887

13,497

2,2046,157

13,5735,125

11,297

1950

93,161

58.2853,62850,316

1.06612,7423,230

41,158

67.163,5033,2021.094

8673,8213,311

69.688,6248,1431.0593,0353,837

11,647

64.1415,14114,0811.0753,5863,921

14,061

2,2696,372

14,4585,215

11,834

1951

105,912

63.3463,69159,357

1.07313,5903,534

48,029

74.113,9903,6441.095

8794,2203,709

76.%10,66510,069

1.0593,2244,239

13,664

70.9317,18515.977

1.0763,9674,095

16,247

2,4376,483

15,8005,217

12,715

1952

111,013

66.7568,87664,182

1.07313,5773,725

50,574

77.594,0593,7171.092

8464,4063,730

82.8611,59710,962

1.0583,1854,558

14,520

74.3018,26016,961

1.0774,1604,079

16.966

2,6286,434

16,9065,107

13,419

1953

117,388

70.4776,43371,253

1.07314,1013,931

55,430

83.034,1833,8141.097

8024,7353,798

86.4112,19411,507

1.0603,1064,762

14,790

76.3319,36418,004

1.0764,2694,108

17,537

2,7886,513

18,1615,179

14,442

1954

111,952

70.4972,92267,574

1.07912,8673,956

50,898

82.603,8433,4951.100

7224,7233,412

88.5412,45211,707

1.0642,9714,897

14,548

78.7419,08417,679

1.0794,4203,883

17,165

2,9366,437

18,8995,126

15,049

1955

120,518

75.3080,05073,889

1.08313,2644,242

56,269

89.544,1613,7671.105

7175,1433,687

90.9013,40812,5%

1.0643,0215,032

15,202

82.1220,28518,757

1.0814,6183,929

18,146

3,0546,801

20,7705,332

16,283

1956

128,824

78.7886,50479,489

1.08813,3414.458

59,475

95.064,6744.2131.109

7465.4844,089

96.3814,91914,019

1.0643,1255,334

16,669

88.4021,99420,274

1.0854,9874,006

19,979

3,2197,097

22,8445.455

17,560

1957

132,999

81.1990,27082.515

1.09413,1154,619

60,572

98.254,8304,3611.108

7295,6584,127

100.2715,34214,3411.0703,0675.578

17,107

94.2423,14521,248

1.0895,3383,968

21,183

3,3667,323

24,6505,635

18,966

1958

127,717

82.3286,48978,719

1.09911,7424,703

55,224

96.084,3223,8971.109

6315,5413,494

103.7815,15214,349

1.0562,9185,699

16,630

101.5022,71920,820

1.0915,7593,686

21,228

3,5047,452

26,1125,708

20,001

1959

139,570

88.2995.84186,937

1.10212,3735,061

62,625

103.684,4193,9571.117

5986,0213,601

108.4116.62315.6031.0653.0316,006

18,203

106.4324,18721,976

1.1016,0913,669

22,347

3,6997.694

28,4605.807

21.481

1960

144,230

89.7299,47889,776

1.10812,3635.170

63,911

105.044,4443,%21.122

5776,1273,536

112.6717,24616,1291.0692,9796,265

18,663

108.8425,14922,783

1.1046,2473,666

22,902

3,8758,005

31,0166,060

23,480

1961

146,130

92.3499,67889,912

1.10911,8975,323

63,332

106.924,3713,8761.128

5426,2703,400

118.0817,71616,4911.0742,9376,5%

19,372

112.9425,37522,903

1.1086,5073,549

23,092

4,0558,133

32,9796,146

24,923

Tabled607B46O4B4Table G.I

607B81607B86

6O4B81604B86

Table F.ITable F.ITable F.I

Table G.I

Table G.I

Table G.I

T a b l e d

Table G.I

Table G.I

Table G.I

Agriculture(Wp)nr = ( E C / F E E ) M r = (eCp)Mr

FEE, f r

E C M r

(Lp).,rV M r = ( e c p ) n r x ( L p ) n r = ( W p ) u r

Government enterprisesw,e = ( E C / F E E ) ^ = (ec p ) , e

FEE^fedFEE,* ,F E E , * * , ,EC f e d

EC$1

ECjco, . ,(Lp)^fed = (Lp/L) n o n f O V I O, X L ^ f e d

(LP)g«l = ( L p / L ) n o n g o v t o ( X Lf e $,<Lp),«ou. = <Lp>,efed + <Lp)ge$1

Vte = ( e c p ) r x ( L p ) g e t o t t l

TOTAL TRADE = W,,Wholesale trade

Wwh«rRetail trade

w r e t l rBuilding rental

W b r =-w r e -w g rROYALTIES Wr

Finance and insurance

wfiGround rent

Wre

DUMMY = Wd

Government

Wgovtol

W = Total EC and WEQTotal variable capital = V» = Wp

wu=w-v»(Wu)p = W u - (W u ) u

(Wu)u = Wu + Wr + Wd

ecp = V*/Lp = Wp/Lp

ecu = W u /L u

$/worker/yearthousandsmillions of Sthousandsmillions of $

$/worker/yearthousandsthousandsthousandsmillions of $millions of Smillions of $thousandsthousandsthousandsmillions of $

millions of S

millions of $

millions of $

millions of S

millions of $

millions of $

millions of $

millions of $

millions of $

millions of Smillions of $millions of $millions of Smillions of $S/prod. workerS/unpr. worker

1,6022,0723,3196,0389,673

3,092538211749

1,676640

2,316447175623

1,925

31,939

10,504

20,352

1,083

5,810

4,308

1,502

18,077

18,077

164,76388,41076,35320,52755,8262,6803,017

1,5722,0003,1435,8109,130

3,241570221791

1,857707

2,564469182650

2,108

32,482

10,382

21,061

1,039

6,046

4,610

1,436

20,121

20,121

164,75385,02179,73221,08358,6492,7253,100

1.5402,0673,1845,7988,931

3,424553234787

1,935760

2,695455193648

2,218

34,714

11,107

22,471

1,136

6,650

5,085

1,564

21,240

21,240

178,76193,16185,60122,99762,603

2,8913,246

1,6711,9993,3405,4459,098

3,640578246824

2,140859

2,999472201674

2,451

37,746

12,462

24,046

1,238

7,355

5,656

1,699

27,741

27,741

206,232105,912100,32027,47772,842

3,1983,431

1,7141,9333,3145,2448,990

3,860620284904

2,4331,0563,489

500229729

2,814

39,659

13,102

25,259

1,298

8,018

6,241

1,776

31,527

31,527

222,097111,013111,08431,88079,2043,3883,620

1,7061,8823,2105,0328,582

3,933599292891

2,3661,1383,504

480234714

2,810

42,029

13,887

26,742

1,401

8,798

6,888

1,910

32,409

32,409

236,846117,388119,45836,22283,236

3,5533,828

1,6281,9023,0974,9558,068

3,984599293892

2,3671,1873,554

474232706

2,813

43,194

14,281

27,379

1,534

9,662

7,578

2,084

33,044

33,044

235,670111,952123,71937,81985,9003,5853,979

1,6711,8473,0874,7447,928

4,246597300897

2,5351,2743,809

471236707

3,002

46,175

15,233

29,287

1,655

10,371

8,129

2,242

34,796

34,796

252,731120,518132,21340,87191,342

3,8004,177

1,7691,7693,1294,4847,932

4,419603302905

2,6891,3103,999

470236706

3,120

49",723

16,855

31,097

1,771

11,240

8,849

2,391

37,224

37,224

272,671128,824143,84745,66098,1874,0434,405

1,8521,7473,2354,2057,787

4,560622305927

2,8591,3684,227

479235714

3,257

52,311

17,814

32,715

1,782

11,989

9,591

2,398

39,783

39,783

286,751132,999153.75249,668

104,0844,2314,611

1,9281,7803,4313,9447,603

4,912633320953

3,1871,4944,681

478242720

3,538

53,600

18,336

33,487

1,777

12,785

10,402

2,383

42,903

42,903

289,269127,717161,55252,264

109,2884,3524,835

1,9861,7713,5173,7917,529

5,041645352997

3,2761,7505,026

486265751

3,785

57,321

19,735

35,678

1,908

13,853

11,302

2,551

44,847

44,847

311,712139,570172,14156,120

116,0214,6495,051

2,1051,7553,6943,6277,635

5,298664372

1,0363,5551,9345,489

496278774

4,103

60,652

20,941

37,774

1,937

14,700

12,102

2,598

48,058

48.058

328,351144,230184,12060,710

123,4104,8005,269

2,2061,7633,8893,5177,757

5,489680368

1,0483,7901,9625,752

503272775

4,253

61,810

21,6f

38,200

2,002

15,735

13,040

2,695

51,574

51,574

338,075146,130191,94562,826

129,1204,9775,426

3 5 38 8.v

- a* *

S8

?"

*2

J1

§S

R"

"2

a ~

*

?3 *" *

So Q

Jo

oS

""

2°

°2

pJ

N

<N

2 —

12

™"

—

—

- 2* *

=

"2

B«

** a* a" •

siiE

Ss

S

S.3SJ

a *

££

so —

R

5

S" Mi

- 2 ^s

9 ^* -

—

q

o

—

-

= S

°°* S

2 5IIS

2"« a' s *

7 -T

vj

O

«n

h

<

^

O O

\ O

N

^

O

r* »r» w

O

»o

*N

C

a £ I 8 R a. S

3 ? S 2 8 P

S

= S

O

S

—

™

2 *

S

JQ

*'^

'""

r~»»> o

o^

pj

—

nr

-»

o

r- o\

o\ «*i

S S 8. S 25

) vt

ro

h

^

\A in

M

^

IA

on

^ r*

O

*«t

O

t*- ^

rn

v*i O

^

I2

S5

? S

= 5

§i:Q

?^

Sa

sa

l^

^ I

S ?

3.8

r" -

• «

*s g

£ -

^ r-"

R * ^

oC so -I ^

^ yj

^* oo -*

tf o

i »V

-

rvf «

SO O

s —

8 "

"-"

'

\O

00 m

v^

R

«SI?J =

s* a • a"

as

s:-

'

I

?

| ??

6 S"

ea^s

HiJ:jiX

-J

II 111 HI

IIIi

ll

j

ii'.S

o.g'S

ill 5;

! *J.

Jlgx g^

j,1

sfiill!

316

Table G.I607B4604B4Table G.I

607B81607B86

604B816O4B86


Table G.I

Table G.I

Table G.I

Table G.I

Table G.I

Table G.I

Table G.I

Agriculture(Wp)agr = (EC/FEE)agr = (ecp)agr

FEElgr

EC., ,(Lp ),g rV«gr = (ecp),gr X (Lp)a g r = (Wp)agr

Government enterpriseswge = (EC/FEE)g e=(ecp)g e

FEEgefed

FEEge$l

FEEgetola|ECfed

ECS,ECgelo la,

(Lp)gef«» = (Lp/L)nongOV,o, x Lgefed

(Lp)ge$| = (Lp/L)n o n g o v t o txLg e s ,(Lp)g«otal = (Lp)gefed + (Lp)gesi

vge = (ecp)g ex(Lp )g e l o t a |

TOTAL TRADE = Wlt

Wholesale trade

w w h l rRetail trade

w r e u rBuilding rental

wb r=wr e-wg rROYALTIES = Wr


wfiGround rent

Wre

DUMMY = Wd

Government

Wgovtol

W=TotalECandWEQTotal variable capital = V* = Wp

wu=w-v*( W u ) p = W u - ( W u ) u

( W u ) u = W,, + Wr + Wd

ecD = V * / L n = W D / L nP P P P

ec u = W u / L u


$/worker/yearthousandsthousandsthousandsmillions of $millions of $millions of Sthousandsthousandsthousandsmillions of $

millions of $

millions of $

millions of S

millions of $

millions of S

millions of $

millions of $

millions o f $

millions of $

millions of $millions of Smillions of Smillions of $millions of S$/prod. worker$/unpr. worker

2,3551,7234,0573,3957,994

5,704691389

1,0803,9682,1926,160

510287797

4,547

65,047

22.770

40,163

2,114

16,620

13,765

2,855

55,437

55,437

360,886155,536205,35068,245

137,1045,1965,680

2,5061,6774,2023,1998,016

6,071694399

1,0934,3112,3256,636

511294804

4,883

68,074

23,964

41,864

2,246

17,684

14,640

3,044

59,321

59,321

379,432162,758216,673

71,594145,079

5,4235,913

2,7881,5524,3273,0278,441

6,393700420

1,1204,5862,5747,160

513308821

5,251

72,554

25,559

44,630

2,365

18,965

15,748

3,217

64,386

64,386

406,662171,998234,665

78,759155,906

5,6806,242

3,0681,4764,5292,9028,905

6,711718428

1,1464,9142,7777,691

527314841

5,646

77,411

27,332

47,578

2,501

20,280

16,868

3,412

69,256

69,256

436,635188,426248,210

81,264166,946

6,0076,403

3,3901,3824,6852,6669,037

6,920785429

1,2145,4013,0008,401

575314888

6,148

83,556

30,072

50,793

2,691

22,029

18,347

3,682

78,394

78,394

480,940207,068273,872

89,893183,979

6,3596,723

3,6321,3144,7722,5549,275

7,197824429

1,2535,7913,2279,018

598311909

6,543

88.539

32,047

53,673

2,819

24,227

20,359

3,869

87,377

87,377

515,034216,257298,77798,634

200,1436,5827,067

3,8901,2985,0492.5139,774

7,806835461

1,2%6,4593,658

10,117605334939

7,331

96,641

34,710

58,734

3,1%

27,371

22,972

4,399

97,769

97,769

566,661236,769329,892108,112221,781

7,0797,587

4,2821,2745,4552,435

10,425

8,417848479

1,3277,0764,094

11,170612346958

8,066

106,485

38,345

64,554

3,587

30,231

25,267

4,%3

107,481

107,481

624,698261,216363,482119,285244,197

7,6558,123

4,5031,2805,7642,367

10,660

9,449866507

1,3738,3774,597

12,974621363984

9,299

115.086

41,512

69,531

4,044

33,007

27,381

5,626

119,474

119,474

667,551270,432397,120129,553267,567

8,1348,819

4,6241,2765,9002,290

10.588

10,042870521

1,3918,8295,140

13,969622373995

9,994

124,025

44,262

75,147

4,616

36,294

29,837

6,456

130,322

130,322

712,247287,525424,721134,081290,641

8,7859,394

4,8411,2936,2602.357

11,411

11,068843530

1,3739,5905,606

15.1%606381986

10,918

135,689

48,443

81.991

5.254

40,256

32,867

7,389

142,590

142,590

783,118324,303458,815140,280318,535

9,5689,983

5,4581,3687,4662,408

13,142

12,101838555

1,39310,4246,433

16,857601398999

12,084

151,100

54,782

90,145

6,173

45,027

36,298

8,730

155,041

155,041

875,185370,490504,695153.527351,168

10,44710,550

5,9061,4588,6112,475

14,618

13,225854596

1,45011,8247,352

19.176608424

1,03213,653

166,627

61,569

98,447

6,611

49,257

39,891

9,366

168,699

168,699

961,227398.505562,722178.138384.583

11.17611,495

6,3981,4409,2132.423

15,502

14,493838644

1,48212,9768,502

21,478587451

1,03715,035

178,072

65,151

106,098

6,824

54,707

45,022

9,685

187,651

187,651

1,024,738410,750613,988193,558420,430

12,21912,476

Table G.2 (cont.)

Sources*

SEHE604B136O5B13

Table F.I

SEHE6O4B76O5B7

Table F.I

SEHE6O4B12605B12

Table F.I

SEHE604B376O5B37

Table F.I

Table G.I607B60604B60Table F.I

Sectors

PRODUCTION = Wp = V*Manufacturing

(wp)man

wsTJlxman = (EC/WS)man

(Lp)m a n

(ecp)man = (wp)man x xman x 52Vman = (ecp)raan X (Lp)m a n = (Wp)man

(wp)min

ECmin

ws m i nxmin = (EC/WS)min

(Lp)m i n

VmL = ( " e c p ) ^ " L p )Tn = ( W p ) m i nConstruction

(Wp)con

ECcon

ws c o nxc o n=(EC/WS)c o n

(Lp)con(ecp)con = (wp)con x xcon x 52Vcon = (eCp)conX(Lp)con = (Wp)con

Transportation and public utilities(wp)tui (railroads wages)EC,U,

ws t u txlu, = (EC/WS)llM

(ecp),u, = (wp) l u txx t m x52(Lp)lu l

V,ul = (ecp)lu, x (Lp)tut = (Wp)lul

Services(WpW = ( E C / F E E ) ^ = ( e c p ) ^FEEJCTV

ECJCTV

(Lp)scrvV — lee \ y | | I — f W I

Units

millions of $

$/worker/weekmillions of $millions of $

thousands$ /worker/yearmillions

$/ worker/ weekmillions of $millions of $






$/worker/yearthousandsmillions of $thousandsmillions of S

1976

459,625

209.32286,704238,046

1.20413,52513,110

177,301

273.9014,60612,243

1.193601

16,99210,214

283.7357,88349,988

1.1583,462

17,08459,153

300.6681,83766,585

1.22919,2163,928

75,484

10,77413,906

149,8279,697

104,475

1977

515,814

228.90324,274266,707

1.21614,08414,472

203,821

301.2016,92314,076

1.202632

18,83011,895

296.6564,70155,219

1.1723,714

18,07567,138

321.4791,24074,158

1.23020,5674,011

82,503

11,56814,541

168,2059,978

115,423

1978

589,202

249.27366,271300,093

1.22114,67115,820

232,099

332.8819,83216,476

1.204663

20,83613,824

318.6976,04864,626

1.1774,207

19,50182,047

343.92103,52384,168

1.23021,9964,161

91,516

12,53715,473

193,98710,478

131,361

1979

664,783

268.94409,736334,840

1.22415,00317,113

256,743

365.0723,72519,673

1.206718

22,89416,443

342.9988,10774,526

1.1824,479

21,08694,439

392.47116,83995,063

1.22925,0834,324

108,463

13,76616,210

223,14610,646

146,552

1980

706,526

288.62436,141355,570

1.22714,13118,409

260,144

397.0628,77323,897

1.204778

24,86019,349

367.7892,67278,111

1.1864,244

22,69096,303

426.56128,129103,958

1.23327,3384,306

117,729

15,23616,794

255,86710,956

166,919

1981

772,351

318.00475,363386,660

1.22913,96920,329

283,974

438.7535,83029,832

1.201857

27,40223,490

399.2697,85982,297

1.1894,056

24,687100,132

457.95140,836114,431

1.23129,3084,327

126,816

16,83817,376

292,58411,171

188,105

1982

786,528

330.26473,056384,038

1.23212,62421,154

267,050

459.8837,45431,217

1.200825

28,69223,681

426.8297,70381,588

1.1983,733

26,57899,210

484.15149,692119,874

1.24931,4384,235

133,125

18,41517,704

326,02311,463

211,085

1983

839,732

354.08490,606397,391

1.23512,45022,731

282,997

479.4033,10727,563

1.201679

29,94320,321

442.97100,48583,151

1.1083,807

27,836105,983

541.85155,354124,344

1.24935,2034,175

146,978

19,56918,348

359,05611,779

230,506

1984

928,680

374.03540,658439,105

1.23113,20123,948

316,126

503.5835,28029,238

1.207692

31,59821,878

458.51113,89993,781

1.2154,273

28,957123,741

573.19165,408132,306

1.25037,2634,360

162,462

20,44419,517

398,99812,134

248,067

1985

967,993

386.37563,178460,857

1.22213,00024,552

319,165

519.9334,72228,992

1.198657

32,38021,260

464.46124,640102,890

1.2114,566

29,257133,581

594.70172,747139,275

1.24038,3564,395

168,589

21,39520,468

437,91712,459

266,560

1986

998,546

396.01579,190473,218

1.22412,81725,204

323,029

525.8130,27325,190

1.202549

32,85918,024

466.75134,046110,230

1.2164,737

29,515139,806

608.38179,268144,153

1.24439,3424,413

173,609

22,39321,371

478,57012,655

283,399

1987

1,060,901

406.31598,082490,292

1.22012,93025,773

333,235

530.8528,44223,578

1.206516

33,29917,173

479.68142,441117,536

1.2124,815

30,229145,541

627.33188,987152,399

1.24040,4534,529

183,231

23,78722,537

536,09313,300

316,381

1988

1,146,222

418.81639,252524,004

1.22013,22926,568

351,454

541.4429,74124,615

1.208526

34,01817,906

495.73154,775127,859

1.2114,979

31,205155,377

673.50200,169161,047

1.24343,5304,647

202,275

25,28223,544

595,23413,836

349,802

1989

1,206,3%

430.09662,166541,838

1.22213,25227,331

362,182

569.7529,62524,461

1.211498

35,88217,879

512.41161,982133,477

1.2145,016

32,336162,198

693.00209,597168,356

1.24544,8634,728

212,118

26,38024,715

651,98014,367

379,012

Table G.I607B4604B4Table G.I

607B81607B86

604B8I6048 86


Table G.I

Table G.I

Table G.I

Table G.I

Table G.I

Table G.I

Table G.I

Agnculture0*P)Mr = (EC/FEE)M r«(ecp)a g r

FEEMr

( L p ) u r

VM r=(ecp). g r x (Lp )M r = (Wp)Mr

Government enterpriseswge = (EC/FEE)ge = (ecp)ge

FEE g e W

FEEge$,FEEgel0U|ECfed

ECjiECg e l 0 U l

(Lp)|Isi=(Lp/L)(J3^x Lg*(Lp)fetoul = (Lp)fefed + (L p ) g e s |

Vge = ( e c p ) g e x ( L p ) g e t 0 U ,

TOTAL TRADE = WH

Wholesale tradeWWh,r

Ret Ail trade

Building rental

wb f=wr e-wg rROYALTIES = Wr


wfiGround rent

wreDUMMY = Wd

Government

W.ov.0,

W=Total EC and WEQTotal variable capital = V = Wp

wu=w-v*(W u ) p =W u - (W u ) u

( Wu)u = Wu + W, + Wd

ecp = VVLp = W p /L p

e c u = W u / L u


$/worker/yearthousandsthousandsthousandsmillions of $millions of $millions of Sthousandsthousandsthousandsmillions of S

millions of $

millions of $

millions of $

millions of $

millions of S

millions of S

millions of $

millions of $

millions of S

millions of $millions of $millions of $millions of Smillions of SS/prod. workerS/unpr. worker

6,8571,532

10,5052.439

16,727

15,882819645

1,46414,0579,194

23.251573451

1.02516,272

198,096

72,729

117.734

7.634

60,880

50.026

10,854

203,818

203,818

1,140,356459,625680,731217,936462,795

13,25413,487

7,5481,490

11,2462,360

17,814

16,915813650

1,46314,9189,829

24,747566452

1,01817,221

219,376

80,191

130,376

8,809

68,330

55,781

12,549

220,498

220,498

1.268,469515,814752,654244,450508,204

14,40914,386

8,2131,525

12,5252,389

19,624

18,005821680

1,50116,07910,94627,025

569471

1,04018,731

247,987

91,013

146,357

10,616

78,887

63,736

15,151

240,542

240,542

1,433,637589,202844,434277,019567,416

15.66615,373

9.1691,524

13,9732.372

21.752

19,313838700

1,53817,60012,10429,704

575481

1.05620,391

279,124

104,562

161,826

12,736

90,144

72,206

17,938

260,444

260,444

1,610,759664,783945,976316,265629,711

17,22316,617

9,8361,530

15,0492,383

23,441

21,279846730

1,57619,74913,78733,536

571493

1,06422,641

305,437

116,543

174,849

14,045

102,955

83,174

19,782

288,253

288,253

1,773,254706,526

1,066,728370,083696.645

18.66018.433

10.7391.444

15,5072,305

24,755

23,828852727

1,57922,43415,19037,624

568485

1.05325,079

331,967

128,702

188,315

14,950

115,041

93,984

21,056

316,738

316,738

1,956,867772,351

1,184,516420,770763,746

20,46620,130

11,4821,480

16,9932,298

26,383

25,336836728

1.56423,10616,52039,626

548478

1,02625,994

349,949

135,414

198,455

16,080

128,739

106,091

22,648

343,899

343,899

2,071,620786,528

1.285,092462,505822,587

21,72621,860

11.6341.477

17,1832,173

25,281

26,996834743

1,57724,78317.78942.572

542483

1,02527,666

373,944

141,433

214,158

18,353

144,817

118,967

25,850

366,390

366,390

2,199,810839,732

1,360,078474,927885,151

23,26922,719

12,3021,466

18,0342,167

26,662

28,485857760

1,61726,89419,16646,060

553492

1,04429,744

412,947

157,541

234,340

21,067

159,358

129,687

29,671

390,890

390,890

2,404,596928,680

1,475,916512,720963,196

24,52223,526

12,8331.458

18.7102,096

26,898

30,220860791

1,65128,77621,11849,894

551506

1,05731,940

440,117

167,464

249,111

23,542

176,610

143.452

33.158

418,975

418,975

2,565,699967,993

1,597,705562,003

1,035,70225,32124,655

13,2191,476

19,5112,079

27,482

31,225856822

1,67829,30623,08952,395

542521

1,06333,198

468,204

176,017

266,681

25,506

200,213

164,290

35.924

443.799

443.799

2,719,892998,546

1,721,347609,131

1,112,21626,06325.878

13,7081.561

21.3982,170

29,746

32,842882833

1,71532,01224,31256,324

557527

1,08435,595

500,999

188,082

284,432

28,485

223,111

182,992

40,119

472,950

472.950

2.913.0891.060,9011.852,188

655,1281,197,060

26,96527,021

13,9871,648

23,0502,216

30,995

34,768908848

1,75635,09825,95461.052

570534

1,10538.413

542.817

206.821

303.861

32,136

242,605

197,343

45,261

505,779

505,779

3,152,1101.146,2222,005,888

714,6881,291,201

28,27528.483

15.0451.608

24.1922.169

32.625

36,115917868

1,78536,61727,84964,466

574544

1,11840,382

576,191

221,875

321,033

33,283

249,835

202,957

46,878

541,555

541,555

3,337,0381,206,3962,130,642

763,0611,367,581

29,31829.444

• SEHE denotes Supplement to Employment, Hours, and Earnings, United States, 1909-84 (BLS 1989). Unless otherwise indicated, all data come from NIPA (e.g. BEA 1986), where the first (two or) three digits (and following letter, if any) denote therelevant table number and subsequent digits the line numbers within those tables.


Glossary of variables in Table G.2ECagr Total employee compensation in agriculture, forestry, and

fisheriesEC c o n Total employee compensation in constructionECf e d Total employee compensation in government enterprises

(federal)ECgetotai Total employee compensation in government enterprises

(federal, state, and local)ECm a n Total employee compensation in manufacturingECm i n Total employee compensation in miningecp Average annual wage of productive workers(ecp)con Estimated annual per-worker employee compensation in

construction(ecp)man Estimated annual per-worker employee compensation in

manufacturing(ecp)min Estimated annual per-worker employee compensation in

mining(ecp)tut Estimated annual per-worker employee compensation in

transportation and public utilitiesECserv Total employee compensation in servicesECsl Total employee compensation in government enterprises (state

and local)ECtut Total employee compensation in transportation and public

utilitiesecu Average annual wage of unproductive workersFEEagr Total full-time equivalent employees in agriculture, forestry,

and fisheriesFEEgefed Total full-time equivalent employees in government enterprises

(federal)FEEgesl Total full-time equivalent employees in government enterprises

(state and local)FEEgetotal Total full-time equivalent employees in government enterprises

(federal, state, and local)FEEserv Total full-time equivalent employees in services(Lp)a g r Estimated total productive labor in agriculture, forestry, and

fisheries(Lp)con Estimated total productive labor in construction(L p)gefed Estimated total productive labor in government enterprises

(federal)(Lp)gesi Estimated total productive labor in government enterprises

(state and local)(Lp)getotai Estimated total productive labor in government enterprises

(federal, state, and local)(L p) man Estimated total productive labor in manu facturing(L p)min Estimated total productive labor in mining

(LP

(LP

Vag,

vc0,

vma

)serv

),««

r. ( W p ) ^

n> ( Wp)con

in> \ "p/man

*min> ("plmin

v*!w

wblwdwfi

V

» ( W p ) t u t

wp


Estimated total productive labor in productive servicesEstimated total productive labor in transportation and publicutilitiesVariable capital in agriculture, forestry, and fisheriesVariable capital in constructionVariable capital in government enterprisesVariable capital in manufacturingVariable capital in miningVariable capital in servicesVariable capital in transportation and public utilitiesVariable capitalEstimated total wage: employee compensation, wageequivalent of self-employed persons, and corporate officers'salariesTotal employee compensation in building rental sectorTotal employee compensation in dummy sectorsTotal employee compensation in finance and insuranceUnit wage of production workers in government enterprises

does just that. We calculate variable capital as the product of productionworker wages wp, the ratio x of employee compensation to wages and sal-aries, and the number Lp of production workers. In this calculation, cor-porate officers' salaries play an insignificant role - only through their veryslight effect on the compensation/wage ratio x. In effect, the slightly highercompensation/salary ratio x' of corporate officers is weighted by theirvery small share in total wages and salaries (4.2% in manufacturing for1968; U.S. Internal Revenue Service, Statistics of Income), so that theratio x is virtually unaffected when we deduct corporate officers' compen-sation and salaries from the numerator and denominator, respectively(the difference is 0.7% in manufacturing for 1968). Thus our estimate ofV*, and hence of SVV*, is essentially the same as if we had first deductedcorporate officers' salaries from employee compensation and from wagesand salaries.

However, the same is not true for our total measure of wages W, be-cause this directly contains corporate officers' salaries. Therefore, ourmeasure of unproductive wages Wu = W - V* is larger by the amount ofCOS. As long as we recognize that Wu is the sum of unproductive workerwages and corporate salaries, this poses no serious problem.

The use of EC as our base also requires that we estimate the unit em-ployee compensation of production workers ecp by enhancing the BLSdata on their unit wage by an estimate of the ratio x (of employee com-pensation EC to wages and salaries WS) for production workers in eachsector. For this ratio x, we use the ratio of EC to WS of all workers in


each sector, implicitly assuming that this ratio is roughly the same forboth production and nonproduction workers. Employee compensationbeing the sum of supplements and wages and salaries, this assumptioncan be checked by calculating the ratio of supplements to wages for pro-duction and nonproduction workers (these data are available only forthe period 1966-77). From the Handbook of Labor Statistics (BLS 1980,tables 132 and 133) we find that for 1968 there are only small differencesbetween production and nonproduction workers with respect to the ratiosof supplements to wages and salaries:

Non- Ratio ofoffice3 All non-officeworkers workers to all

Manufacturing 0.131 0.126 1.039Nonmanufacturing 0.114 0.107 1.061

3 For manufacturing, "non-office" is equivalent to production workers. See BLS(1980, p. 318, table 132, n. 5).

H

Surplus value and profit

The estimates of value added and final product in Appendix E and ofvariable capital in Appendix G allow us to calculate surplus value andsurplus product. By definition:

S* = VA* — V* = surplus value (in money form);

S*/ V* = rate of surplus value;

NP* = necessary product (consumption of productive workers)

= V*;

and

SP* = FP* - NP* = surplus product.

The Marxian measures may be compared to naive estimates P+ andP+/EC.

P+ = VA — EC = profit-type income (gross of all business taxes),

whereVA = FD = NNP = net national product (NIPA) andEC = total wages.

Hence

P+/EC = profit-type income/wage ratio.

We may also define more restricted measures of profit, such as P =P+-IBT (where IBT = indirect business taxes) and Pn = P + - I B T - cor-porate income tax = profit, net of all business taxes.

Table H.I details surplus value and profit for the period 1948-89.

323

Table H.I. Surplus value and profit, 1948-89 (billions of dollars)

Sources

Table E.ITable G.2

Table E.2Table E.ITable E.2Table G.2

112 1"604B1"

B-79*B-80, B-82C

Variables

S* = VA*-V*VA*V**

SVV*

SP* = FP*-NP*FP* = GFP*-DP

GFP*=TP*-M;TP*Mp

D P

NP* = V*

P+ = VA-ECVA = FD = NNPEC

PVEC

Pn = (P+ ) -IBT-corporate income tax

IBT = indirect business taxCorporate income tax

P = (P +) -IBT

1948

149.94238.35

88.411.70

149.91238.32247.74446.21198.47

9.4288.41

99.11241.20142.09

0.70

66.5120.2012.4078.91

1949

148.64233.66

85.021.75

148.58233.60242.90431.96189.06

9.2985.02

96.40238.40142.00

0.68

64.9021.3010.2075.10

1950

165.26258.4293.16

1.77

165.09258.25269.06481.62212.56

10.8193.16

109.18264.60155.42

0.70

67.7823.5017.9085.68

1951

188.25294.17105.91

1.78

188.26294.18307.03551.62244.59

12.85105.91

124.61306.20181.60

0.69

76.7125.3022.6099.31

1952

194.51305.52111.01

1.75

194.79305.81319.61573.95254.35

13.80111.01

126.15322.50196.35

0.64

79.0527.7019.4098.45

1953

204.52321.91117.39

1.74

204.29321.68336.71605.37268.66

15.04117.39

130.28340.70210.42

0.62

80.2829.7020.30

100.58

1954

208.20320.15111.95

1.86

208.23320.18335.26596.63261.36

15.08111.95

130.63340.00209.37

0.62

83.4329.6017.60

101.03

1955

228.55349.07120.52

1.90

228.16348.67365.74652.91287.18

17.07120.52

145.59371.50225.92

0.64

91.2932.3022.00

113.29

1956

236.97365.79128.82

1.84

236.74365.56384.10687.21303.11

18.54128.82

145.36390.10244.74

0.59

88.3635.0022.00

110.36

1957

250.25383.25133.00

1.88

249.88382.88402.67717.30314.63

19.79133.00

152.14409.90257.76

0.59

93.2437.5021.40

114.64

1958

256.15383.87127.72

2.01

256.04383.75403.67711.67308.00

19.92127.72

154.24414.00259.76

0.59

96.5438.7019.00

115.54

Sources Variables 1959 1960 1961 1962 1963 1964 1965 1966 1967 1968 1969

Table E.ITable G.2


112 1"604B1'

B-79*B-80, B-82C

S* = VA*-V*VA*V*

svv*SP* = FP*-NP*FP* = GFP*-DP

GFP*=TP*-MP

TP*M'p

DpNP* = V*


PVEC

Pn = (P+ ) -IBT-corporate income tax


P = (P + ) -IBT

278.42417.99139.57

1.99

278.34417.91439.36774.293J4.9321.44

139.57

169.96451.20281.24

0.60

104.4641.9023.60

128.06

286.46430.69144.23

1.99

285.93430.16451.95795.67343.7221.78

144.23

172.24468.90296.66

0.58

104.0445.5022.70

126.74

296.54442.67146.13

2.03

295.95442.08463.88811.42347.5421.80

146.13

180.54486.10305.56

0.59

109.6448.1022.80

132.44

320.20475.73155.54

2.06

319.54475.07498.12869.52371.4023.05

155.54

197.78525.20327.42

0.60

122.0851.7024.00

146.08

337.71500.46162.76

2.07

337.07499.83523.74913.42389.6823.91

162.76

209.98555.50345.52

0.61

129.0854.7026.20

155.28

364.54536.54172.00

2.12

364.00536.00561.05973.35412.31

25.05172.00

224.91595.90370.99

0.61

138.1158.8028.00

166.11

395.00583.42188.43

2.10

394.44582.87609.78

1057.19447.41

26.91188.43

247.88647.70399.82

0.62

154.2862.7030.90

185.18

430.65637.72207.07

2.08

430.09637.16665.94

1149.69483.74

28.79207.07

266.95709.90442.95

0.60

167.8565.4033.70

201.55

454.40670.66216.26

2.10

453.42669.68699.15

1199.81500.6629.48

216.26

273.48749.00475.52

0.58

170.3870.4032.70

203.08

493.63730.40236.77

2.08

493.12729.89762.32

1307.46545.14

32.43236.77

293.98818.70524.72

0.56

175.5879.0039.40

214.98

523.83785.04261.22

2.01

523.25784.46819.72

1406.26586.5435.26

261.22

304.13882.50578.37

0.53

177.8386.6039.70

217.53

Table H.I (cont.)

Sources

Table E.ITable G.2


112 1"604B1"

B-79*B-80, B-82f

Variables

S* = VA*-V*VA*V*

SVV*

SP* = FP*-NP*FP* = GFP*-D P

GFP* = TP*-M P

TP*MP

DpNP* = V*


PVEC

Pn = (P +) -IBT-corporate income tax


P = (P + ) -IBT

1970

547.67818.11270.43

2.03

546.86817.30853.88

1456.35602.4736.59

270.43

308.31926.60618.29

0.50

179.6194.3034.40

214.01

1971

596.70884.22287.53

2.08

596.04883.56923.12

1567.82644.70

39.56287.53

345.731005.10659.37

0.52

204.43103.6037.70

242.13

1972

645.98970.28324.30

1.99

645.51969.81

1014.081728.41714.3344.27

324.30

378.561104.80726.24

0.52

225.26111.4041.90

267.16

1973

719.751090.24370.49

1.94

719.631090.121142.521979.91837.4052.40

370.49

428.371241.20812.83

0.53

258.07121.0049.30

307.37

1974

778.251176.75398.50

1.95

778.821177.331235.822162.38

926.5658.50

398.50

444.121335.40891.29

0.50

263.02129.3051.80

314.82

1975

867.021277.77410.75

2.11

868.781279.531344.712368.481023.78

65.17410.75

487.921436.60948.68

0.51

297.02140.0050.90

347.92

1976

968.821428.45459.63

2.11

971.251430.881507.062694.391187.33

76.18459.63

545.751603.601057.85

0.52

329.95151.6064.20

394.15

1977

1083.131598.95515.81

2.10

1086.661602.471690.833058.101367.27

88.36515.81

612.381789.001176.62

0.52

373.88165.5073.00

446.88

1978

1221.071810.27589.20

2.07

1221.761810.971910.873456.761545.89

99.90589.20

690.572019.801329.23

0.52

429.27177.8083.50

512.77

1979

1346.242011.02664.78

2.03

1347.442012.222122.763833.251710.49

110.54664.78

751.002242.401491.40

0.50

474.30188.7088.00

562.30

1980

1462.702169.23706.53

2.07

1463.672170.202289.844141.101851.27119.64706.53

789.882428.101638.22

0.48

493.08212.00

84.80577.88

Sources Variables 1981 1982 1983 1984 198S 1986 1987 1988 1989

Table E.ITable G.2


112 1"604B1"

B-79*B-80, B-82C

S* = VA*-V*VA*V*

svv*SP* = FP*-NP*FP*=GFP*-DP

GFP* = TP*-M P

TP*MP

DpNP* = V*


PVEC

Pn = (P +) -IBT-corporate income tax


P = (P +) -IBT

1668.192440.54772.35

2.16

1669.402441.752576.064654.402078.34

134.31772.35

897.392704.801807.41

0.50

566.99249.30

81.10648.09

1724.682511.20786.53

2.19

1726.062512.592649.254763.862114.61

136.66786.53

875.792782.801907.01

0.46

556.29256.4063.10

619.39

1865.802705.53

839.732.22

1867.152706.882851.365086.972235.61

144.48839.73

988.403009.102020.70

0.49

631.10280.1077.20

708.30

2101.783030.46928.68

2.26

2103.703032.383193.775691.022497.25

161.39928.68

1142.883356.802213.93

0.52

739.48309.5093.90

833.38

2258.683226.68967.99

2.33

2258.313226.303395.536014.182618.65

169.23967.99

1210.053577.602367.55

0.51

783.75329.9096.40

880.15

2401.113399.66998.55

2.40

2389.253387.803559.996224.472664.48

172.19998.55

1260.103771.502511.40

0.50

808.30345.50106.30914.60

2563.383624.281060.90

2.42

2555.523616.423797.936606.592808.66

181.511060.90

1339.204028.602689.40

0.50

847.30365.00126.90974.20

2752.813899.031146.22

2.40

2755.183901.404103.237226.223122.99201.83

1146.22

1454.304359.402905.10

0.50

932.80385.30136.20

1069.00

2943.354149.751206.40

2.44

2945.324151.714363.577641.823278.25211.86

1206.40

1567.404646.403079.00

0.51

1021.30411.00135.10

1156.40

* From NIPA (e.g. BEA 1986), where the first three digits (and following letter, if any) denote the relevant table number and subsequent digits the line numbers withinthose tables.6 Table from CEA (1991). For 1948-58, CEA (1971, table C-66) and CEA (1983, table B-77) were used.

to


Glossary of variables in Table H.IDpECFD = NNPFP*GFP*M ' PNP* = V*P+PPn

s*svv*SP*TP*V*VAVA*

Depreciation of productive fixed capitalEmployee compensationFinal demand = net national product (NIPA)Marxian final productMarxian gross final productMaterials inputs into productionNecessary product (consumption of productive workers)Property-type income (gross of all business taxes)Property-type income (net of indirect business taxes)Property-type income (net of all business taxes)Surplus value (in money form)Rate of surplus valueSurplus productMarxian total productVariable capital (in money form)Net national product (NIPA)Marxian net value added

Rates of exploitation of productive andunproductive workers

Our calculations are based upon the formula for relative rates of exploi-tation, derived in Section 4.2:

(l + e u ) ^ h u /h p

(l + ep) ~ ecu/ecp'

whereeu, ep = rates of exploitation of productive and unproductive workers;hu, hp = hours per unproductive and productive worker; and

ecu, ecp = employee compensation per unproductive and productiveworjcer.

Since the rate of exploitation of productive workers is simply the rateof surplus value, we substitute S*/V* for ep and derive eu:

hu /hp

ecu/ecp

Individual steps in the calculation are shown next. Table I.I gives the an-nual results and sources for the variables.

(1) The first step is to calculate the average hours of production work-ers hp:

Hp = hp • Lp = total hours of production and nonsupervisoryworkers in the private nonagricultural sector,

wherehp = average hours per production and nonsupervisory worker in the

private nonagricultural sector, andLp = number of production and nonsupervisory workers in the

private nonagricultural sector.

329

o

Table I.I. Rates of exploitation of unproductive workers, 1948-89

123456789

10111213141516171819202122232425

Sources

CEA, B-44C-2"

BLS*BLS*

O 2 , C-3*C-2, C-3"

Table J.ITable F.ITable F.I

Table G.2Table G.2

Table H.I

Variables

H;=h;xL;KK

Hp = H;-(Hp),-(Hp)fire

(Hp),=(hp)tx(Lp),(hp),(Lp),

(H p) f t r e = (hp) f i r e x (Lp ) f i r e

(hp) f t r e

(Lp)f l r e

Lp = L;-(Lp),-(Lp)f l r e

Hp = (Hp/L'p)x52h u=h(L/L u ) -h p (L p /L u )

hL

LPLU = L - L P

h u/h p

ecu

ecp

ecu/ecp(1+eu)/(l + ep)=(hu/hp)/(ecu/ecp)SVV*eu = [0 + eu)/(l + ep)] x (1 + SVV*) - 1eu/ep

Units

thousand weekly hoursweekly hoursthousandsthousand weekly hoursthousand weekly hoursweekly hoursthousandsthousand weekly hoursweekly hoursthousandsthousandshours /prod, worker/yearhours /unpr. worker/yearhours/FEE/yearthousandsthousandsthousands

$/unpr. worker$/prod. worker/year

1948

1,379,560.0040.00

34,489.00974,250.00348,611.60

40.408,629.00

56,698.4037.90

1,496.0024,364.002,079.342,042.532,063.36

58,301.0032,993.9125,307.09

0.983,017.072,679.59

1.130.871.701.350.80

1949

1,306,464.6039.40

33,159.00901,024.50348,097.50

40.508,595.00

57,342.6037.80

1,517.0023,047.002,032.942,057.292,043.94

56,919.0031,201.3625,717.64

1.013,100.282,724.93

1.140.891.751.440.83

1950

1,367,090.2039.80

34,349.00954,038.70354,051.00

40.508,742.00

59,000.5037.70

1,565.0024,042.002,063.472,059.452,061.66

58,600.0032,226.0726,373.93

1.003,245.652,890.85

1.120.891.771.470.83

1951

1,445,377.5039.90

36,225.001,016,042.60

368,185.5040.50

9,091.0061,149.40

37.701,622.00

25,512.002,070.962,059.372,065.52

62,366.0033,123.3629,242.64

0.993,430.593,197.52

1.070.931.781.570.89

1952

1,462,055.7039.90

36,643.001,025,118.30

373,320.0040.00

9,333.0063,617.40

37.801,683.00

25,627.002,080.082,045.622,063.42

63,457.0032,768.2330,688.77

0.983,619.703,387.82

1.070.921.751.530.88

1953

1,492,682.4039.60

37,694.001,051,364.00

375,645.0039.50

9,510.0065,673.40

37.701,742.00

26,442.002,067.582,039.862,054.12

64,247.0033,042.7631,204.24

0.993,828.253,552.62

1.080.921.741.510.87

1954

1,418,391.6039.10

36,276.00976,936.40373,512.00

39.509,456.00

67,943.2037.60

1,807.0025,013.00

2,030.972,050.292,040.61

62,324.0031,230.3131,093.69

1.013,978.903,584.71

1.110.911.861.600.86

38

88

8S

88

88

88

SS

8S

88

SS

S8

12

88

;

f 2

55

oo

't

o!

s-

NS

So

fiii S

^ & 8 Si"

*

'ri O

»O

N

*

N N

N *

O

Sa

s

2

88888888 8882PS 8 P

1 T

.i

.l

1

l ^

.^

oC

oo ~ •*

oC

ro «* «

oo ro

co oo

r~

<S

N" N

N

« •"

sfs"a

ssfs"ir>

On

•n

r^

ri—

op

nm

oo

. ,

i . R

. «

1 ^

331

Table I.I (cont.)

12345678910111213141516171819202122232425

1967

1,715,206.0038.00

45,137.001,177,566.00443,628.60

36.6012,121.0094,011.40

37.102,534.0030,482.002,008.842,002.362,005.20

75,137.0032,856.3242,280.68

1.007,066.526,581.91

1.070.932.101.880.89

1968

1,756.679.4037.80

46,473.001,205,826.20452,766.20

36.1012,542.0098,087.00

37.002,651.00

31,280.002,004.571,983.891,992.88

76,929.0033,445.3543,483.65

0.997,586.587,079.28

1.070.922.081.850.89

1969

1,817,441.6037.70

48,208.001,246,217.10467,455.80

35.7013.094.00

103,768.7037.10

2,797.0032,317.002,005.241,986.121,994.39

78,875.0034,125.4244,749.58

0.998.122.587,654.58

1.060.932.011.810.90

1970

1,786.587.6037.10

48.156.001,208,790.80472,137.50

35.3013,375.00

105,659.3036.70

2,879.0031,902.001.970.321,981.371,976.68

78,275.0033,247.2145,027.79

1.018,819.448,133.96

1.080.932.031.810.89

1971

1,776,661.2036.90

48,148.001,191,280.50477,886.50

35.1013,615.00

107.494.2036.60

2,937.0031,596.001,960.581,985.511,975.04

77,937.0032,727.4245,209.58

1.019,394.508,785.45

1.070.952.081.910.92

1972

1,847,669.0037.00

49,937.001,243,679.10493,311.50

34.9014,135.00

110,678.4036.60

3,024.0032,778.001,973.011,985.961,980.46

79,856.0033,896.3445.959.66

1.019,982.999,567.50

1.040.961.991.890.95

1973

1,926,216.9036.90

52,201.001,302.849.30509,139.00

34.6014,715.00

114.228.6036.60

3,121.0034,365.001,971.431,975.281,973.64

83,299.0035.462.1347,836.87

1.0010,550.3410,447.47

1.010.991.941.920.99

1974

1,927,528.5036.50

52.809.001,297,908.70512,965.80

34.2014,999.00

116,654.0036.50

3,196.0034,614.001,949.831,946.571,947.94

84,612.0035,657.4748.954.53

1.0011,494.7911,175.92

1.030.971.951.870.96

1975

1,840,775.1036.10

50,991.001,215,680.90509,279.70

33.9015,023.00

115,814.5036.50

3,173.0032.795.001,927.591.946.891,939.06

82,827.0033,615.1949,211.81

1.0112,476.4412,219.18

1.020.992.112.080.98

1976

1,909,581.7036.10

52,897.001.264.165.20527.371.30

33.7015,649.00

118,045.2036.40

3,243.0034,005.001,933.141,935.511,934.54

85,151.0034,677.0750,473.93

1.0013,486.7813,254.44

1.020.982.112.060.98

1977

1,986,444.0036.00

55,179.001,319,470.40543,322.80

33.3016,316.00

123,650.8036.40

3,397.0035.466.001,934.601,930.121,931.94

88,116.0035,797.8652,318.14

1.0014,386.1114,409.09

1.001.002.102.101.00

1978

2,081,984.8035.80

58,156.001,384,694.50566,505.10

32.9017,219.00

130,785.2036.40

3,593.0037,344.001,928.131,917.761,921.97

92,539.0037,609.5754,929.43

0.9915,373.0815,666.28

0.981.012.072.111.02

1 -** —T —

* <*T -^ r

iT

rr"

0000*

»O

fO

'<

mN

fi

te

hc

i<S

O

— <N

«o

©

a S

ag

8

S

g 8 8*

m In «

""

5 <n """

~* " 5

*o «o r^

?5

-2a"a"

A d

iaHA

333


Glossary of variables in Table LIecp Employee compensation per productive workerecu Employee compensation per unproductive workerep Rate of exploitation of productive workerseu Rate of exploitation of unproductive workersh Average hours worked per full-time equivalent employee in domestic

industrieshp Average productive worker hoursHJ, Production worker hours in the roughly productive sectorsHJ Total hours of production and nonsupervisory workers in the private

nonagricultural sectorhp Average hours of production and nonsupervisory workers in the

private nonagricultural sector(Hp)fire Total "production" worker hours in finance, insurance, and real estate(hp)fire Hours per "production" worker in finance, insurance, and real estate(Hp)t Total "production" worker hours in trade(hp)t Hours per "production" worker in tradehu Average unproductive worker hoursL Total employmentLp Total productive employmentLp Number of production workers in the roughly productive sectorsLp Number of production and nonsupervisory workers in the private

nonagricultural sector(Lp)fire Number of "production" workers in finance, insurance, and real

estate(Lp)t Number of "production" workers in tradeLu Total unproductive employment

(2) The private nonagricultural sector includes unproductive sectorssuch as trade, finance, and real estate. Hence we need to adjust total hoursfor this, in order to better approximate hours per productive worker hp.We calculate as follows:

(Hp)t = (hp)t • (Lp)t = total "production" worker hours in trade;

(Hp)fire = (hp)fire-(Lp)fire = total "production" worker hours in finance,insurance, and real estate;

Hp = Hp - (Hp)t - (Hp)fire = production worker hours in the roughlyproductive sectors;

Lp = Lp — (Lp)t — (Lp)fire = number of production workers in theroughly productive sectors;

hp = Hp/Lp = average productive worker hours.

Rates of exploitation 335

(3) Total productive worker hours can now be calculated as the prod-uct of average hours hp (just calculated) and our previously calculatedtotal productive employment Lp (which includes self-employed persons)from Table F.I:

(4) Finally, we can estimate average hours hu of unproductive workersby noting that total hours of all workers H = Hu + Hp = hu• Lu + hp• Lp,that total employment L = Lu + Lp, and that average hours worked h =H/L, so that

hu = h . (L /L u ) -h p . (L p /L u ) .

Measures of productivity

The Marxian measure of productivity q* is the primary one. It is derivedby deflating our measure of total product TP* by the GNP price deflatorpy (in 1982 dollars), and then dividing by hours of productive labor Hp toobtain hourly productivity. Because orthodox measures of productivityare based on value added rather than total product, we also calculate aquasi-Marxian measure y*, which is real Marxian value added per pro-ductive worker hour. This differs greatly in level from q*, but has essen-tially the same trend, because the proportion CVTP* of circulating con-stant capital to total product is extremely stable (see Section 5.2, Figure5.6, and Appendix E). These Marxian productivity measures are listed inTable J.I.

Orthodox measures of productivity vary considerably. The most com-mon one is real GDP per employee hour, which we call y. Also availableis the BLS measure y! of real GDP originating in the nonfarm businesssector by their estimate of hours of persons engaged in production (em-ployees plus self-employed persons) in this same sector. Since the BLSmeasure is only available in index-number form, we calculate an equiva-lent measure of productivity y2 in the nonfarm business sector, as theratio of real GDP to total hours of all persons engaged. The total-hoursmeasure H2 is in turn calculated by multiplying the average hours perfull-time equivalent employee in domestic industries (from NIPA) by esti-mated nonfarm total employment (based on our employment data inTable F.I).

Table J.I presents the calculations of Marxian and orthodox measuresof productivity, along with associated measures of hours worked.

336

Measures of productivity 337

Glossary of variables in Table J.IFEE Total full-time equivalent employees in domestic industriesGDP Total GDPGDP2 Nonfarm private business GDPGDP2r Nonfarm private business GDP in 1982 dollarsGDPr Total GDP in 1982 dollarsGFPr Marxian gross final product in 1982 dollarsGFP* Marxian gross final producth Average annual full-time equivalent employee hours in domestic

industriesH1 Total hours worked in domestic industriesH2 Total hours worked in nonfarm private businesses by workers and the

self-employedHp Total hours worked by productive workershp Average annual productive worker hoursL Total employmentL' Total nonfarm, nongovernment employmentLfarm Total employment in farmsLgovm Total employment in governmentLp Total productive employmentpy Implicit price deflator for GNP (1982 = 100)q* Marxian measure of productivity: total real product per productive

worker hourTPr Total product in 1982 dollarsTP* Marxian total producty* Quasi-Marxian measure of productivity: real Marxian value added

per productive worker houry Orthodox measure of productivity: GDP per full- and part-time

workers' hoursy, BLS measure of productivity (1948 = 100): nonfarm private

business product per person engaged in productiony2 Orthodox measure of productivity: nonfarm real GDP per hour

of persons engaged in production


Table J.I. Productivity of labor, 1948-89

23456

789

1011

1213141516

17

1819202122

2324252627282930313233

Sources*

Table E.2704 1see line 23

Table H.Isee line 23

107 2see line 28

B-46*

107 4see line 26

Table I.ITable F.I

6112607B2

Table F.ITable F.I610B5

Variables

q*=TPr/Hp

q* (index numbers, 1948 = 100)TPr=TP*/py

TP*py (price deflator for GNP)

Hp

y*=GFPr/Hp

y* (index numbers, 1948 = 100)GFPr = GFP*/py

GFP*

HP

y = GDPr/Hly (index numbers, 1948 = 100)GDPr = GDP/pyGDP

HI = total hrs. in domestic industries

y,(BLS; 1948 = 100)

y2=GDP2r/H2 (nonfarm prv. bus.)y2 (index numbers, 1948 = 100)

GDP2r=GDP2/pyGDP2 (nonfarm prv. bus.)

H2 = total hrs. in prv. non-agr.

Derivation of hours workedHp = h p xL p

hP

LPH2 = h x L 'h = HI/FEE domestic industries

HI = total hrs. in domestic industriesFEE domestic industries

L'=L-L g o v m -L r a r m

L

L,ovn,

Lf»rm

Units

1982 $/hr by prod, workers

billions of 1982 $billions of $

millions

1982 $/hr by prod, workers

billions of 1982 $billions of $millions

1982 $/hr pt & ft workers


GDP in 1982 $/hr by PEP

1982 $/hr by workers & SEP


millionshours/prod, worker/yearthousandsmillionshours /worker/yearmillionsthousandsthousandsthousandsthousandsthousands

1948

27.56100.00

1,890.71446.21

23.668,605.51

15.30100.00

1,049.74247.7

68,605.51

11.11100.00

1,102.12260.10

99,227

100.0

9.59100.00908.47214.40

94,683

68,605.512,079.34

32,993.9194,683.48

2,063.3699,22748,090.0045,888.0058,3016,063.006,350.00

1949

28.98105.15

1,838.13431.96

23.563,430.64

16.30106.50

1,033.61242.9

63,430.64

11.51103.61

1,102.13259.00

95,769

101.7

10.03104.57907.66213.30

90,467

63,430.642,032.94

31,201.3690,467.012,043.94

95,76946,855.0044,261.0056,9196,487.006,171.00

" Unless otherwise indicated, all data come from NIPA (e.g. BEA 1986), where the first three digits (and following letter,if any) denote the relevant table number and subsequent digits the line numbers within those tables.* Table number from CEA (1989).


1950

30.30109.%

2,015.13481.6223.9

66,497.62

16.93110.64

1,125.76269.1

66,497.62

11.98107.82

1,200.00286.80

100,205

108.2

10.57110.16997.07238.30

94,331

66,497.622,063.47

32,226.0794,331.332,061.66

100,20548,604.0045,755.0058,6006,718.006,127.00

1951

32.04116.25

2,197.70551.6225.1

68,597.01

17.83116.54

1,223.22307.0

68,597.01

12.14109.27

1,320.32331.40

108,785

111.4

10.87113.27

1,080.08271.10

99,379

68,597.012,070.%33,123.3699,378.602,065.52

108,78552,667.0048,113.0062,3668,518.005,735.00

1952

33.02119.82

2,250.805.73.9525.5

68,160.46

18.39120.18

1,253.36319.6

68,160.46

12.34111.08

1,370.20349.40

111,053

114.1

11.20116.71

1,124.31286.70

100,404

68,160.462,080.0832,768.23100,403.712,063.42

111,05353,820.0048,659.0063,4579,218.005,580.00

1953

34.21124.14

2,337.35605.3725.9

68,318.52

19.03124.36

1,300.05336.7

68,318.52

12.68114.16

1,426.64369.50

112,508

116.5

11.60120.92

1,183.01306.40

101,968

68,318.522,067.58

33,042.76101,968.332,054.12

112,50854,772.0049,641.0064,2479,204.005,402.00

1954

35.77129.78

2,268.555%.6326.3

63,427.87

20.10131.35

1,274.76335.3

63,427.87

13.02117.22

1,407.98370.30

108,142

118.3

11.95124.50

1,166.54306.80

97,653

63,427.872,030.9731,230.3197,653.282,040.61

108,14252,995.0047,855.0062,3249,049.005,420.00

1955

36.55132.63

2,400.42652.9127.2

65,669.66

20.48133.82

1,344.63365.7

65,669.66

13.27119.51

1,482.72403.30

111,699

121.7

12.29128.06

1,245.22338.70

101,342

65,669.662,070.6531,714.45101,342.272,060.22

111,69954,217.0049,190.0063,3668,939.005,237.00

1956

37.32135.41

2,445.57687.2128.1

65,534.53

20.86136.32

1,366.90384.1

65,534.53

13.26119.39

1,513.17425.20

114,113

122 A

12.39129.12

1,286.12361.40

103,815

65,534.532,056.6831,864.18103,815.482,054.57

114,11355,541.0050,529.0064,5229,031.004,%2.00

1957

38.67140.32

2,464.%717.3029.1

63,740.01

21.71141.88

1,383.76402.7

63,740.01

13.52121.72

1,538.14447.60

113,771

124.7

12.63131.65

1,305.84380.00

103,378

63,740.012,027.79

31,433.17103,377.542,033.15

113,77155,958.0050,846.0064,7799,209.004,724.00

1958

40.70147.69

2,396.20711.6729.7

58,871.32

23.09150.88

1,359.16403.7

58,871.32

13.87124.89

1,528.28453.90

110,174

127.6

12.81133.47

1,275.76378.90

99,621

58,871.322,005.91

29,348.9799,621.272,034.46

110,17454,154.0048,%7.0062,7659,231.004,567.00

(more)


Table J.I (cont.)

23456

7891011

1213141516

17

1819202122

2324252627282930313233

1959

41.61150.97

2,547.01774.2930.4

61,216.73

23.61154.30

1,445.26439.4

61,216.73

14.21127.97

1,620.72492.70

114,022

131.7

13.33138.89

1,374.67417.90

103,153

61,216.732,039.17

30,020.46103,152.522,048.14

114,02255,671.0050,364.0064,0999,309.004,426.00

1960

42.57154.46

2,574.98795.6730.9

60,489.83

24.18158.02

1,462.61451.9

60,489.83

14.34129.07

1,656.31511.80

115,534

133.1

13.41139.75

1,399.35432.40

104,358

60,489.832,013.19

30,046.71104,358.482,038.21

115,53456,684.0051,201.0064,9899,545.004,243.00

1961

43.82159.02

2,600.71811.4231.2

59,343.48

25.05163.74

1,486.80463.9

59,343.48

14.72132.57

1,698.72530.00

115,368

137.5

13.79143.74

1,426.28445.00

103,414

59,343.482,021.01

29,363.23103,413.692,039.64

115,36856,563.0050,702.0064,7409,894.004,144.00

1962

44.88162.84

2,725.78869.5231.9

60,736.75

25.71168.02

1,561.50498.1

60,736.75

15.05135.49

1,787.15570.10

118,759

141.8

14.16147.60

1,500.63478.70

105,959

60,736.752,028.85

29,936.58105,959.312,044.68

118,75958,082.0051,822.0066,09110,268.004,001.00

1963

46.09167.26

2,819.18913.4232.4

61,160.48

26.43172.73

1,616.48523.7

61,160.48

15.40138.66

1,858.02602.00

120,646

147.0

14.56151.70

1,562.35506.20

107,339

61,160.482,037.80

30,013.06107,339.382,047.17

120,64658,933.0052,433.0066,65510,460.003,762.00

1964

48.01174.20

2,958.52973.3532.9

61,625.11

27.67180.85

1,705.31561.0

61,625.11

15.88142.98

1,958.66644.40

123,339

152.9

15.08157.12

1,654.10544.20

109,719

61,625.112,035.18

30,279.87109,719.322,048.07

123,33960,222.0053,572.0067,87410,770.003,532.00

1965

48.71176.74

3,127.771,057.19

33.864,214.98

28.09183.61

1,804.07609.8

64,214.98

16.18145.68

2,068.93699.30

127,866

156.7

15.36160.07

1,745.56590.00

113,654

64,214.982,047.33

31,365.18113,654.132,042.52

127,86662,602.0055,644.0070,12811,118.003,366.00

1966

49.36179.11

3,284.821,149.69

35.066,546.13

28.59186.86

1,902.69665.9

66,546.13

16.32146.94

2,189.71766.40

134,171

160.3

15.51161.63

1,834.00641.90

118,263

66,546.132,043.4532,565.57118,262.702,031.97

134,17166,030.0058,201.0073,30112,023.003,077.00


1967

50.64183.73

3,342.091,199.81

35.966,003.05

29.51192.84

1,947.50699.2

66,003.05

16.57149.16

2,257.38810.40

136,251

164.3

15.83165.01

1,888.02677.80

119,247

66,003.052,008.84

32,856.32119,246.952,005.20

136,25167,949.0059,469.0075,13712,695.002,973.00

1968

51.73187.70

3,468.051,307.46

37.767,043.56

30.16197.11

2,022.06762.3

67,043.56

16.89152.06

2,349.87885.90

139,131

169.2

16.18168.65

1,963.93740.40

121,368

67,043.562,004.5733,445.35121,368.45

1,992.88139,13169,814.0060,901.0076,92913,099.002,929.00

1969

51.63187.36

3,533.321,406.26

39.868,429.60

30.10196.71

2,059.60819.7

68,429.60

16.82151.46

2,404.77957.10

142,950

168.6

16.04167.19

2,007.29798.90

125,128

68,429.602,005.2434,125.42125,128.12

1,994.39142,95071,676.0062,740.0078,87513,325.002,810.00

1970

52.93192.07

3,467.511,456.35

42.065,507.62

31.04202.83

2,033.06853.9

65,507.62

17.06153.61

2,400.481,008.20

140,6%

169.4

16.07167.50

1,978.81831.10

123,129

65,507.621,970.32

33,247.21123,129.26

1.976.68140,69671,178.0062,291.0078,27513,251.002,733.00

1971

55.03199.69

3,531.121,567.82

44.464,164.82

32.40211.76

2,079.09923.1

64,164.82

17.61158.57

2,462.611,093.40

139,823

174.5

16.49171.86

2,021.40897.50

122,585

64,164.821,960.58

32,727.42122,584.85

1,975.04139,82370,795.0062,067.0077,93713,198.002,672.00

1972

55.58201.67

3,717.011,728.41

46.566,877.80

32.61213.12

2,180.821,014.1

66,877.80

17.97161.76

2,584.091,201.60

143,825

179.8

16.80175.06

2,126.67988.90

126,613

66,877.801,973.01

33,896.34126,612.82

1,980.46143,82572,622.0063,931.0079,85613,231.002,694.00

1973

57.21207.60

3,999.831,979.91

49.569,911.08

33.01215.77

2,308.111,142.5

69,911.08

18.09162.90

2,713.331,343.30

149,963

183.7

16.74174.46

2,218.991,098.40

132,559

69,911.081,971.43

35,462.13132,559.45

1,973.64149,96375,983.0067,165.0083,29913,418.002,716.00

1974

57.60208.99

4,004.402,162.38

54.069,525.84

32.92215.13

2,288.561,235.8

69,525.84

17.92161.37

2,691.301,453.30

150,157

180.2

16.58172.85

2,203.521,189.90

132,867

69,525.841,949.83

35,657.47132,867.08

1,947.94150,15777,085.0068,209.0084,61213,630.002,773.00

1975

61.64223.67

3,994.072,368.48

59.364,796.39

35.00228.72

2,267.641,344.7

64,796.39

18.25164.34

2,665.941,580.90

146,052

183.5

16.93176.40

2,172.681,288.40

128,370

64,976.391,927.59

33,615.19128,369.70

1,939.06146,05275,321.0066,202.0082,82713,902.002,723.00

(more)


Table J.I (cont.)

123456

7891011

1213141516

17

1819202122

2324252627282930313233

1976

63.70231.13

4,270.032,694.39

63.167,035.79

35.63232.85

2,388.361,507.1

67,035.79

18.58167.32

2,791.921,761.70

150,229

188.4

17.34180.70

2,295.881,448.70

132,420

67,035.791,933.14

34,677.07132,419.58

1,934.54150,22977,656.0068,450.0085,15113,997.002,704.00

1977

65.61238.08

4,543.983,058.10

67.369,254.48

36.28237.09

2,512.381,690.8

69,254.48

18.81169.34

2,919.911,965.10

155,247

191.8

17.57183.17

2,424.671,631.80

137,962

69,254.481,934.60

35,797.86137,961.91

1,931.94155,24780,358.0071,411.0088,11614,125.002,580.00

1978

66.02239.57

4,787.753,456.76

72.272,516.17

36.50238.53

2,646.641,910.9

72,516.17

18.94170.55

3,073.682,219.20

162,255

193.5

17.65183.98

2,562.471,850.10

145,157

72,516.171,928.13

37,609.57145,157.12

1,921.97162,25584,421.0075,525.0092,53914,447.002,567.00

1979

65.55237.85

4,876.913,833.25

78.674,399.03

36.30237.24

2,700.712,122.8

74,399.03

18.77169.02

3,135.372,464.40

167,014

190.5

17.38181.10

2,613.872,054.50

150,427

74,399.031,927.53

38,598.17150,427.45

1,917.30167,01487,109.0078,458.0095,52514,568.002,499.00

1980

66.99243.08

4,832.094,141.10

85.772,129.89

37.04242.09

2,671.922,289.8

72,129.89

18.91170.24

3,132.322,684.40

165,652

189.9

17.49182.27

2,609.572,236.40

149,213

72,129.891,905.00

37,863.38149,213.50

1,902.38165,65287,076.0078,435.0095,73414,774.002,525.00

1981

69.13250.86

4,951.494,654.40

94.071,621.12

38.26250.07

2,740.492,576.1

71,621.12

19.20172.85

3,192.023,000.50

166,268

191.8

17.68184.27

2,658.512,499.00

150,362

71,621.121,897.87

37,737.65150,362.28

1,893.09166,26887,829.0079,427.0096,58214,741.002,414.00

1982

70.28255.00

4,763.864,763.86

100.067,787.90

39.08255.42

2,649.252,649.3

67,787.90

19.10171.93

3,114.803,114.80

163,114

190.1

17.48182.17

2,581.302,581.30

147,680

67,787.901,872.45

36,202.80147,679.51

1,895.20163,11486,067.0077,923.0094,99014,657.002,410.00

1983

71.66260.02

4,896.035,086.97103.9

68,322.81

40.17262.51

2,744.332,851.4

68,322.81

19.56176.10

3,229.843,355.80

165,129

195.6

17.94187.00

2,696.822,802.00

150,308

68,322.811,893.23

36,087.93150,308.34

1,903.75165,12986,739.0078,954.0095,95214,697.002,301.00


1984

73.13265.37

5,284.145,691.02107.7

72,254.44

41.04268.23

2,965.433,193.8

72,254.44

19.90179.14

3,458.503,724.80

173,815

199.8

18.20189.72

2,896.103,119.10

159,095

72,254.441,907.86

37,871.95159,095.19

1,905.97173,81591,195.0083,472.00100,60714,894.002,241.00

1985

74.25269.41

5,374.606,014.18111.9

72,387.05

41.92273.96

3,034.443,395.5

72,387.05

20.01180.19

3,551.563,974.20

177,456

202.5

18.40191.73

2,987.313,342.80

162,383

72,387.051,893.51

38,229.04162,383.30

1,893.79177,45693,704.0085,745.00103,03115,202.002,084.00

1986

74.75271.25

5,417.296,224.47114.9

72,468.79

42.75279.42

3,098.343,560.0

72,468.79

20.45184.08

3,660.054,205.40

179,011

206.7

19.62204.44

3,212.453,691.10

163,771

72,468.791,891.53

38,312.30163,771.43

1,875.64179,01195,440.0087,315.00104,83115,483.002,033.00

1987

74.47270.21

5,547.096,606.59

119.174,490.29

42.81279.78

3,188.863,797.9

74,490.29

20.54184.95

3,775.824,497.00

183,804

208.7

19.64204.71

3,314.443,947.50

168,743

74,490.291,893.32

39,343.69168,742.73

1,872.36183,80498,167.0090,123.00107,89115,768.002,000.00

1988

78.01283.05

5,957.317,226.22121.3

76,370.62

44.29289.48

3,382.714,103.276,370.62

21.07189.67

3,990.274,840.20

189,408

213.9

19.37201.84

3,376.174,095.30

174,335

76,370.621,883.93

40,538.03174,335.021,875.22

189,408101,006.0092,968.00110,96216,003.001,991.00

1989

78.03283.13

6,050.537,641.82126.3

77,542.07

44.56291.19

3,454.934,363.677,542.07

21.15190.41

4,088.045,163.20

193,299

212.4

19.33201.47

3,441.494,346.60178,029

77,542.071,884.46

41,148.07178,028.62

1,868.16193,299103,470.0095,296.00113,51116,324.001,891.00

K

Government absorption of surplus value

A useful supplementary measure concerns the relation between total sur-plus value and the portion absorbed by government purchases of com-modities and of (administrative) labor power. Government purchases ofcommodities directly absorb a portion of the surplus product, and gov-ernment administrative employment indirectly absorbs another portionthrough the consumption expenditures of government workers (see Sec-tion 3.2.B). Thus, total government expenditure G£ s G* 4- WG is a mea-sure of the total absorption of the surplus product by unproductive gov-ernment expenditures. Table K.I shows G£ and G£/SP* for the postwarperiod (where SP* = Marxian surplus product).

344

Table K.I. Government absorption of surplus value, 1948-89 (billions of dollars)

Sources Variables 1948 1949 1950 1951 1952 1953 1954 1955 1956 1957 1958 1959 1960

Table E.2 G*Table E.2 WGTable H.I SP*

G*/SP*

Sources Variables 1962 1963 1964 1965 1966 1967 1968 1969 1970 1971 1972 1973 1974

Table E.2 G*Table E.2 WGTable H.I SP*

G*/SP*

Sources Variables

1961

G*=G* + WG 32.50 38.86 38.62 60.20 75.56 82.36 75.59 74.85 79.09 86.73 94.63 96.72 99.03 106.3714.40 18.76 17.42 32.50 44.06 49.96 42.59 40.05 41.89 46.93 51.73 51.92 50.93 54.7718.10 20.10 21.20 27.70 31.50 32.40 33.00 34.80 37.20 39.80 42.90 44.80 48.10 51.60

149.91 148.58 165.09 188.26 194.79 204.29 208.23 228.16 236.74 249.88 256.04 278.34 285.93 295.950.22 0.26 0.23 0.32 0.39 0.40 0.36 0.33 0.33 0.35 0.37 0.35 0.35 0.36

1975

G* = G* + W G 115.66 120.82 126.81 135.10 154.54 175.30 192.22 200.46 210.13 222.76 238.64 253.47 284.33 318.2960.26 61.52 62.41 65.80 76.14 87.90 94.42 92.96 90.63 92.46 96.04 98.47 115.63 130.5955.40 59.30 64.40 69.30 78.40 87.40 97.80 107.50 119.50 130.30 142.60 155.00 168.70 187.70

319.54 337.07 364.00 394.44 430.09 453.42 493.12 523.25 546.86 596.04 645.51 719.63 778.82 868.780.36 0.36 0.35 0.34 0.36 0.39 0.39 0.38 0.38 0.37 0.37 0.35 0.37 0.37

1976 1977 1978 1979 1980 1981 1982 1983 1984 1985 1986 1987 1988 1989

G* = G* + W G 337.29 363.34 396.97 435.78 494.43 547.37 598.61 624.39 679.89 755.83 797.00 837.34 871.73 925.91Table E.2 G* 133.49 142.84 156.47 175.38 206.13 230.67 254.71 257.99 289.29 336.83 353.20 365.44 366.63 384.31Table E.2 W G 203.80 220.50 240.50 260.40 288.30 316.70 343.90 366.40 390.60 419.00 443.80 471.90 505.10 541.60Table H.I SP* 971.25 1086.66 1221.76 1347.44 1463.67 1669.40 1726.06 1867.15 2103.70 2258.31 2389.25 2555.52 2755.18 2945.32

G*/SP* 0.35 0.33 0.32 0.32 0.34 0.33 0.35 0.33 0.32 0.33 0.33 0.33 0.32 0.31

Aglietta's index of the rate of surplus value

Aglietta distinguishes between productive and unproductive labor. How-ever, he believes that price-value deviations make the money form of therate of surplus value a biased indicator of the trend of the value rate ofsurplus value. For this reason, he sets out "to find a more faithful statisti-cal indicator [of the] long run trend" in the rate of surplus value (Aglietta1979, p. 88). He concludes that the share of real wages in productivity isa more appropriate measure of the share of the value of labor power inlabor value added, assuming that social productivities (the reciprocals ofthe unit labor values) of the consumer and producer sectors rise at roughlythe same rate in the long run. To see this, we will derive his results in asomewhat different way. Using our own notation, the share of produc-tion worker wages in current-dollar value added can be written as

v*' = Wp/VA = (w-Hp)/(py-VAr) = (pc wr)/(py-y) = (pc/py)-(wr/y)f

whereVA = current-dollar (NIPA) net output (value added);

VAr m constant-dollar (NIPA) net output (value added);H p s total hours of productive labor;

w = nominal wage rate of production workers;pc • price index of consumer goods;wr B hourly real wage of production workers = w/pc;py B price index for net output; and

y B real (constant-dollar) net output per labor hour = VAr/Hp.By way of contrast, the constant-dollar wage share, which Aglietta

(1979, p. 89) calls the "real social wage cost," is

w' = (Wp/pc)/(VA/py) = wr/yr.

Finally, since the aggregate value of labor power is the value of thereal wage of an hour of productive labor (Ac* wr) multiplied by the hours

346

Aglietta's index of the rate of surplus value 347

worked by productive labor Hp, and since the value added by living (pro-ductive) labor (V + S) is also the labor value of real net output (Ay-VAr),we can express the value ratio V/(V + S) as

= (Ac-wr.Hp)/(Ay-VAr)

= (Ac/Ay)(wr/y) = (Ac/Ay)w',

whereAc ss unit labor value of (workers') consumption goods, andAy s unit labor value of net output.

We can now see three things. First, the trend of the current-dollar pro-duction wage share v*' will reflect that of the value share v' if departmen-tal price-value deviations (pc/Ac and py/Ac) are small or at least move insimilar ways over time. Our direct comparison of money and value ratesof surplus value (Section 5.10) indicates that this is indeed the case, soAglietta is wrong to place so much emphasis on price-value deviations.

Second, an Aglietta-type index w' will reflect the equivalent Marxianvalue ratio v' if (Ac/Ay), the ratio of the unit labor values of consumergoods to that of the net product, is stable over the long run.1 These unitvalues, being quantities of direct and indirect labor required per unit prod-uct, can be thought of as reciprocals of the social productivity of labor.Thus, as Aglietta notes, the condition for w' to reflect the trend of v' isthat the social productivity of labor in the sectors producing consump-tion goods and the net product improve at roughly the same rate. Juil-lard (1992) has indeed found this to be true: in his estimates, the ratio ofthe unit labor values of the consumer and producer sectors in the U.S.

1 Aglietta defines m, as the current-dollar value added per hour of labor, which inour notation can be written as mt = (Y/L)t = [(py-Yr)/(Ay-Yr)]t = (py/Ay)t, sincethe money value of net output is its price index multiplied by its real level, andthe labor value of net output (which is equal to the total amount of living labortime L) is its unit value index multiplied by its real level. He also defines mt as theratio of the money wage bill to the value of labor power, which we can write asmt = (W/V)t = [(pc-CRw)/(Ac-CRw)]t = (pc/Ac)t, where CRw is the total realconsumption of workers (this assumes workers consume their wages). Then theratio mt/mt = (pc/Ac),/(py/Ay)t = the ratio of the price-value deviations of con-sumer goods and net product, respectively, at time t. Aglietta (1979, p. 89) callsthe index number (m,/mt)/(m0/m0) "the index of the share of wages at a con-stant rate of surplus value," and argues that the condition for his assumed cor-relation between the variable capital share v' m V/( V + S) and the real wage share("the real social wage cost") is "that the index of the share of wages at a constantrate of surplus value can be represented by the index of consumer prices [relativeto net output prices]" (p. 89). From our expression for the ratio m,/mt, it is evi-dent that this condition holds only if the index number of relative unit values ofconsumer goods and net output is roughly constant over the long run. This isprecisely the condition derived here.


economy never varies by more than 3% over the entire postwar periodfrom 1948 to 1980 - except for a four-year interval from 1955 to 1958,when it rises by a total of 10% (Juillard 1992, p. 24, fig. 7).

Finally, the index w' will reflect the trend in the Marxian money valueindex of exploitation v*' if pc/py is stable over time. A sufficient (but nota necessary) condition for this is that the two previously described rela-tions - between v*' and v' and between v' and w' - hold.

For empirical purposes, we construct an exploitation index v*' andAglietta-type measures of the "real social wage cost" v", both based onthe sketchy citations of his data sources. Because we were unable to ade-quately approximate it with any existing series from the sources he cites,we chose to estimate Aglietta's real social wage cost w' directly from hisown Diagram 1 (Aglietta 1979, p. 91). See Table L.I for further details.

Glossary of variables in Table L.Iecp Employee compensation per production workerecpr Real employee compensation per production workereCpr Real hourly employee compensation per production workerh p Average hours of productive laborpc Price deflator for personal consumptionS* Surplus value (in money form)V* Variable capital (in money form)v*' Exploitation index (productive wage bill/value added)v" Aglietta-type "real social wage cost"w' Aglietta's own "real social wage cost"y* Marxian real net final product per productive worker hour

Table L.I. Aglietta's index of S*/V*, 1948-89

Sources

Table H.ITable H.I

Table J.I

Table G.2704 2"Table I.I

Aglietta

Sources

Variables

v*'=VV(V* + S*)v*' = V*/(V* + S*)

V*

s*V=ec p r /y*v '=ec p r /y*

y*ecpr = ecp r /hp

ecpr = ecp/pcecp

pc (price deflator)hp

w'w'c

Variables

Units

index numbers"


index numbers"

index numbers"1982 $/hour1982 $/prod. worker$/prod. worker

hours/prod, worker/year

index numbers"

Units

1948

100.000.37

88.41149.94

100.000.33

100.005.01

10,426.402,679.59

25.702,079.34

100.0099.00

1959

1949

98.100.36

85.02148.64

98.050.32

106.505.24

10,644.252,724.93

25.602,032.94

96.9796.00

1960

1950

97.190.36

93.16165.26

96.380.32

110.645.35

11,033.782,890.85

26.202,063.47

92.9392.00

1961

1951

97.070.36

105.91188.25

95.040.31

116.545.55

11,501.863,197.52

27.802,070.96

92.9392.00

1962

1952

97.960.36

111.01194.51

95.170.31

120.185.73

11,928.963,387.82

28.402,080.08

99.4998.50

1963

1953

98.310.36

117.39204.52

95.010.31

124.365.93

12,250.433,552.62

29.002,067.58

100.0099.00

1964

1954

94.280.35

111.95208.20

92.090.30

131.356.07

12,318.593,584.71

29.102,030.97

96.9796.00

1965

1955

93.080.35

120.52228.55

92.710.30

133.826.22

12,881.653,800.09

29.502,070.65

96.9796.00

1966

1956

94.950.35

128.82236.97

95.540.31

136.326.53

13,431.574,042.90

30.102,056.68

96.9796.00

1967

1957

93.560.35

133.00250.25

94.610.31

141.886.73

13,648.934,231.17

31.002,027.79

93.9493.00

1968

1958

89.700.33

127.72256.15

90.740.30

150.886.87

13,771.114,351.67

31.602,005.91

95.%95.00

1969

v*'=VV(V*v*'=VV(V*

Table H.I V*Table H.I S*

Table G.2704 2*Table I.I

v"=ec'pr/y*v"=ec'pr/y*

y*ecpr = ecp r /hp

ecpr = ecp/pcecp


index numbers"


index numbers"



index numbers"

90.02 90.280.33 0.33

139.57 144.23278.42 286.46

Aglietta w'f

91.230.30

154.307.06

14,393.744,649.18

32.302,039.17

96.4695.50

91.460.30

158.027.25

14,590.294,800.21

32.902,013.19

95.%95.00

89.000.33

146.13296.54

90.070.30

163.747.39

14,944.854,976.64

33.302,021.01

93.9493.00

88.140.33

155.54320.20

89.660.29

168.027.55

15,326.015,195.52

33.902,028.85

90.9190.00

87.680.33

162.76337.71

89.320.29

172.737.74

15,764.305,422.92

34.402,037.80

86.3685.50

86.430.32

172.00364.54

87.070.32

188.43395.00

87.540.32

207.07430.65

86.930.32

216.26454.40

87.39 89.710.32 0.33

236.77 261.22493.63 523.83

87.94 89.53 90.490.29 0.29 0.30

180.85 183.61 186.867.97 8.24 8.48

16,229.34 16,874.93 17,325.635,680.27 6,007.47 6,358.51

35.00 35.60 36.702,035.18 2,047.33 2,043.45

90.12 90.92 94.390.30 0.30 0.31

192.84 197.11 196-718.71 8.99 9.31

17,505.07 18,013.43 18,669.726,581.91 7,079.28 7,654.58

37.60 39.30 41.002,008.84 2,004.57 2,005.24

86.6785.80

86.8786.00

86.3685.50

84.8584.00

83.8483.00

85.8685.00

Table L.I fcont.)

Sources

Table H.ITable H.I

Table J.I

Table G.2704 2*Table I.I

Variables

v*'=V*/(V» + S*)v*'=VV(V* + S*)

V*

s*v '=ec p r /y*v'=ec'pr/y*

y*ecpr = ecp r /h p

ecpr = ecp/pcecp


w'

Units

index numbers"


index numbers"



index numbers"

1970

89.120.33

270.43547.67

94.620.31

202.839.62

18,960.298,133.%

42.901,970.32

88.89

1971

87.670.33

287.53596.70

93.990.31

211.769.98

19,566.718,785.45

44.901,960.58

86.87

1972

90.110.33

324.30645.98

97.170.32

213.1210.38

20,487.169,567.50

46.701,973.01

85.86

1973

91.620.34

370.49719.75

98.750.32

215.7710.68

21,063.4510,447.47

49.601,971.43

83.33

1974

91.300.34

398.50778.25

96.960.32

215.1310.46

20,394.0111,175.92

54.801,949.83

82.83

1975

86.670.32

410.75867.02

93.370.31

228.7210.71

20,640.5012,219.18

59.201,927.59

1976

86.750.32

459.63968.82

93.810.31

232.8510.95

21,173.2213,254.44

62.601,933.14

1977

86.970.32

515.811,083.13

93.930.31

237.0911.17

21,602.8314,409.09

66.701,934.60

1978

87.750.33

589.201,221.07

94.880.31

238.5311.35

21,880.2815,666.28

71.601,928.13

1979

89.120.33

664.781,346.24

96.050.31

237.2411.43

22,024.5217,223.18

78.201,927.53

1980

87.810.33

706.531,462.70

93.180.31

242.0911.31

21,547.2018,659.88

86.601,905.00

Aglietta 88.00 86.00 85.00 82.50 82.00

Sources Variables Units 1981 1982 1983 1984 1985 1986 1987 1989

Table H.ITable H.I

Table J.I

Table G.2704 2*

v*'=V*/(V* + S*)v*'=VV(V* + S*)

V*

s*v*=ecpr/y*v*=ecpr/y*

y*ec p r=ec p r /hp

ecpr = ecp/pcecp

pc (price deflator)

index numbers"


index numbers"


85.320.32

772.351,668.19

90.910.30

250.0711.40

21,634.6020,466.34

94.60

84.440.31

786.531,724.68

90.600.30

255.4211.60

21,725.6021,725.60

100.00

83.680.31

839.731,865.80

89.690.29

262.5111.81

22,352.6123,269.07

104.10

82.620.31

928.682,101.78

88.160.29

268.2311.86

22,621.3824,521.58

108.40

80.880.30

967.992,258.68

86.760.28

273.9611.92

22,567.6425,320.89

112.20

79.190.29

998.552,401.11

85.300.28

279.4211.95

22,604.7926,063.32

115.30

78.920.29

1,060.902,563.38

85.240.28

279.7811.96

22,640.6026,964.96

119.10

79.260.29

1,146.222,752.81

83.250.27

289.4812.08

22,765.8828,275.23

124.20

78.380.29

1,206.402,943.35

82.030.27

291.1911.98

22,569.9829,318.41

129.90Table I.I hours/prod, worker/year 1,897.87 1,872.45 1,893.23 1,907.86 1,893.51 1,891.53 1,893.32 1,883.93 1,884.46

"1948 = 100.* Data in this row come from NIPA (e.g. BEA 1986), line 2 of table 704.f Aglietta's (1979, p. 91) social wage cost estimates.

M

Mage and NIPA measures of the capitalistsector gross product

Mage (1963) bases his calculations on "the aggregate non-farm private busi-ness economy," which is whole domestic economy minus: general gov-ernment, government enterprises, and private households and nonprofitinstitutions (p. 161); finance, insurance, and real estate (pp. 165,181); andprofessional services (pp. 165, 183). What remains is mining, construc-tion, manufacturing, transportation, communication, utilities, produc-tive services, and wholesale/retail trade, which is simply his definition ofcapitalist production and trade (i.e. primary) sectors. His own method ofderiving this estimate of the primary-sector gross product is to build it upby separately estimating its various components from a variety of datasources (Mage 1963, chap. VI and apx. to chap. VI). But it could havebeen derived far more easily in a direct manner.1

We begin by deriving the NIPA estimate of GDP in the primary sec-tors, and then compare it to Mage's own capitalist-sector gross product,as shown in Table M.I.2

Mage's estimate is somewhat larger than the direct NIPA equivalent.To see why, it is useful to break down Mage's measure into categoriescomparable to those of NIPA-IO GDP; see Table M.2. The sole con-ceptual difference between Mage's measure and the equivalent NIPA onearises from the items under the heading of net interest and net rent. As

1 We use data on gross product by sector, which were unavailable in Mage's time(and have been discontinued in recent times). But Mage could have combinedexisting data on national income by sector with corresponding data on indirectbusiness taxes by sector (which he himself uses: Mage 1963, p. 271, table D-III,footnote for column g).

2 Table M.I incorporates data from BEA (1976), which was used because it con-tains a table of gross product by sector (table 6.1) that does not appear in subse-quent NIPA summaries.

351


Table M.I. NIPA-based GDP in production and trade sectors, 1958

(billions of dollars)

GDP(PT) = [(GDP nonfarm business) — (finance, insurance, real estate)— (government enterprise) — (professional services)]"

= 370 .7-61 .2-5 .0-6 .6 = 297.9

GVA (Mage) = 305.4*

a BEA 1976, table 6.1: line 181 minus line 135 minus line 173 minus professional services.Mage's category of professional services is meant to represent noncapitalist professionalservices, which is why he only deducts it in his estimates of the unincorporated sector (Mage1963, p. 183). We estimate this as the sum of the unincorporated income of medical and legalservices - table 6.14 (BEA 1976): line 17 plus line 18 equals $6,556 million.b Mage (1963, p. 271): table D-III, column h (gross product).

Table M.2. Components of Mage's gross product and NIPA GDP

GDP (NIPA-IO)* Gross product (Mage)*

Indirect business taxes Indirect business taxesEmployee compensation Employee compensationCorporate profits Corporate profitsIncome of unincorporated enterprises Income of unincorporated enterprisesNet interest Net interest paid— Net rentsCapital consumption allowances Capital consumption allowances

a The entries under the NIPA-IO measure of GDP are quite straightforward except for netinterest and the absence of net rent. For nonfinancial sectors, net interest is only actual netinterest paid minus net interest paid to the financial sector. For nonrental sectors, net rentspaid are treated as part of the costs of operation (intermediate inputs) rather than valueadded; see Section B.I for further details.b Mage (1963, pp. 270-1, table D-III). Indirect business taxes and employee compensationappear directly in this table. The elements in columns b-e in Mage's table add up to the re-maining five elements listed under Mage's gross product above. "Other gross surplus value"in column b of Mage's table D-III represents gross surplus value minus corporate officers'salaries (which appear under employee compensation), which can also be expressed as thesum of: corporate profits net of profits taxes; profit of unincorporated enterprises, definedas their total income minus the wage equivalent for proprietors and partners; total (corporateand noncorporate) net interest paid; total net rents paid net of real estate taxes; and totalcapital consumption allowances (Mage 1963, pp. 180-8). When we add to this the elementsin column c (wage equivalent), d (corporate tax liability), and e (real estate taxes), we obtainthe last five elements listed in Table M.2.

noted in Table M.2, the NIPA category of net interest in nonfinancial sec-

tors is actual total net interest paid minus net interest paid to the financial

sectors (the latter being treated as imputed interest received). One can

therefore recover total net interest paid, as Mage (1963, pp. 182-4) did

Mage and NIPA measures of gross product 353

Table M.3. NIPA equivalent of Mage's nonfarm gross value added,1958 (billions of dollars)

GDP(PT)'=NIPA equivalent of Mage's gross value added= GDP(PT) + imputed interest receivedfl+net rents paid*= 297.9 + 2.5 + 6.9 = 307.3

GVA (Mage) = 305.4

a BEA (1976): table 8.2, lines 39 and 41.b Mage (1963): [p. 252, table B-IV, column d (after-tax corporate net rents paid)] + [p. 255,table B-V, column d (after-tax noncorporate net rents paid)] + [p. 271, table D-III, columne (real estate tax)].

from Internal Revenue Service data,3 simply by adding the imputed in-terest received by the production and trade sectors (which is listed in sep-arate NIPA tables) back into NIPA net interest. The problem of net rentspaid is somewhat more complicated, since these are treated as part of thecosts of operation (intermediate inputs) rather than value added, so thatthey appear only in input-output tables. For this category, we use Mage'sown estimates. Table M.3 illustrates the steps in the calculation of theNIPA equivalent of Mage's capitalist sector gross product in 1958, andcompares the final estimate with Mage's own (laboriously built-up) total.

Although our procedure is considerably simpler, it produces virtuallythe same result as Mage's. The difference between the two estimates is lessthan six-tenths of one percent. Table M.4 breaks down our NIPA-basedestimate into three broad elements: indirect business taxes, employee com-pensation, and gross profit-type income (defined as NIPA profit-type re-turn, net interest plus imputed interest received, and capitalist consump-tion allowances), and compares these components to the correspondingones in Mage.

It is apparent that differences between individual components are some-what greater than between totals, though no individual component differsby more than 6%-7%. Both indirect business taxes and employee compen-sation are larger in Mage than in our NIPA-based estimates, while profit-type income is correspondingly smaller. But this seems to be due to revi-sions within the NIPA data itself, since the figures in Mage are from earlierpublications than the ones we use: Mage (1963, p. 176) takes his data froma 1962 publication.

3 Mage also uses IRS data to estimate actual net rent paid. But this is already in-cluded in NIPA gross value added. Furthermore, as we are concerned only withthe GVA of the production and trade sectors, no adjustment is needed for im-puted rentals since these appear only in the revenue of the rental sector.


Table M.4. Components of NIPA-equivalent and Mage'scapitalist sector nonfarm gross product, 1958 (billions ofdollars)

NIPA-equivalent* Mage*

Indirect business taxesEmployee compensationGross property-type incomeCapitalist gross product

29.2181<g96.9

307.3

31.2183.191.1

305.5

a Each component represents (nonfarm business) minus (finance, insur-ance, and real estate) minus (government enterprise) minus (professionalservices). The latter was estimated by taking a proportion x of the relevantcomponent of the GDP of total services, where x is the ratio of noncapi-talist professional services income to the GDP of all services; from TableM l and NIPA table 6.1, line 153 (BEA 1976), respectively, x = 6.6/42.3.Thus, the indirect business tax was derived from table 6.1 (BEA 1976) asline 185 minus line 139 minus line 179 minus x-(line 157); employee com-pensation was defined as line 182 minus line 136 minus line 174 minusx-(line 154). Gross property-type income was the remainder of the ad-justed GDP(PT)' estimated in Table M.3.b Gross property-type income based on Mage's data is defined here as thesum of other gross surplus value, proprietor wage equivalent, profit taxliability, and real estate tax (Mage 1963, pp. 270-1, table D-III). See alsoTable M.5.

Finally, for the sake of completeness, it is worth summarizing the rela-tion between the category we call gross property-type income and whatMage defines as gross surplus value. Table M.5 compares the two, usingMage's own figures for 1958.

Mage and NIPA measures of gross product 355

Table M.5. Relation between gross property-typeincome and Mage's gross surplus value, 1958(millions of dollars)

Gross property-type income: 90,993°Other gross surplus value: 50,086Proprietor wage equivalent: 23,729Profit tax liability: 15,513Real estate tax: 1,665

Other gross surplus value: 50,086ft

Corporate gross surplus value: 53,001Noncorporate gross surplus value: 7,460less Corporate officers' salaries: —10,375

Mage's gross surplus value: 60,461Gross property-type income: 90,993less Proprietor wage equivalent: —23,729less Profit tax liability: -15,513less Real estate tax: — 1,665plus Corporate officers' salaries: +10,375

a Mage (1963): pp. 270-1, table D-III, columns b-e.b Mage (1963): table B-IV, column g; table B-V, column g; table B-IV,column b.

N

The net transfer between workers andthe state, and its impact on the rate ofsurplus value

In order to measure the net impact of state expenditures and taxes on therate of surplus standard of living of wage and salary earners, we need toexamine the net transfer between these wage and salary earners and thestate. This net transfer is defined as benefits received by workers minustaxes paid. In this appendix we briefly outline the methods of allocatingvarious government expenditures and taxes to labor, and then report esti-mates of the net transfer for the period 1952-85. Because the net transferis negative over most of this period, it actually represents a net tax onworkers. What follows is a brief summary of the methodology in Shaikhand Tonak (1987).

In determining the portion of state expenditures directed toward work-ers, we begin by classifying them into three major groups. The first groupconsists of items such as labor training and services, housing and com-munity services, income support, social security, and welfare (except forthe small items called military disability and military retirement, whichwe treat as a cost of war). These services are assumed to be received en-tirely by workers either in money or in commodity form. The secondgroup includes such conventional categories as education, health and hos-pitals, recreational and cultural activities, energy, natural resources, trans-portation, and postal services; these are treated as social consumption ingeneral, and the workers' share in them is estimated by multiplying thegroup total by the share of total labor income in personal income. Thelast group comprises two kinds of expenditures, (a) Central executive,legislative and judicial activities, international affairs, space, national de-fense, civilian safety, veteran benefits, and agriculture; these are the ex-penses of reproducing and maintaining the system itself, what Marx callsthe faux frais of capitalist society (Marx 1977, p. 446). (b) Economic

356

Net transfer between workers and the state 357

development, regulation and services, net interest, and others and unallo-cables; this set represents expenditures directed mainly toward small busi-nesses, related administrative activities, and interest payments to the high-est income brackets. We therefore exclude both (a) and (b) from laborincome and consumption.

Our point of departure on the tax side is total employee compensation.This is the total cost incurred by capitalists for the purchase of laborpower; it includes wages and also such benefits as employer contributionsfor social insurance and other labor income. Two main groups of taxesflow out of this total. Employee compensation is the cost to capitalists ofhiring workers. But the income received by workers is less than this be-cause a certain portion, labeled employee and employer contributions, isdeducted for social security.1 Accordingly, our first group of taxes con-sists of the portion of employee compensation which goes toward socialsecurity taxes; the second group consists of personal income taxes, motorvehicle licenses, property taxes (primarily on homes), and other taxes andnontaxes (a very small category which includes passport fees, fines, etc.).Since these are levied on both earned and unearned incomes, the portionemanating from labor is estimated by using the share of total labor in-come in personal income.

To summarize, social welfare expenditures directed toward workers arethe sum of all government expenditures on labor training and services,housing and community services, income support, social security and wel-fare (except for military disability and retirement), and the bulk of edu-cation, health and hospitals, recreational and cultural activities, energy,natural resources, transportation, and postal service expenditures. Sim-ilarly, taxes levied directly on workers' compensation include all socialsecurity contributions as well as the bulk of personal income taxes, motorvehicle licenses, property taxes, and other taxes and nontaxes.2 The nettransfer is then the difference between social welfare expenditures directedtoward the working class and taxes taken out of the flow of employeecompensation. Table N.I illustrates the calculations for 1964. Table N.2presents the whole series from 1952 to 1985, with rates calculated relativeto total employee compensation EC.

1 An additional very small category was added here. It consists of net governmentreceipts from lotteries, etc., which we treat as a kind of direct tax. It is actuallylisted as a net expenditure in government accounts, but since it is consistentlynegative we treat it as a positive net tax (Tonak 1987).

2 We leave out the group of taxes comprising corporate profit taxes, indirect busi-ness taxes, and estate and gift taxes (which only apply to the highest income lev-els), because they are generally not levied on workers.


Table N.I. Estimation of the net transfer for the UnitedStates, 1964

Social welfare expenditures0

Group IIncome support, social security, welfareHousing and commu ty servicesLabor training and services

Group IIb

EducationHealth and hospitalsRecreational and cultural activitiesEnergyNatural resourcesPostal serviceTransportation

Bl = Total benefits and income received by labor

Taxes0

Group IContributions for social insurance

Group II*Personal income taxes (federal and state)Other taxes and nontaxesMotor vehicle taxes and licensesPersonal property taxes

Tl = Total taxes paid by labor

Net transfer:

Total

29.92.80.7

27.66.41.21.02.00.8

13.1

30.1

50.03.81.18.4

68.0-76.2 =

Labor

29.92.80.7

20.14.70.90.71.50.66.7

68.0

30.1

36.42.80.86.1

76.2

-8 .1

Note: All figures are rounded.a The data for social welfare expenditures are directly available in BEA (1981,pp. 151, 159).b To obtain the portions of these expenditures directed toward labor, all itemsin this group are multiplied by the "labor share" (0.727 for 1964); transportationis also adjusted by the gas share of passenger cars (Tonak 1984, chap. IV, apx. II).c The data for the taxes are directly available in BEA (1981, pp. 121,123,129,134).d To obtain the portions of these taxes paid by labor, all items in this group aremultiplied by the "labor share" (0.727 for 1964), except for property taxes. Forproperty taxes we consider only the part paid by homeowners, which in turn isadjusted by using the "labor share" (Tonak 1984, chap. IV, apx. I).

Table N.2. Benefit, tax, net transfer rates, and adjusted and unadjusted rates of surplus value, 1952-89

Sources"

S & TS & TS & TTable G.2

TableH.lTable H.I

Sources*


Table H.ITable H.I

Sources*


Table H.ITable H.I

Variables

Benefit rate (Bl/EC)Tax rate (Tl/EC)Net transfer rate (Ntrrate)V*NtrV* = Net transfer out of V* = (Ntrrate)V*S*SVV*(S* •/V**) = (S* - NtrV*)/( V* + NtrV*)

Variables

Benefit rate (Bl/EC)Tax rate (Tl/EC)Net transfer rate (Ntrrate)V*NtrV* = Net transfer out of V* = (Ntrrate)V*S*S*/V*(S*V V**) = (S* - NtrV*)/( V* + NtrV*)

Variables

Benefit rate (Bl/EC)Tax rate (Tl/EC)Net transfer rate (Ntrrate)V*NtrV* = Net transfer out of V* = (Ntrrate)V*S*SVV*(S*V V**) = (S* - NtrV*)/( V* + NtrV*)

1952

0.110.18

-0.07111.01-7.55194.51

1.751.95

1965

0.190.21

-0.02188.43-3.46395.00

2.102.15

1978

0.280.29

-0.01589.20-3.06

1221.072.072.09

1953

0.110.17

-0 .06117.39-7.38204.52

1.741.93

1966

0.200.23

-0.03207.07-6.34

430.652.082.18

1979

0.280.30

-0 .02664.78

-11.101346.24

2.032.08

1954

0.130.17

-0.04111.95-4 .72208.20

1.861.99

1967

0.210.24

-0.02216.26-5.12

454.402.102.18

1980

0.290.300.00

706.53-1 .82

1462.702.072.08

1955

0.130.17

-0.05120.52-5.69228.55

1.902.04

1968

0.220.25

-0.03236.77-7.26

493.632.082.18

1981

0.300.31

-0.01772.35-10.521668.19

2.162.20

1956

0.130.18

-0.05128.82-6.30236.97

1.841.99

1969

0.220.26

-0.05261.22

-12.24523.83

2.012.15

1982

0.300.31

-0.01786.53-6.01

1724.682.192.22

1957

0.140.19

-0.04133.00-5.90250.25

1.882.02

1970

0.240.25

-0.02270.43-4.82547.67

2.032.08

1983

0.300.310.00

839.73-2.49

1865.802.222.23

1958

0.170.19

-0 .02127.72-2.55256.15

2.012.07

1971

0.250.250.01

287.531.48

596.702.082.06

1984

0.290.31

-0 .02928.68-18.232101.78

2.262.33

1959

0.160.19

-0.03139.57-4.37278.42

1.992.09

1972

0.260.27

-0.01324.30-3.55645.98

1.992.02

1985

0.290.31

-0.03967.99-24.262258.68

2.332.42

1960

0.170.21

-0.04144.23-5.74286.46

1.992.11

1973

0.260.27

-0.01370.49-5.20719.75

1.941.98

1986

0.290.31

-0 .02998.55-24.912401.11

2.402.49

1961

0.180.21

-0.02146.13-3.58296.54

2.032.11

1974

0.270.28

-0.01398.50-2 .30778.25

1.951.97

1987

0.280.32

-0.031060.90-35.252563.38

2.422.53

1962

0.180.21

-0.03155.54-4.75320.20

2.062.16

1975

0.310.270.04

410.7515.77

867.022.112.00

1988

0.280.31

-0.031146.22-39.012752.81

2.402.52

1963

0.180.22

-0.04162.76-5.91337.71

2.072.19

1976

0.300.280.02

459.639.28

968.822.112.05

1989

0.290.32

-0.041206.40-65.772943.35

2.442.58

1964

0.190.21

-0.02172.00-3.76364.54

2.122.19

1977

0.290.280.01

515.813.64

1083.132.102.08

* S & T denotes Shaikh and Tonak (forthcoming).

REFERENCES

Aglietta, M. 1979. A Theory of Capitalist Regulation: The U.S. Experience (trans. D. Fern-bach). London: New Left Books.

Amsden, A. 1981. "An International Comparison of the Rate of Surplus Value in Manufac-turing Industry," Cambridge Journal of Economics 5: 229-49.

Bach, G. L. 1966. Economics: Art Introduction to Analysis and Policy. New York: Prentice-Hall.

Baran, P. A. 1957. The Political Economy of Growth. New York: Monthly Review Press.Baran, P. A., and Sweezy, P. M. 1966. Monopoly Capital. New York: Monthly Review

Press.BE A. See U.S. Department of Commerce, Bureau of Economic Analysis.BIE. See U.S. Bureau of Interindustrial Economics.Beckerman, W. 1968. An Introduction to National Income Analysis. London: Weidenfeld

and Nicolson.BLS. See U.S. Department of Labor, Bureau of Labor Statistics.Boddy, R., and Crotty, J. 1975. "Class Conflict and Macro-Policy: The Political Business

Cycle," Review of Radical Political Economics 7:1-19.Bottomore, T. (ed.) 1983. A Dictionary of Marxist Thought. Oxford: Basil Black well.Bowles, S., and Gintis, H. 1982. "The Crisis of Liberal Democratic Capitalism: The Case

of the United States," Politics and Society 11: 51-93.Bowles, S., Gordon, D. M., and Weisskopf, T. E. 1984. Beyond the Wasteland. New York:

Anchor Press.Carson, C. S. 1984. "The Underground Economy: An Introduction," Survey of Current

Business 64: 21-37.Carson, C. S., and Honsa, J. 1990. "The United Nations System of National Accounts: An

Introduction," Survey of Current Business 70: 20-30.Carson, C. S., and Jaszi, G. 1982. "Comments," Survey of Current Business 62: 57-9.CEA. See Council of Economic Advisers.Chernomas, R. 1991. "Is Unproductive Labor a (Missing) Link in the Mainstream Eco-

nomic Analysis of Growth Stagnation1/" Unpublished manuscript, Department of Eco-nomics, University of Manitoba, Winnipeg.

Coontz, S. 1965. Productive Labor and Effective Demand. London: Routledge and KeganPaul.

361

References 362

Corey, L. 1934. The Decline of American Capitalism. Salem, NH: Ayer (reprinted in 1972).Council of Economic Advisers (CEA). Various years. Economic Report of the President.

Washington, DC: Government Printing Office.Cuneo, C. J. 1978. "Class Exploitation in Canada," Canadian Review of Sociology and

Anthropology 15: 284-300.1982. "Class Struggle and Measurement of the Rate of Surplus Value," Canadian Review

of Sociology and Anthropology 19: 377-424.Denison, E. F. 1982. "Integrated Economic Accounts for the United States, 1947-1980:

Comment," Survey of Current Business 62: 59-65.Eaton, J. 1966. Political Economy: A Marxist Textbook. New York: International.Eisner, R. 1985. "The Total Incomes System of Accounts," Survey of Current Business 65:

24-48.1988. "Extended Accounts for National Income and Product," Journal of Economic

Literature 26:1611-84.Emerson, R. J., and Rowe, P. N. 1982. "Professor Cuneo's Analysis of Class Exploitation

in Canada," Canadian Review of Sociology and Anthropology 19: 279-88.Erdos, T. 1970. "Surplus Value and Its Rate in Contemporary Capitalism," Ada Oeconom-

ica 5: 371-88.Evans, W. D., and Hoffenberg, M. 1952. "Interindustry Relations Study for 1947," Review

of Economics and Statistics 34: 97-142.Farnham, A. 1989. "What Milken Means," Fortune (24 April), pp. 16-17.Foley, D. 1982. "The Value of Money, the Value of Labor Power, and the Marxian Trans-

formation Problem," Review of Radical Political Economics 14: 37-46.Foss, M. F. 1984. Changing Utilization of Fixed Capital: An Element in Long Term Growth.

Washington, DC: American Enterprise Institute for Public Policy Research.Gillman, J. 1958. The Falling Rate of Profit, Marx's Law and Its Significance to Twentieth

Century Capitalism. New York: Cameron Associates.Glyn, A., and Sutcliffe, R. 1972. British Capitalism, Workers and the Profits Squeeze.

Harmondsworth: Penguin.Goldsmith, R. W. 1968. "National Wealth," in International Encyclopedia of the Social

Sciences. New York: Macmillan.Goodwin, R. M. 1967. "A Growth Cycle," in C. H. Feinstein (ed.), Socialism, Capitalism

and Economic Growth. London: Cambridge University Press.Gough, I. 1972. "Productive and Unproductive Labour in Marx," New Left Review 12:

47-72.Gouverneur, J. 1983. Contemporary Capitalism and Marxist Economics. Oxford: M. Rob-

ertson.Harrod, R. F. 1939. "An Essay in Dynamic Theory," Economic Journal 49:14-33.Hicks, U. 1946. "The Terminology of Tax Analysis," Economic Journal 56: 38-50.HUD. See U.S. Department of Housing and Urban Development.Hunt, E. K. 1979. "The Categories of Productive and Unproductive Labour in Marxist

Economic Theory," Science and Society 43: 303-25.Izumi, H. No date. "A Survey of Estimations of the Rate of Surplus Value in Japan," un-

published manuscript.1980. (trans.) "Estimation of Surplus Value Using Labor Values," Keizai 193.1983. (trans.) "International Comparisons of the Rate of Surplus Value Using Labor

Values," Keizai 227.Jorgenson, D. W., and Fraumeni, B. M. 1987. "The Accumulation of Human and Non-

Human Capital, 1948-1984," unpublished manuscript, Department of Economics, Har-vard University, Cambridge, MA.

References 363

Juillard, M. 1988. "Un Schema de Reproduction pour l'Economie des Etats-Unis: 1948-1980. Tentative de Modelisation et de Quantification," Ph.D. dissertation, Universitede Geneve, Geneve.

1992. "The Regime of Intensive Accumulation of the Post-War: The Case of France andthe U.S.," in D. Papadimitriou (ed.), Profits, Deficits and Instability. New York: St.Martin's.

Kahn, H. C. 1968. Employee Compensation Under the Income Tax. New York: NationalBureau of Economic Research.

Kalmans, R. 1992. "The Political Economy of Exploitation: A Comparative Study of theRate of Surplus Value in Japan and the United States, 1958-1980," Ph.D. dissertation,Department of Economics, New School for Social Research, New York.

Kendrick, J. W. 1968. "A Brief History of National Income Accounts," in D. Sills (ed.), TheInternational Encyclopedia of the Social Sciences, vol. II. New York: Crowell, Collierand MacMillan, pp. 19-33.

Kendrick, J. W. 1970. "The Historical Development of National Income Accounts," Historyof Political Economy 11: 284-315.

Khanjian, A. 1989. "Measuring and Comparing the Price and Value Rates of Surplus Valuein the U.S., 1958-1977," Ph.D. dissertation, Department of Economics, New Schoolfor Social Research, New York.

Labor Research Association. 1948. Trends in American Capitalism: Profit and Living Stan-dards. New York: International.

Lancaster, K. J. 1968. Mathematical Economics. London: Macmillan.Leontief, W. 1951. The Structure of the American Economy: 1919-1939. New York: Oxford

University Press.Lipietz, A. 1982. "The So-Called 'Transformation Problem' Revisited," Journal of Eco-

nomic Theory 26: 59-88.Lippit, V. 1985. "The Concept of the Surplus in Economic Development," Review of Radi-

cal Political Economics 17: 1-19.Mage, S. H. 1963. "The Law of the Falling Tendency of the Rate of Profit: Its Place in the

Marxian Theoretical System and Relevance to the United States," Ph.D. dissertation,Department of Economics, Columbia University, New York.

Mandel, E. 1975. Late Capitalism. London: New Left Books.1976. "Introduction," in K. Marx, Capital, vol. 1, New York: Vintage.1981. "Introduction," in K. Marx, Capital, vol. 2. New York: Vintage.

Marx, K. 1963. Theories of Surplus-Value, Part I. Moscow: Progress Publishers.1967a. Capital, vol. 1. New York: International.1967b. Capital, vol. 3. New York: International.1977. Capital, vol. 1 (trans. B. Fowkes). New York: Vintage.

Miller, J. 1989. "Social Wage or Social Profit," Review of Radical Political Economics 21:82-90.

Morishima, M. 1973. Marx's Economics. Cambridge: Cambridge University Press.Moseley, F. B. 1982. "The Rate of Surplus-Value in the United States: 1947-1977," Ph.D.

dissertation, University of Massachusetts, Amherst.1985. "The Rate of Surplus Value in the Postwar U.S. Economy: A Critique of Weiss-

kopf's Estimates," Cambridge Journal of Economics 9: 57-79.Naples, M. 1987. "Cyclical and Secular Productivity Slowdown," in R. Cherry et al., The

Imperiled Economy. Book I: Macroeconomics from a Left Perspective. New York:Union for Radical Political Economics.

Nordhaus, W., and Tobin, J. 1972. Economic Growth. New York: National Bureau of Eco-nomic Research.

References 364

Ochoa, E. 1984. "Labor Values and Prices of Production: An Interindustry Study of theU.S. Economy, 1947-1972," Ph.D. dissertation, Department of Economics, New Schoolfor Social Research, New York.

1988. "Values, Prices and Wage-Profit Curves in the U.S. Economy," Cambridge Journalof Economics 13: 413-30.

O'Connor, J. 1975. "Productive and Unproductive Labor," Politics and Society 5: 297-336.Okishio, N. 1959. "Measurement of the Rate of Surplus Value," Histotsubasbi University

Institute of Economic Research 10: 1-9.Okishio, N., and Nakatani, T. 1985. "A Measurement of the Rate of Surplus Value in Ja-

pan: The 1980 Case," Kobe University Economic Review 31: 1-13.Papadimitriou, D. 1988. "The Structure of the Greek Economy, 1958-1977: An Empirical

Analysis of Marxian Economics," Ph.D. dissertation, Department of Economics, NewSchool for Social Research, New York.

Perlo, V. 1974. The Unstable Economy: Booms and Recessions in the United States since1945. New York: International.

Petrovic, P. 1987. "The Deviation of Production Prices from Labor Values: Some Method-ology and Empirical Evidence," Cambridge Journal of Economics 11:197-210.

Phillips, J. D. 1966. "Appendix: Estimating the Economic Surplus," in Baran and Sweezy(1966).

Poulantzas, N. 1975. Classes in Contemporary Capitalism. London: New Left Books.Repetto, R., McGrath, W., Wells, M., Beer, C , and Rossini, F. 1989. Wasting Assets: Nat-

ural Resources in National Income Accounts. Washington, DC: World Resources In-stitute.

Reynolds, L. G., and Gregory, P. 1965. Wages, Productivity, and Industrialization in PuertoRico. Homewood, IL: Irwin.

Ricardo, D. 1951. Notes on Malthus, vol. II of P. Sraffa (ed.), The Works and Correspon-dence of David Ricardo. Cambridge: Cambridge University Press.

Ruggles, N. D. 1987. "Social Accounting," in J. Eatwell, M. Milgate, and P. Newman (eds.),The New Palgrave: A Dictionary of Economics. London: Macmillan.

Ruggles, R., and Ruggles, N. D. 1982. "Integrated Economic Accounts for the United States,1947-1980," Survey of Current Business 62: 1-53.

Sanger, D. E. 1992. "Japa'n's Premier Joins Critics of Americans' Work Habits," New YorkTimes (4 February), pp. Al, A6.

Scott, M. 1990. "Extended Accounts for National Income and Product: A Comment,"Journal of Economic Literature 28: 1172-86.

Shaikh, A. 1975. "IO Accounts and Marxian Categories," unpublished manuscript, Depart-ment of Economics, New School for Social Research, New York.

1978a. "An Introduction to the History of Crisis Theories," in U.S. Capitalism in Crisis,Union for Radical Political Economics. New York: Monthly Review Press, pp. 219-41.

1978b. "National Income Accounts and Marxian Categories," unpublished manuscript, De-partment of Economics, Graduate Faculty, New School for Social Research, New York.

1980a. "On the Laws of International Exchange," in E. J. Nell (ed.), Growth, Profits, andProperty: Essays in the Revival of Political Economy. New York: Cambridge Univer-sity Press.

1980b. "Production and Non-Production Labor: Theoretical and Empirical Implica-tions," working paper, Lehrman Institute, New York.

1984. "The Transformation from Marx to Sraffa," in E. Mandel and A. Freeman (eds.),Ricardo, Marx, Sraffa. London: Verso.

1986. "Surplus Value," in J. Eatwell, M. Milgate, and P. Newman (eds.), The New Pal-grave: A Dictionary of Economic Theory and Doctrine. London: Macmillan.

References 365

1987. "The Falling Rate of Profit and the Economic Crisis in the U.S.," in R. Cherry et al.(eds.), The Imperiled Economy, Book I. New York: Union for Radical Political Eco-nomics.

1989. "Accumulation, Finance and Effective Demand in Marx, Keynes, and Kalecki," inW. Semmler (ed.), Financial Dynamics and Business Cycles: New Perspectives. Ar-monk, NY: M. E. Sharpe.

1992a. "A Comment on 'The Value Controversy Reconsidered' by Itoh," in B. Robertsand S. Feiner (eds.), Radical Economics. Boston: Kluwer.

1992b. "The Falling Rate of Profit, and Long Waves in Accumulation: Theory and Evi-dence," in A. Kleinknecht et al. (eds.), New Findings in Long Wave Research. London:MacMillan.

Shaikh, A., and Tonak, E. A. 1987. "The Welfare State and Myth of the Social Wage," inR. Cherry et al. (eds.), The Imperiled Economy, Book I. New York: Union for RadicalPolitical Economics.

Forthcoming. "The Social Wage in the United States," in A. Shaikh and I. Bakker (eds.),The Welfare State and the Social Wage: An International Study.

Sharpe, A. 1982a. "A Survey of Empirical Marxian Economics," unpublished manuscript,Ottawa.

1982b. "The Structure of the Canadian Economy, 1961-76: A Marxian Input-OutputAnalysis," Ph.D. dissertation, Economics Department, McGill University, Montreal.

Sherman, H. J. 1986. "Changes in the Character of the U.S. Business Cycle," Review ofRadical Political Economics 18: 190-204.

Simon, N. 1965. "Personal Consumption Expenditures in the 1958 Input-Output Study,"Survey of Current Business 45: 7-20.

Stanfield, R. A. 1973. The Economic Surplus and Neo-Marxism. Lexington, MA: D. C.Heath.

Studenski, P. 1958. The Income of Nations. New York University Press.Summers, L. H., and Summers, V. P. 1989. "When Financial Markets Work too Well: A

Cautious Case for a Securities Transactions Tax," Journal of Financial Services Re-search 3: 261-86.

Thurow, L. C. 1980. The Zero Sum Society. New York: Basic Books.1992. Head to Head: The Coming Economic Battle among Japan, Europe, and Amer-

ica. New York: Morrow.Tice, H. S., and Moczar, L. J. 1986. "Foreign Transactions in the National Income and

Product Accounts: An Overview," Survey of Current Business 66: 1-18.Tonak, E. Ahmet. 1984. "A Conceptualization of State Revenues and Expenditures: U.S.,

1952-1980," Ph.D. dissertation, Department of Economics, New School for SocialResearch, New York.

1987. "The U.S. Welfare State and the Working Class: 1952-80," Review of Radical Po-litical Economics 19: 47-72.

Tsaliki, P., and Tsoulfidis, L. 1988. "Capital Accumulation and the Rate of Profit in Post-war Greek Economy," Journal of Modern Hellenism 5: 189-209.

Uchitelle, L. 1989. "A Sharp Rise of Private Guards," New York Times 14 October, pp.33, 37.

United Nations. 1991. National Accounts Statistics: Main Aggregates and Detailed Tables,1989, Part I. New York: United Nations.

U.S. Bureau of the Census. 1975. Historical Statistics of the United States: Colonial Timesto 1970. Washington, DC: Government Printing Office.

U.S. Bureau of Interindustrial Economics (BIE). 1983. BIE Capital Stock Database (mag-netic tape). Washington, DC.

References 366

U.S. Department of Commerce, Bureau of Economic Analysis (BEA). 1965. "The Transac-tions Table of the 1958 Input-Output Study and Revised Direct and Total Require-ments Data," Survey of Current Business 45: 33-49.

1969. "Input-Output Structure of the U.S. Economy: 1963," Survey of Current Business49: 30-5.

1970. "Input-Output Structure of the U.S. Economy: 1947," mimeo, March.1971. "Personal Consumption Expenditures in the 1963 Input-Output Study," Survey of

Current Business 51: 34-8.1974. "The Input-Output Structure of the U.S. Economy: 1967," Survey of Current Busi-

ness 54:38-43.1976. "The National Income and Product Accounts of the U.S., 1929-1974, Statistical

Tables," Survey of Current Business 56.1979. "Dollar Value Tables for the 1972 Input-Output Study," Survey of Current Busi-

ness 59: 51-72.1980. "Definitions and Conventions of the 1972 Input-Output Study," by P. M. Ritz.

BEA Staff Paper no. 34. Washington, DC: Government Printing Office.1981. The National Income and Product Accounts of the United States, 1929-76: Statisti-

cal Tables. Washington, DC: Government Printing Office.1984. "The Input-Output Structure of the U.S. Economy, 1977," Survey of Current Busi-

ness 64: 42-84.1986. The National Income and Product Accounts for the United States, 1929-1982: Sta-

tistical Tables. Washington, DC: Government Printing Office.1987. Fixed Reproducible Tangible Wealth, 1929-85. Washington, DC: Government

Printing Office.U.S. Department of Housing and Urban Development (HUD). 1979. Statistical Yearbook.

Washington, DC: Government Printing Office.U.S. Department of Labor, Bureau of Labor Statistics (BLS). 1979. Time Series Data for

Input-Output Industries: Output, Price, and Employment, Bulletin 2018. Washington,DC: Government Printing Office.

1980. Handbook of Labor Statistics, Bulletin 2070. Washington, DC: Government Print-ing Office.

1989. Supplement to Employment, Hours, and Earnings, U.S., 1909-1984. Washington,DC: Government Printing Office.

1991a. Employment and Training Report of the President. Washington, DC: Govern-ment Printing Office.

1991b. Employment and Earnings, United States, 1909-90, Bulletin 1312-12. Washington,DC: Government Printing Office.

U.S. Internal Revenue Service, Statistics of Income (annual).Van Den Berg, A., and Smith, M. R. 1982. "On 'Class Exploitation' in Canada," Canadian

Review of Sociology and Anthropology 19: 264-78.Varga, E. 1928. The Decline of Capitalism: The Economics of the Decline of Capitalism

After Stabilization. London: Communist Party of Great Britain.1935. The Great Crisis and Its Political Consequences, 1928-34. New York: International

(reprinted by Howard Fertig, New York, 1974).1964. Politico-Economic Problems of Capitalism. Moscow: Progress Publishers.

Vance, T. N. 1970. The Permanent War Economy. Berkeley: Independent Socialist Press.Varley, D. 1938. "On the Computation of the Rate of Surplus Value," Science and Society

2: 393-6.Weisskopf, T. 1979. "Marxian Crisis Theory and the Rate of Profit in the Postwar U.S.,"

Cambridge Journal of Economics 3: 341-78.

References 367

1984. "An Estimation of Federal Income Taxes Paid by Labor," private correspondencewith E. A. Tonak, 13 February.

Wolff, E. N. 1975. "The Rate of Surplus Value in Puerto Rico," Journal of Political Econ-omy 83: 935-49.

1977a. "Capitalist Development, Surplus Value and Reproduction: An Empirical Exami-nation of Puerto Rico," in J. Schwartz (ed.), The Subtle Anatomy of Capitalism. SantaMonica, CA: Goodyear.

1977b. "Unproductive Labor and the Rate of Surplus Value in the United States, 1947-67," in P. Zarembka (ed.), Research in Political Economy, vol. I. Greenwich, CT: JAIPress, pp. 87-115.

1979. "The Rate of Surplus Value, the Organic Composition, and the General Rate ofProfit in the U.S. Economy, 1947-67," American Economic Review 69: 329-41.

1986. "The Productivity Slowdown and the Fall in the U.S. Rate of Profit, 1947-1976,"Review of Radical Political Economics 18: 87-109.

1987. Growth, Accumulation and Unproductive Activity; An Analysis of the PostwarU.S. Economy. New York: Cambridge University Press.

Wright, E. O. 1978. Class, Crisis and the State. London: New Left Books.Young, A. H., and Tice, H. S. 1985. "An Introduction to National Economic Accounting,"

Survey of Current Business 65: 59-76.

AUTHOR INDEX

Aglietta, M., 164,182-4,224,226-7, 346-8Amsden, A., 165-6

Baran, P. A., 20,152,153,198, 203, 208Boddy,R., 156-7,224Bowles, S., 157, 224

Corey, L., 162Crotty,J., 156-7,224Cuneo,C.J.,161n,165

Denison,E. F.,9

Eaton, J., 173-4,184,226Eisner, R., 9-12,14-15,16,17Emerson, R. J., 16Erdos,T., 206-8,228Evans, W.D., 242

Fraumeni,B.M.,10,12,14-16Freeman, R., 5

Gillman, J., 162-3,166-7,173,175Glyn, A., 155-6,180,224Gordon, D. M., 157Gouverneur, J., 184

Harrod, R. F., 213nHicks, U., 65,140Hoffenberg,M.,242Hook, M.W., 268Hunt,E.K.,30n

Izumi, H., 152,166n, 192,194-7,227

Jorgenson, D. W., 10,12,14-16Juillard, M., 233,234-43, 347-8

Kalecki,M.,211Kalmans, R., 197Kendrick,J.W.,12,14,16Keynes,J.M.,4,211Khanjian, A., 82, 84, 86,143-4,154,160,

196,197-8, 201-2, 223, 224, 227Kuznets, S., 10,11

Lancaster, K. J., 3, 32, 210Leontief,W.,242Lippit,V.,203

Mage, S. H., 146,174-80,181,185, 226,351-4

Malthus,T.R.,211Mandel,E., 160,162-4,165Marx, K., 20,21-37 passim, 152,157,167n,

174,175n, 179, 210-12, 213, 214, 216Morishima, M., 158Moseley,F.B., 185-6,226

Nakatani,T., 192,193,194, 227Nordhaus,W.,ll,12,14-16

Ochoa,E.,143Okishio, N., 153,157-8,192-4,195, 227

Papadimitriou, D., 189, 226Perlo,V.,162,164,165,182Phillips, J.D., 203-4,228Poulantzas, N., 21

Repetto, R., 17Ricardo, D., 211Ruggles,N.D.,9,15,16Ruggles, R., 9,15,16

369

Author index 370

Scott, M., 15Shaikh, A., 16, 82,122,137,143,165,166,

180-1,185,188, 201, 212n, 214, 226, 356-7Sharpe, A., 152,160-1,163, 225Sherman, H.J., 157, 224Smith, A., 21,165, 210Stanfield, R. A., 203, 204-6, 208,228Studenski, P.,3Summers, L. H.,4Summers, V. P., 4Sutcliffe, R., 155-6,180, 224Sweezy, P. M., 20,153,198, 203

Thurow, L., 5Tobin,J.,ll,12,14-16

Tonak, E. Ahmet, 16,137,186-7,188-9,226,356-7

Tsaliki, P., 189-90, 226Tsoulfidis,L., 189-90, 226

Van Den Berg, A., 165Vance, T. N., 163Varga, E., 161-2,165,166,168,170,171,179Varley, D., 162Von Neumann, J., 238

Weisskopf,T.,157,203,224Wolff, E. N., 86,154,158-60,192,197-202,

223-4, 225, 227

Zolotas, X., 11,12,14-16

SUBJECT INDEX

ABR (amortization of building andequipment rentals), see rentals, buildingand equipment

accumulation: actual rate of, 214-16;capital, 213-14; long-term patterns of,184

advertising, 26-7agriculture enterprises, 176,177,181alienation: see profit on alienationamortization of building and equipment

rentals: see rentals, building andequipment

annual series, 92-108

balance sheets, national, 6, 8BE A: see Bureau of Economic Analysisbenchmark tables: see Bureau of Economic

Analysis, input-output tablesbenefits, workers', 188BIE: see Bureau of Interindustrial

EconomicsBLS: see Bureau of Labor StatisticsBritain, 155-6building and equipment rentals: see rentals,

building and equipmentBureau of Economic Analysis, 9; capital

stock data, 273; capital stock series,233n; input-output tables, 91-2, 233, 234;on scrap and second-hand goodsindustry, 240

Bureau of Interindustrial Economics, 273Bureau of Labor Statistics, 108, 206, 295;

on production and nonproductionworkers, 108; on real gross domesticproduct, 336; on wages, 112-13, 304, 321

business: payments to government, 60, 62;profit-type income, 62; profits, 57-8;

rental payments, 146; and royalties,258-67; taxes, 167, 353; value added, 62;waste, 204

business sector: consumer stocks and,13-14; defined in NIPA, 185; governmentstocks and, 13-14

businesses, unincorporated, 13

capacity utilization, 122-4; classicaleconomics and, 213; defined, 190;warranted path and, 213n; Wharton-typemeasure of, 189

capital: accumulation, 213-14; business,13-14; circuits of, 56, 59; expenditures, 9;human, 13; intangible, 13; labor and, 30,31,152; organic composition of, 189;research and development as, 14; stock,13-14, 233n, 273; transfer-in of, 59; valuecomposition of, 122,150, 214; see alsoconstant capital; variable capital

capitalism: consumption under, 43, 46;demand and, 211; growth under, 229-30;labor under, 29-31, 49,129,160-1, 202;monopoly, 203; noncapitalist activitiesand, 211; production under, 184; profitunder, 184; profitability under, 229-30;surplus value under, 29-31; transactions,8; unincorporated enterprises and, 186;user values under, 34; workers' standardof living under, 216

census data, 170-2, 225circulation sector, 189citizen wage: see social wageclassical economics, 210, 211; capacity

utilization in, 213; labor in, 33, 229;production in, 3, 5,18, 25; profit in,210-11; surplus value in, 210-11

371

Subject index 372

classification, industrial, 234-7, 238closed economies, 72-3commissions, dealers', 269commodities, 47-8; bundles, 80, 85, 86,191,

196; characteristics of, 2-3, 27n, 32,210;distribution and, 23-4; governmentpurchases of, 137, 344; production and,34, 36; services and, 163; transformed bydistribution, 32; transportation and,23-4; uses of, 92

company, defined, 238comparable imports, 240,241-2compensation, employee: see employee

compensationcompensation, true, 137computers, rental of, 255-6consistent Marxian/orthodox mappings,

84-5constant capital, 42, 45,49,176,177,180,

181; flow, 97-108; intermediate inputsand, 121; labor value of, 81, 82; inMarxian/NIP A categories, 175; moneyvalue of, 81,191; variable capital and, 222

constant-commodity and -industrytechnology, 238, 239

consumer goods, 86,144consumer price index, 165consumption: distribution as, 32; growth

and, 211; in input-output tables, 92; vs.production, 25; productive workers,87-8,194, 227; social maintenance as, 32;transportation and, 23; unproductiveworkers, 87-8

consumption, capitalist, 43,46consumption, personal, 2, 22, 28, 61, 206,

229consumption, social, 28, 213,214; employ-

ment and, 18; growth and, 18,18n, 19,19n; nonproduction outcomes and, 210,211; nonproductive activities as, 2, 28;production and, 229; social savings rateand,18

consumption, total essential, 206consumption, workers', 43,46, 81-2conventional accounts: see national income

and product accountscorporate officers, salaries of, 305, 321costs: overhead, 168-9; pass-through, 255,

256, 257; socially necessary, 203, 208, 228currency units, 41cyclical fluctuations in rate of profit, 122-9,

157

data-source effect, 171defense, national, 10-11,137deficit, government, 60

Definitions and Conventions of the 1972Input-Output Study, 247

demand, final: see final demanddemand, intermediate, 42-3,46development, 166n, 195disbursements: of dividends, 59; govern-

ment, 60; royalty payments as, 54-5, 56discretionary fund, economic surplus as,

228disinvestment in inventories, 45ndistribution: of commodities, 23-4; as

consumption, 32; defined, 26; productionand, 27, 32; as social activity, 21; usevalues in, 26

dividends, 59domestically produced and realized value,

65double-balance production accounts,

6-7dummy industries in input-output tables,

75, 234, 237-8; government, 60-1, 73,220; household, 71, 73

durable goods: see goods, durable

eating and drinking places, 242-3economic boundaries, national, 65-6Economic Growth Project, 242economic surplus, 152-3, 202-9, 228-9;

political, 206, 228economies: closed, 72-3; open, 73employee compensation, 170,222, 353;

NIPA-based estimates of, 108,111-13,304, 305-22; total, 137-40,141,145,146,357

employer contributions, 111, 112employment, 233; government, 137, 344;

growth and, 211; military, 31; NIPA-based estimates of, 108,295; productive,49, 211-12, 221, 222; profit and, 211-12;ratio, 132; sales, 31; social consumptionand, 18; social reproduction and, 31;total, 222

environmental degradation, 16-17equipment: adjustment, 257-8; see also

rentals, building and equipmentestablishment, defined, 238exploitation, rate of, 161-2,182,198;

adjusted, 64; defined, 224; for productiveand unproductive workers, 86-8,129-30,224, 329-35; profit and, 155-6,157,195;skill-adjusted, Bin; surplus labor and,208; surplus value and, 129,130,199-201,206-8, 224

exploitation index, 348exports: domestic prices, 67-8,69; net, 92;

as transfers of value, 67-8

Subject index 373

extended national accounts, 9-18; Marxian,229; orthodox, 229

FAC: see force account constructionfactor incomes, 179-80fees, 52, 72fictitious rentals: see rentals, imputedfinal demand, 55, 60; comparable imports

and, 241-2; gross, 92; in Marxian/orthodox mapping, 90; royalties and,220, 221

final product, 43-4, 55; royalties and, 221;see also gross final product

final use, 92, 95-6finance charges, 52, 53, 54, 55, 72financial accounts, 7fire protection, 10-11flow-of-funds accounts, 6, 8, 9flows: input-output measures of, 42;

Marxian measures of, 42; primary,40-51; secondary, 52-63, 72

force account construction, 247-8;imputations of, 247; in input-outputtables, 233

foreign trade, 65-71, 73, 220-1

gas and oil exploration costs, 233GDP: see gross domestic productGFP: see gross final productGNP: see gross national productgoods: consumer, 86,144; consumption,

158-9; durable, 9,10,13-14; nondurable,13-14; physical, 4, 21; from productionsector, 48; services and, 2,18, 22-7, 33,40, 73, 210

government: activities, 59-63,150,176,177,181; administrative labor, 61,161, 344;commodity purchases, 137, 344; dummyindustry, 60-1, 73, 220; employment, 137;expenditures, 92,137,199, 202, 204, 344,356-7; household payments to, 60, 267;industry, 60-1, 73, 220, 234, 237; sector,72, 73, 220; stocks, 13-14; surplusproduct and, 150; surplus value and, 137,223, 344; total product purchases, 223;trading activities, 51

Greece, 189-90gross domestic product, 8, 73; defined, 66;

gross value added and, 185; nonimputedbusiness, 186; per employee hour, 336;productivity and, 131-2; royalties sectors,186; total, 336

gross final demand, 92gross final product, 15-16, 97; gross

national product and, 15, 221; inMarxian /orthodox mapping, 90;productivity and, 131-2

gross housing product, 185gross investment, 90, 92gross national product, 8, 9, 73; defined,

66; gross final product and, 15,221; grossvalue added and, 189; in NIPA 97;potential, 205-6; real, 97; total productand,221

gross output, 42, 47, 49, 50, 51, 55, 80;nonimputed rentals and, 268-70;royalties and, 53, 221

gross product, 51, 55, 75,97; in capitalistsector, 351-4; royalties and, 54, 221; totalproduct and,221

gross profit/wage ratio, 166gross surplus value, 165,168-9, 354gross trading margin, 97, 255gross value added, 170,186; gross domestic

product and, 185,186; gross nationalproduct and, 189; in input-output tables,92; in Marxian/orthodox mapping, 90,146; surplus value and, 161

ground rents, 52, 53, 54, 55, 60, 64, 72, 223growth, 19,129, 211, 222, 229-30guard labor, 10-11

Haig-Simon-Hicks income, 10,15Handbook of Labor Statistics, 322home maintenance expenditures, 253household activities, 12,12n, 15, 28nhouseholds, 12; industry, 71, 73, 234, 237;

income, 56; labor, 71; payments togovernment, 60, 267; royalties, 57-8,263-7

housing: see owner-occupied housing;rentals

illegal production, 10-12imports: comparable, 240, 241-2; non-

comparable, 234, 237, 240-1; prices,68-9; as transfers of value, 67, 68-9

imputed rentals: see rentals, imputedincome: Haig-Simon-Hicks, 10,15;

household, 56; national, 167n; ofunincorporated enterprises, 143,185-6

income, profit-type: see profit-type incomeincomes, factor, 179-80inconsistent Marxian/orthodox mappings,

85-6,86,197-9, 223-4industrial classification, 234-7,238industries, dummy: see dummy industriesindustries, transactions between, 239-40industry rates of surplus value, 195input, intermediate: see intermediate inputinput-output database, methodology,

233-52input-output tables, 6, 7, 38-40,42,190-1,

192,193; aggregation, 243-52;

Subject index 374

input-output tables (cont.)benchmark years, 89, 233, 234; buildingand equipment rentals in, 51; commod-ities in, 46-8, 92; consumption in, 92;dummy industries in, 60-1, 73, 220,234,237-8; final use in, 92; force accountconstruction in, 233; governmentactivities in, 61-3, 92; imputed rentals in,267; industrial classification in, 234-8;intermediate inputs in, 92, 278-9;interpolation of variables in, 278-9;Make tables in, 238-40; Marxianmeasures and, 42-5, 72-5; modificationsof, 234-43; money flows vs. quantityflows in, 81; NIPA data and, 92-108;owner-occupied housing in, 248; price-value deviations in, 84-5; producer pricesin, 79-80, 81,196; production in, 42-51,238; purchaser prices in, 80, 84,196; rest-of-world flows in, 278-9; royalties in,53-6, 220, 278-9; summary, 274; totalvalue in, 92; trade sector in, 45-51;trading margins and, 80,196; trans-actions between industries in, 239-40;transportation, 51; use side in, 42-3; Usetables in, 238-40; value added in, 234

interest, 52; net, 60, 72,145-6, 223, 352-3;paid by productive workers, 64

intermediate demand, 42-3,46intermediate input, 42,45,48, 49,146,222;

in annual series, 96; comparable importsand, 241; constant capital and, 121; ininput-output tables, 92,278-9; inMarxian /orthodox mapping, 90;royalties and, 54; of trading sectors,186; variable capital and, 121

intermediate productive use, 92Internal Revenue Service, 353international trade, 66-71inventory, 45n; unintended change in, 42;

valuation adjustment, 90; valuationindustry, 234,238

investment, aggregate, 10,212; durablegoods as, 10; gross, 90,92; in inventories,45n; total, 43,46

IO-NIPA/Marxian mapping: seeMarxian /orthodox mapping

IO tables: see input-output tablesIRS: see Internal Revenue Service

Japan,152-3,195

Korean War defense buildup, 137

labor: capital and, 30, 31; capitalisticallyemployed, 29-31,129; in classical

economics, 33; coefficients, 81; gov-ernment administrative, 161; growthand, 211; household, 71; in Marxianeconomics, 33; necessary, 229; net taxon, 137-41,184,187-9,198; and nonlaboractivities, 25; in orthodox economics, 33;production, 22, 24-5; share, 188, 226;social productivity of, 347; and socialrelations, 29; socially necessary, 32-3;time, 31,129, 200-1, 224; total, 109-11;wage, 30,152,160-1

labor, productive, 108,150,197, 225; andcapital, 152; under capitalism, 29-31,202; defined, 295; employment and, 221;Marx's definition of, 30; in Marxian/neoclassical economics, 202-3; in ortho-dox economics, 32-4; production sectorsand, 295; real social wage cost of, 227;socialism and, 152; surplus value and,153-4,187, 202; total wages and, 221-2;unproductive labor and, 25,151,160,163-4,180,198, 221, 225-6, 295-6

labor, unproductive: under capitalism, 202;defined, 295; in Marxian economics,202-3; necessity and, 202-3,216-20;nonproduction workers and, 295; profitand, 31; services as, 227; surplus valueand, 153-4,216; variable capital and,187-8

labor power, productive, 81-2,191,194;price-value deviations and, 144; valueof, 31, 81-2,178-9,183-4,192,193,194,346-8

Labor Research Association, 167-9,172-3,175

labor squeeze, 155-7,224-5labor value: aggregate, 157-61,190-202;

calculations, 79-86; of constant capital,81; of consumption goods, 159; magni-tudes, 141-3,191-2,223; measures, 70,80,153-4; of productive labor power,178-9,191; surplus value and, 194-5;of variable capital, 159,178

labor value added, 178labor-value/producer-price ratios, 81,191,

196,224land, rental and sale of, 51, 72, 254,269,

270leisure time, 10,14,15lottery receipts, 188LRA: see Labor Research Association

maintenance, social, 21-2,26,27, 32,189Make tables, 238-40managers, salaries of, 162manufacturing, 162,165,225

Subject index 375

marketability, 3-4, 33-4Marxian accounts: see Marxian measuresMarxian economics: labor in, 33,152,153,

229; production in, 34; profit in, 35,122-29; surplus value in, 152

Marxian measures: of flows, 42; govern-ment activities in, 59-63; notation of,38-9; price-value deviations in, 143-4;of production, 42-51; of productivity,131-2,189, 221, 222, 336; of profit, 213,214; of revenue side, 75, 77; of royalties,53-6; of trade sector, 45-51; of use side,75,77

Marxian /orthodox mapping, 42-5, 72-5,90-1,146,153,154-61,174-81, 263;consistent, 84-5,143; double-entryaccounting of, 198; inconsistent, 85-6,197-9, 223-4; surplus product and valuein, 114-21; symmetric, 197-9; valuedadded in, 50-1

materialized composition of capital, 122,124

materials used up in production, 92money rate of surplus value, 143-4,158-60,

182,193, 227money value: aggregate, 155-7,172-190;

calculations, 79- 80, 81-2; of constantcapital, 81,191; magnitudes, 191-2;measures, 153-4; sectoral, 161-2

monopoly pricing, 164moral critiques of production and

nonproduction activities, 21, 28n

national accounts: conventional, 1;extended, 9-18, 229; Marxian, 20;official, 6-8,12; production accountsand, 210; production sector in, 45-51;Soviet-style, 229; trade sector in, 45-51;types of, 7-9; United Nations systemsof, 8

national balance sheets, 6,8national defense, 10-11,137national economic boundaries, 65-6national income, 167nnational income and product accounts, 6, 7,

97; annual series from, 92-108; businesssector in, 185; census data and, 170-2;employee compensation in, 108,111-13,304, 305-22; employment in, 108,295;gross product in, 351-4; input-outputtables and, 92-108; lottery receipts in,188; manufacturing data in, 225;Marxian categories and, 153,154-61; netinterest paid in, 352-3; owner-occupiedhousing in, 188; production in, 108; profitin, 213,214; surplus value in, 150,171-2;

total product and value in, 94-5; wagesin, 108,111-12, 304; see also input-outputtables

national material product, 4,18national product, 1-2; net, 9,145-6,221natural resources, 17necessary labor time, 87,129,224necessary product, 43,46,86necessity, 20,202-3, 210,216-20; social,

32-3, 203, 208, 228neoclassical economics, 3-4,18,202-3,229net exports, 92net final product, 221, 222net interest, 60,72,145-6,223, 352-3net national product, 9,145-6,221net product, 6, 7,10-11,211net tax: see tax, netnet transfer, 63-4, 356-7net value added, 161,186new value, 208, 228NIP A: see national income and product

accountsNNP: see net national productnonagricultural sector, 189, 334noncapitalist activities, 71, 73, 211noncapitalist surplus product, 227-8noncomparable imports, 234, 237, 240-1noncorporate profits, 204nnondurable goods, 13-14nonfarm private business economy, 351nonlabor activities, 25nonproduction activities, 4-5,10-11;

consumption as, 2; government activitiesas, 60,61; labor, 211,229; mistakenconception of, 21-2; in orthodoxeconomics, 6; rate of growth and, 18,18n; "regrettables and disamenities," 12,15,17n; social consumption as, 18,28;transportation as, 23-4; workers, 295;see also production, consumption and

nonvalorized portion of workers' standardof living, 216

objective material properties, 23-4objects of possession and appropriation, 26objects of social use: see use valuesofficial accounts: see national accountsoil and gas exploration costs, 233open economies, 73oppression, and socially necessary costs,

208organic composition of capital, 189orthodox economics: labor in, 32-4;

Marxian categories and, 131-2,146,216-21; net national product in, 145-6;production in, 6,12; productivity in,

Subject index 376

orthodox economics (cont.)131-2, 336; royalties in, 261, 263; surplusvalue in, 114-21; value added in, 50-1;see also Marxian/orthodox mapping

outcomes, vs. outputs, 2,210output, gross: see gross outputoverhead costs, 168-9owner-occupied housing, 51, 267; imputed

rentals of, 185, 253-4; in input-outputtables, 24, 248; in NIPA categories, 188;as unincorporated business, 13

partners: see proprietors and partnerspass-through costs, 255, 256,257passenger transportation, 23, 24patents, 52pension plans, 111, 112personal consumption, 2,22,28, 61,206,

229personal income tax, 199physical goods, 21police, 10-11political surplus, 206, 208, 228possession and appropriation, objects of,

26potential surplus, 204price-value deviations, 178,183,184, 347;

aggregate effects of, 223; consumer goodsand, 144; empirical magnitudes of, 143-4;in input-output measures, 84-5; laborpower and, 144; Marxian measures of,143-4; money rate and, 182, 226-7; inPuerto Rico, 158; purchaser prices and,69-71,144; surplus value and, 143-4,153-4,158,160,165, 201, 223, 346;variable capital and, 144

prices: changes in, 15; consumer, 165; ofconsumption goods, 158-9; final selling,41; magnitudes, 84, 85; Sraffian, 143;wholesale, 165

prices, producer: see producer pricesprices, purchaser: see purchaser pricespricing, monopoly, 164primary flows, 40-51primary sectors, 39, 72, 220, 351producer prices, 45, 47-8; input-output

tables and, 79-80, 81,196; labor valuecalculations of, 82; relative, 69

producing sector, 171product: final, 43-4, 55,221; input-output

measures of, 42; necessary, 43,46, 86;physical, 4; transfers between sectorsand,53

product, surplus: see surplus productproduct, total: see total product

production, 72; accounts, 6-7, 210,229;aggregate profit on, 212; capitalist,29-31,184; classical, 3, 5,18; compre-hensive, 3; consumption and, 25,229;defined, 2-5, 22,40; distribution and, 27,32; household, 12; illegal, 10,12; inputinto, 11,46; input-output measures of,42-5; labor and, 22,211; leisure time as,10,14; marketability and, 33-4; Marxian,34,42-5; in Marxian /orthodox mapping,90; materials used up in, 92; mistakenconceptions of 20-1; neoclassical, 3-4,18; nonmarket, 9-10; nonproductionactivities and, 2-3, 20-8, 228-9; non-production labor and, 152,153,210;operational criterion of, in neoclassicaleconomics, 33, 202; orthodox, 6,12;persons engaged in, 108; preconditionsof, 10,11; processes, 238; restricted, 3; associal activity, 21; social maintenance as,32; as socially necessary labor, 32-3;Sraffian prices of, 143; transportation as,23; use values and, 29-31; utility basedconcept, 3n, 12n, 17n

production sector, 45-51, 57-8, 59; andproductive labor, 295; and royalties, 186;surplus value in, 164

production workers: capitalisticallyemployed, 49; nonproduction workersand, 108; wages of, 161,163, 222-3

productive activities, 193,196,197, 211-12productive consumption vector, 192-3productive employment, 49, 222productive industries, 79,194productive inputs share, 97productive labor: see labor, productive;

labor, unproductiveproductive sectors, 145,193productive workers: see workers,

productive and unproductiveproductivity: gross domestic product and,

131-2; gross final product and, 131-2; oflabor, 150; Marxian, 131-2,189,221, 222,336; net output and, 157; orthodoxmeasures of, 131-2, 336; share of realwages in, 182, 346; so-called slowdown,132, 222; social, 347; total product and,131-2; wages and, 164

profit, 45, 46, 48, 50-1, 56,122-9, 222;aggregate, 216,267; average rate of,122-9; in Britain, 155-6; business, 57-8;capital stock and, 13-14; capitalist, 184;classical, 210-11; corporate rate of,122-4,222; cyclical fluctuations in,122-9,157; exploitation rate and, 155-6,

Subject index 371

157; general rate of, 167n, 214-16;Marxian, 35,122-9,146-51,163,213,214;monetary, 58-9; money rate of, 226-7;NIPA-based estimates, 213,214; non-corporate, 204n; on production, 212;productive employment and, 211-12;profit share and, 157; royalties and, 54;surplus value and, 35-7, 58-9,114,157,166,179, 202, 210-11, 213, 214-16, 323;unproductive labor and, 31; value com-position of capital and, 214; variablecapital and, 157

profit on alienation, 35, 36-7,210-11, 216profit-type income, 42, 50, 55, 222, 353;

business, 62; government and, 62;primary and secondary sectors, 59;royalties and, 221; surplus value and,56-9,173, 216, 221

profit/wage ratio, 59,180; in Britain,155-6; and exploitation rates, 195; gross,166; in Marxian and NIPA categories,154-5; in Puerto Rico, 158; surplus valueand, 114-20,185,189, 222, 224-5

profitability, 229-30promonopoly taxation, 164properties, objective material, 23-4property-type income, 167-9, 203-4,204,

354proprietors and partners, 112n, 143; wage

equivalent of, 176n, 177,181,185,186, 201Puerto Rico, 158-60purchaser prices, 45,47-8; input-output

measures and, 80, 84,196; labor valueand, 79,223; money value calculationsand, 79-80; price-value deviations and,69-71,144

quantity flows, 81

rational allocation, 203Reagan-Bush era (1980-89), 129,151,214real estate sector, 189, 248, 253-8, 269, 273realized-value measure of balance of trade,

70regulation theory, 182-4relative wage rates, 88,131,158,159,160relative working time, 88,130-1rental sector, 176rental value, 185rentals: building and equipment, 51, 72,

90, 91, 97, 254-8, 270-3; business, 146;ground rents, 52, 53, 54, 55, 60, 64, 72,223; imputed, 253-4, 267; net rents paid,353; nonimputed, 268-70; land, 51, 72,254, 269, 270; owner-occupied, 51; astrading activities, 51, 254-6

reproduction, social: see socialreproduction

research and development, 14rest-of-world accounts, 66, 73, 96, 234,237,

278-9retail trade industry, 242,243revenue, circuits of, 56reverse adjustment, 247-8ROW: see rest-of-world accountsroyalties, 52, 53-6, 72-3; aggregate profits

and, 267; in annual series, 96; business,258-67; direct payment of, 269; finaldemand and, 220; flows, 221; govern-ment, 60,61; household, 57-8,263-7;in input-output tables, 53-6,278-9;Marxian, 53-6; in Marxian/orthodoxmapping, 90; nonimputed rentals and,268-70; orthodox, 261,263; productionsector and, 57-8, 59,186; productiveworkers and, 64; as services, 263n; totalproduct and, 54,220; trading sectorsand, 186; as transfer payments, 261n;variable capital and, 137-41

royalties sector, 220,258-67; governmentand, 62; gross domestic product of, 186;in input-output accounts, 220; real estatesector and, 189; rental sector as, 176;unproductive activities in, 199

salaries: of corporate officers, 305-21; ofmanagers, 162

savings rate, 18, 214, 216scrap and second-hand goods industry, 234,

238, 240secondary flows, 52-63, 72secondary products, 238-40secondary sectors, 39, 52, 53, 72, 220sectoral effect, 171self-employed persons, 111-12,143,198,

304-5services: commodities and, 163; distribution

and, 32; labor and, 174,210,227;production workers and, 194; asproductive activities, 21, 72,193,196;royalties as, 263n; trading, 48; asunproductive activities, 21,192,194

SIC: see Standard IndustrialClassification

skill-adjusted rates of exploitation, 131nskills, 131,158-60slowdown, productivity, 132,222social accounting, 65,140-1social activities, 21, 22social benefit expenditures, 137,141social burden rate, 213, 214

Subject index 378

social consumption: see consumption,social

social maintenance, 21-2, 26, 27, 32,189social product, 162-3social productivity of labor, 347social relations and labor, 29social reproduction, 11,21-2, 27, 28, 31,60social savings rate, 214, 216social security, 111, 112,199social wage, 64-5,141,164,182-3, 227, 346,

347, 348social welfare, 12,165-6, 357socialism, 152socially necessary costs, 203, 208, 228Soviet-style national accounts, 229Sraffian prices of production, 143Standard Industrial Classification, 234-7,

238standard of living of workers, 30-1, 216state activities, 21-2, 27; see also

governmentstocks, 13-14surplus, economic, 202-9, 228-9; political,

228surplus, government, 60surplus capital, 198surplus elements, 205-6surplus income, 167surplus labor, 184-5, 208surplus labor time, 87,129, 208,224surplus product, 43,44,46,198; allocation

of, 212; capitalist, 153, 227-8; govern-ment activities and, 150; in labor valuecalculations, 82; in Marxian/orthodoxmappings, 86,114-21; noncapitalist,227-8; surplus value and, 113-21

surplus value, 42, 44, 45-46, 50-1, 56,124,175-6,177,178,179-80,180-1,182-3,199,211-16, 346-8; adjusted rate of, 64;aggregate estimates of, 170; approxi-mation of, 144-6; balance of trade and,71; under capitalism, 29-31; classical,210-11; defined, 190; development and,166n, 195; division of, 212-14; economicsurplus and, 208-9, 228; exploitation rateof, 129,130,199-201, 206-8,224; gov-ernment absorption of, 137, 223, 344;gross rate of, 165,168-9; gross valueadded and, 161; industry rates of, 195;in Japan, 152-3,195; Labor ResearchAssociation on, 172; labor value rate of,194-5; in manufacturing sector, 225;Marxian, 152,175; in Marxian/orthodoxmappings, 86,144-51,154-5; moneyform, 226; money rate, 143-4,182,193,227; net rate of, 165; net surplus value

realized and, 166-7; net tax and, 137-41,180,186,187-8, 223; net transfers and,137, 356-7; net value added and, 161; inNIPA-based estimates, 150; politicaleconomic surplus and, 228; price-valuedeviations and, 143-4,153-4,158,160,165, 201,223, 346; prices of consumptiongoods and, 158-9; in production sectors,164; productive labor and, 153-4,187,202; profit and, 35-7,114,157,166,179,202,210-11, 213,216, 323; profit-typeincome and, 56-9,173,214,221; profit/wage ratio and, 114-20,157,160,185,189,222, 224-5; property-type income and,167-9; in Puerto Rico, 158-60; realizedvs. true rate of, 164; salaries of managersand, 162; royalties and, 221; sectoralestimates of, 170; social product and,162-3; in South Korea, 195-6,197;surplus labor time and, 129; surplusproduct and, 113-21; taxes and, 162;transfers of value and, 165-6; transfersout of wages and, 223; in United States,195; unproductive activities and, 192,193;unproductive labor and, 153-4, 200-1,202, 216; value added and, 166; valuecomposition of capital and, 214; valuerate, 143-4,159-60,160-1,182,193, 227;variable capital and, 166

symmetry in Marxian /orthodox mappings,85,191,197-9

tax, 52, 54, 55, 72,140-1, 357; analyticalincidence of, 140; paid by workers, 64,188; real wages and, 164-5; socialwelfare expenditures and, 164-5; sur-plus value and, 162; variable capitaland,163,198

tax, business, 167tax, estimated, 177tax, income, 188,199tax, indirect business, 353tax, net, 173-4, 223; on labor, 137-41,184,

187-9,198, 223, 356; surplus value and,141,180,186,187-8, 223; variable capitaland, 223; on wages, 199

tax, social security, 199tax-shifting incidence of taxes, 140taxation, promonopoly, 164taxation, state, 186,187total employment, 222total essential consumption, 206total investment, 43,46total labor, 108-11total product, 6, 7n, 43, 55, 62,97,150;

expansion of the measure of, 62; genuine

Subject index 379

uses of, 61-2; government purchases of,223; gross national product and, 221;labor value calculations of, 82; in NIPA-based estimates, 94-5, 97; as physicalproduct, 4; primary sectors, 220;productivity and, 131-2; real, 97;royalties and, 54, 220, 221; secondaryflows and, 72; secondary sectors, 53

total value, 42, 43,46, 47-50, 55, 59, 62,150,180; circulation of, 180; constantcapital flow and, 97-108; flows, 226; ininput-output tables, 92; in Marxian/NIP A categories, 175; money form of,179; NIPA-based estimates, 94-5, 97;real, 120; royalties and, 54, 221;secondary sectors, 53

total wages, 111-13,221-2trade, 51; balance of, 70, 71; denned, 40;

foreign, 65-71, 73; international, 66-71;manufacturing and, 162; in Marxian/orthodox mapping, 90; services, 48;use values in, 72

trade sector, 45-51, 66-7,171,186,197;building and equipment rentals and, 51,254-6

trading margin, 45-8, 69, 80, 86,196transfer, net, 63-4, 356-7transfer payments, 34, 261n, 222-3transfer tables, 239transfers, 53, 56-9,66-71, 72, 73,165-6,

220-1transformation problem, 179, 216transportation: activity, 65-6; commodity,

23-4; consumption and, 23; distributive,51,90-1; input-output measures of, 51;margins, 51; as nonproduction activity,23-4; objective material properties of,23-4; passenger, 23, 24; as production,23,51

unbundling, 91, 91n, 255-8unincorporated enterprises, 185-6unincorporated income, 143unincorporated sector, 177United States: Department of Commerce,

233; exploitation rate in, 88; input-output tables, 89,91-2; surplus valuein, 195

unnecessary activities, 193n, 198; see alsonecessity

unproductive activities: effects of, onprofitability and growth, 229-30;productive workers and, 194; in royaltiessector, 199; services as, 192,194; socialburden rate and, 214; surplus value and,192,193; trade sector as, 197; unnecessary

activities and, 193n, 198; see alsoproductive activities

unproductive labor: see labor,unproductive

unproductive workers: see workers,productive and unproductive

Use tables, 238-40use values, 22-3, 24-8, 40; advertising

and, 26-7; under capitalism, 34; indistribution, 26; as material things oreffects, 22-3; production and, 24-5,29-31; royalties and, 258-9; in socialmaintenance 26, 27; in trade, 72

valorized workers' standard of living,216

value, surplus: see surplus valuevalue, total: see total valuevalue, transfers of, 56-9, 65,66-71, 72,

73,165-6,171, 220-1value/price ratio, 158-9value added, 43-4, 54, 55,145-6,173,177,

347; in BE A input-output tables, 234;business, 62; defined, 145; governmentactivities and, 62; Marxian, 50-1; inMarxian/NIPA categories, 175; net, 161,186; new revenue created and, 184;orthodox, 50-1; royalties and, 221,260-1, 263-4; surplus value and, 161,166

value composition of capital, 122,124,150,214

value of labor power, 194; standard ofliving and, 30-1

value magnitudes, 84, 85value rate of surplus value, 143-4,159-60,

160-1,182,193, 227value ratio, 347value, use: see use valuesvariable capital, 42,45,49, 59,108,111-13,

177,179-80,181,184,199, 201, 222;constant capital and, 222; defined, 145,164,189,190; intermediate inputs and,121; Labor Research Association on,172-3; labor value and, 159,178; inMarxian/NIPA categories, 175; moneyform of, 191; net surplus value realizedand, 166-7; net transfers and, 137;price-value deviations and, 144; profitand, 157; royalties and, 137-41; salariesof corporate officers and, 305, 321;surplus value and, 166; taxes and, 64-5,163,198,223; unproductive labor and,187-8; wages and, 161,185, 222-3, 304-22

variables: input-output, 278-9; primary,283

Vietnam War defense buildup, 137

Subject index 380

wage bills, 108wage equivalent: of proprietors and

partners, 176n, 177,181,185,186, 201; ofself-employed persons, 198

wage labor, 30,152,160-1wage squeeze, 222wages, 42,45, 46, 48,49, 56; in BLS-based

estimates, 112-13, 304; effective, 187; inMarxian categories, 163; net tax on, 199;in NIPA-based estimates, 108,111-12,304; of productive workers, 64,112-13,131,150,161,167, 222-3, 305, 322;productivity and, 164,182, 346; rates of,88,131,159; relative, 88,131,158,159,160; social, 64-5,141,164,182-3, 227,346, 347, 348; taxes and, 164-5; total,111-13, 221-2; transfers out of, 63-4,222-3; of unproductive workers, 112-13,131,150, 305, 322; variable capital and,161,185, 222-3, 304-22

waste, business, 204

Wharton-type measure of capacityutilization, 189

wholesale price index, 165workers: agricultural, 159; benefits of, 188;

consumption of, 87-8,194, 227; effectivewage of, 187; exploitation rate of, 88;government expenditures on, 356-7; nettax on, 356; net transfer between, and thestate, 356-7; standard of living of, 216;taxes paid by, 188

workers, productive and unproductive, 64;consumption, 87- 8, 227; exploitationrate of, 86-8,129-31, 224, 329- 35;productive consumption vector of, 192-3;unproductive expenditures of, 194; wagesof, 112-13,131,150,167, 305, 322; see alsolabor, productive; labor, unproductive

workers' share, index of, 164,182working class, 21working time, relative, 88,130-1

anwar m. shaikh, e. ahmet tonak measuring the wealth of nations the political economy of national...

Documents

extended national accounts

official national accounts

production labor

productive labor

social wealth

labor valuecalculations

money value flows

cambridge cb2