the informal sector and the macroeconomy: a computable general equilibrium approach for peru

Pergamon

World Development. Vol. 22, No. 9, pp. 1393-141 I, 1994

Elsevier Science Ltd Printed in Great Britain

0305-750x(94)00053-0

The Informal Sector and the Macroeconomy: A Computable General Equilibrium Approach

for Peru

BRUCE KELLEY * Florida International University, Miami

Summary.- This paper examines the macroeconomic implications of the informal sector in Peru through the use of a structuralist, computable general equilibrium model. The lack of formal sector employment drives informal activity while formal and informal output are treated as imperfect substitutes. Simulations show that informal activity reduces the Keynesian multiplier and complicates distributional issues as the income of formal workers and informal producers can move in opposite directions. A final simulation highlights the limitations of strategies designed to promote the informal sector. Total output and income of informal producers decline following an increase in productivity in these processes.

1. INTRODUCTION

In recent years the informal sector has drawn con-

siderable attention due to a congruence of political, economic and social forces. In general the bulk of this research has focused on the microeconomic aspects of the informal sector or provided descriptive case studies of informal sector workers or firms.’ Little is known about the macroeconomics role of the informal sector such as its effect on the macro adjustment process or the impact of macro policy on these activities. One consequence of this is that programs designed to aid informal producers in the developing world are adopted without regard to their macroeconomic implications.

This paper analyzes the macroeconomic role of the informal sector through the use of a multisector, computable general equilibrium (CGE) model for Peru. The model follows the structuralist tradition formalized by Taylor (1979, 1983 and 1991). but extends these models by differentiating between formal and informal production in both the labor and product market. The advantage of the CGE methodology for this study is that it captures the structural aspects that drive informal activity as well as differ-

ences between the informal and formal sector and

heterogeneity within the informal sector. In the

model, the lack of formal sector employment is responsible for informal activity while output of the two sectors are treated as imperfect substitutes. Model simulations are then used to analyze how informal activity affects the macroeconomic and distributional impact of the heterodox policies implemented by Alan Garcia in 1985. A final simulation examines the effects of capital accumulation within

the informal sector, a common policy designed to help informal producers.

The simulations illustrate the various channels through which informal activity affects the macro economy. The first simulation shows how competition between formal and informal output reduces the Keynesian multiplier. The second simulation highlights the role of relative prices and the importance of substitution between the two sectors in the product and labor markets. Following an increase in formal sector wages, informal output rises and formal production falls. Informal activity complicates political economy issues in these simulations since the real incomes of informal producers and formal sector workers move in opposite directions. The final simulation examines the argument, popularized in Peru by de Soto (1986) and his Institute de Lihertud J

Demouacia (ILD), that free of government imposed barriers, informal producers would prosper. The macroeconomic implications of this much-touted “other path” are seen to undermine the microeconomic logic as higher informal sector productivity results in a deterioration of the terms of trade and income in this sector. Thus, while informal activity will continue to play an important role in Peru, the paper concludes that this sector should not be viewed as the key to economic growth and improved living standards for Peruvians.

Section 2 discusses the definition of the informal sector, identifies the linkages between the informal

*The author would like to thank Bill Gibson, Robert Cruz, Maria Willumsen and the anonymous referees of the journal for valuable comments on earlier drafts of this paper.

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sector and the rest of the economy and establishes the stylized facts to be incorporated into the model. In section 3 the mode1 is presented where special attention is given to the informal sector’s role. Section 4 develops the Social Accounting Matrix (SAM) with emphasis on data issues regarding the informal sector. The model is then used to simulate the economy’s response to three policy shocks: a rise in investment, formal sector wage increases and greater informal sector productivity. The goal of these simulations is to understand how the informal sector affects the macroeconomic adjustment process, and in turn how macroeconomic changes affect the informal sector. The conclusion summa- rizes these results and draws out some of the associated political implications.

2. THE INFORMAL SECTOR

One of the most striking features of the informal sector literature is the number of way in which this term has been used. Surveying the literature, Peattie (1987) suggests that the term’s ambiguity is largely responsible for its wide acceptance. Differences appear at the most basic level. the unit of analysis, where the informal sector has been defined with respect to commodities, markets, activities. enterprises, institutions and individuals. Even where the informal sector’s domain is agreed upon, competing definitions and motivations exist. These difficulties expand considerably when evaluating data issues as discussed below.

The CGE model is compatible with various con- ceptualizations of the informal sector.’ Given that CGE methodology is built around markets (both goods and factor) and production (processes) it is necessary to define the informal sector with respect to both of these dimensions. This can be done in a variety of ways following the theoretical work on this topic. For example, Peattie defines informal goods such as housing. Gibson and Kelley (1994)

differentiate between production processes based on profitability while Portes. Castells and Benton (1989) look at the informal sector in a manner paral- lel to segmented labor market theories.

In this paper the informal sector is limited to certain legal goods and services that are exchanged in markets. This condition excludes production for own consumption as well as illicit goods, such as cocaine, from the informal sector since the unique structure and motivation of these activities would significantly muddle the concept.’ In our model informal production is limited to six goods and services that arc listed, along with some relevant characteristics (See Table I).”

While the preceding discussion limits the goods produced by the informal sector, it does not provide a definition of such production. In the literature informal processes have been defined by legal status (de Soto, 1986). production technology (Carbonetto and Carazo. l986), non-normal profit rates (Gibson and Kelley, 1994) or the organization and control of production (Kelley, 1990) while empirical studies typically use firm size as a proxy for the informal sector. This paper will incorporate a number of these characteristics into the picture of the informal sector developed here.

First, informal production is organized around an individual, family or small group of friends. This means that the direct producer controls the production process and receives the net product whereas formal sector workers earn a wage. The technical aspects of production also differ between sectors with informal processes characterized as labor-intensive reflecting the scarcity of both physical and human capital. For Peru, Carbonetto and Carazo ( 1986) estimate the capital-worker ratio to be $500 in the informal sector and $20,000 in the formal sector while labor productivity in the latter is twice that of the former. A third stylized fact associated with the informal sector involves its relationship with the state. De Soto (1986) is largely responsible for the current popularity of this theme. but the informal

Informal process Type of product

‘/c of output from IS

Light manufacturing Textiles Diverse services

Consruction Surface transportation Commerce

simple metalworking furniture tailored suits sweaters food preparation personal services

repair services housing taxis. buses light trucking mostly retail

40 II X 37 14 12 19 12 26

7 3 5 43 23 I 0 36 36 38

*As a percent of total output of each good in base SAM. Numbers do not sum to IOO% due to rounding. Figure\ developed by author as described in section 4.

INFORMAL SECTOR AND MACROECONOMY 1395

sector’s legal status has long been noted.’ Although his thesis of excessive government regulation as the sole cause of informal activity remains controversial, few deny that informal enterprises typically violate regulatory statutes and pay little taxes. While such behavior results in higher disposable income in the short run, it also introduces problems regarding investment, property rights and security that limit growth. Estimates concerning the income of informal producers always indicate informal producers earn less than formal workers.h Theoretical explana- tions of these differences include formal sector unionization and labor legislation (Mazumbar, 197.5) labor heterogeneity and efficiency wage arguments (Bardhan, 1988).

A final difference to discuss involves the output of the respective sectors. While formal and informal output are similar, examples of product differentia- tion and imperfect substitutability between the two sectors abound. Informal merchants sell goods in smaller quantities, offer different quality goods (fresher fruit) and occupy different locations (streets) than formal retailers.’ Another example involves goods, such as alpaca sweaters or expensive furnish- ing, where limited market size precludes efficient formal sector production, The small size and flexible nature of informal production give these producers an advantage in filling such niche markets. Repair services and customized manufacturing are concen- trated in the informal sector for this reason. In order to capture these differences in the model, the output of the two sectors are treated as imperfect substitutes and aggregated into a composite good that is exchanged in the market. Relative prices and the degree of substitution between the output of the respective sectors determine the composite good’s makeup and each sector’s output. As relative prices shift, the composition of the composite commodity changes which has important macroeconomic impacts in the simulations.

These unique characteristics of the informal sector suggest that the motivation of production, investment and savings decisions, supply elasticities and distributional issues will vary between formal and informal sector. Such differences, however, do not provide the motivation for, or a theory of, informal activity. This is found in the relationship between the informal sector and labor market. Higher wages, greater stability of income and superior working conditions make formal sector employment more desirable than informal activity. Due to rapid population growth, economic stagnation and the capital- intensive nature of formal production, however, the formal sector does not employ the entire labor force. With minimal savings and the absence of government-sponsored transfer payments, workers who cannot find formal sector employment are forced to

develop alternative income sources. While some turn to criminal or other activities, the vast majority of this surplus labor pool in developing countries enters the informal sector. “Full employment” exists, but this is achieved through changes in the level of informal activity rather than by adjustments in the formal labor market.

3. THE MODEL

This section describes the CGE model and how it reflects the major structural characteristics of the Peruvian economy and the stylized facts of the informal sector discussed above. Before exploring the model it is helpful to discuss the CGE methodology and its suitability for analyzing this issue. CGE models are essentially complicated versions of the circu- lar flow diagram taught in introductory economics where the system of equations maps the flow of goods, services and factors of production between the various economic agents in the economy for a given time period. Markets clear ex-post since actual supply and demand must be equal, but this identity can be fulfilled by changes in output, price or some other variable where the specific adjustment mechanism reflects the characteristics of the respective market as well as macroeconomic conditions. Along with these sectoral balances, the budget constraints for the respective economic agents as well as macroeconomic identities, such as the savings-investment balance, form the core of the CGE model.

In addition to the internal consistency requirements, there are several other advantages of the CGE methodology for our study of the informal sector. First, the model captures both the microeconomic reaction of individuals to, and the macroeconomic impact of, an exogenous shock. For example, a change in relative prices causes migration within the informal sector, altering the level and composition of output, which affects other variables such as income distribution. The CGE methodology also allows significant sectoral disaggregation which is necessary to capture the technological and structural differences that exist across industries in a developing economy such as Peru. Sectoral disaggregation is particularly important in this study since it allows the model to capture differences within the informal sector, a critical feature of these activities. The drawback of such disaggregation is that it makes the model too complicated to solve analytically so empirical simulations are required. The CGE methodology also forces the modeler to be explicit about market structure and the connection between the empirical model and economic theory. Not only does this demystify the underlying economic assumptions, it also makes the transmission mechanism and the connections

I396 WORLD DEVELOPMENT

between the endogenous variables more transparent. Finally, and most relevant for this study, the CGE model has distinct advantages regarding data requirements. Instead of requiring a long time series as in an econometric study, the CGE model only needs data for one point in time which are incorporated into a consistent macroeconomic framework according to explicit assumptions concerning the informal sector, parameter values and economic theory. While the data requirements are still daunt- ing. the alternative of an extended time series does not exist making econometric analysis impossible.

With this understanding of CGE methodology. we can turn to the actual model. To save space, the actual equations are given in Appendix A. The model has IX domestic goods, six of which are composite goods made up of formal and informal output, and one noncompetitive imported good. There are five economic actors: three domestic classes (formal sector workers, capitalists and informal producers) plus the government and foreigners. Total capital stock and its distribution across industries is fixed. Labor is assumed to move costlessly across processes and between the formal and informal sector.

In the goods market sectoral balance is given by the equality of supply and demand where supply is determined according to structural characteristics. For each good or service except commerce, total demand is made up of intermediate, consumption, investment, government and export demand. Intermediate demand is given by the Leontieff technology while consumption is linear in expenditure.” Both investment and government demand are given in real terms while export demand depends upon the type of good as described above.

Commerce. good IS, is treated differently since demand for this service is a derived demand based on commercial margins associated with the purchase of other goods4 Commercial margins are fixed in physical units and given in the National Accounts for each good and type of demand. The commercial markup is determined by the physical margin multi- plied by the price of commercial services where the difference between producer and retail price goes to merchants for their services. If H,, represents the physical margin on good i when purchased by process ,;. H,, the physical margin on good i when purchased by final demand type/’ and D,, the final demand of good by demand type,/: total demand for commercial services is given by:

xi, = ; ; a&X,+ ;j ;: O,,Di, ,=I ,=I ,=I ,=I

The government collects income and sales tax from the formal sector while their expenditures are

fixed exogenously. The government is also rcsponsi- hle for two production processes (public infrastruc- ture and government services) where the difference between revenue and cost is the profit (or loss) of parastatal enterprises. I0 The fiscal deficit is considered to be nonbinding and determined endogenously.

in the external sector. resource-based goods (agriculture, minerals and petroleum) account for 75% of export earnings reflecting Peru’s reliance on traditional exports. Structural constraints determine this supply in the short run and price is given by the world market following the small country assumption. Exports adjust to clear these markets. The remaining 25% of exports come from nonresource- based production. Since exports are a relatively small portion of demand for these goods, they can be fixed in real terms. All imports are considered to be noncompetitive and treated as a separate good. The external account is balanced by changes in foreign savings.”

Labor is considered to be homogeneous which avoids differences retlecting skill, gender and spatial factors. Due to excess capacity in the formal sector. labor-output coefficients in this sector are taken as constant. Labor productivity is also assumed to be constant in the informal sector since these processes use so little capital that the marginal product of labor will not change significantly as workers enter or leave these processes. In informal processes that require a significant amount of capital, workers typically use personal or household assets. For example, drivers frequently use their own personal vehicles to provide informal transportation services. In this sense entry into this process is restricted to individuals who own their own car which means capital- labor ratios. and thus productivity. will not change significantly as the number of workers in these processes change.”

Despite the common assumption concerning labor productivity, issues concerning income distribution differ between the two sectors. In the simulations the formal sector wage is fixed by institutional factors while the imputed wage of informal producers is the net product which is determined endogenously as the difference between price and intermediate costs. Based on Peruvian data, formal sector employment is more remunerative than informal activity in the base SAM.” This difference. considered the formal sector wage premium, varies across processes and changes during the simulations as relative prices and income within the informal sector shift. Changing relative income within the informal sector induces informal producers to switch processes which alters the composition of informal output as well as the distribution of income between formal and informal scctorx.

As discussed ahove. formal and informal output


are treated as imperfect substitutes and combined into a composite good using an Armington function (Armington, 1969). This technique is frequently used in CGE models to account for differences between domestic and imported goods (Dervis et al., 1982, p. 224). The strength of such an approach is that it allows relative prices and the elasticity of substitution between formal and informal sector output to determine the composition of the composite good. If P’, represents the informal-formal price ratio for good i and o, the elasticity of substitution between formal and informal output of this good, the portion of informal output in the ith commodity, $,, can be expressed as:

4, = f (P, ‘9 0;) (&ml? < 0

As P’, (the relative price of informal output) increases, formal output replaces informal production in the composite commodity where the magnitude of this change depends upon the elasticity of substitution between formal and informal output. As output becomes more homogeneous (u, increases), a given change in relative prices will have a larger effect on the composition of the composite commodity. In the extreme case where u, = CC the goods are homogeneous and therefore prices must be equal. Given the limited data for the informal sector, values for this parameter cannot be obtained from the literature. Instead simulations will be run using several values for this variable in order to show how changes in this parameter alter the adjustment process and change the simulation results.‘”

The final aspect concerning the informal sector to be discussed at this point involves how workers are distributed between the respective informal processes. From our theory of the informal sector, the number of informal producers is given by the difference between total labor force and formal sector employment. Due to the disaggregated nature of the informal sector in this study, however, we need a mechanism to allocate producers to the respective informal processes. This mechanism should reflect the relative income and barriers to entry associated with each informal process. The labor allocation equation can be written as:

18 17

liy/CE- C I& = r,(P, - C k,aJJ !=I i= I

j=l9,20,...,24

where 1, is the labor-output coefficient for process j. X, the output of process j, z th: total labor force, c, (the output price of process j, rl, the cost of input i to process j and a, the input-output coefficient. The F, term is a scale term taken from the base SAM

while ~1, is a parameter which reflects barriers to entry for the respective informal process. Since the first 18 processes are formal, the term in parentheses on the left-hand side represents the total size of the informal sector labor force. The term in parenthesis on the right-hand side corresponds to the value of the net product of the informal process which deter- mines the income of the informal producer. As barr- ers to entry decline, a, increases so income differences between informal processes play a larger role in deciding where labor goes to within the informal sector. As with the a, term discussed above, no empirical estimates for this parameter exist so we will run simulations to check the model’s sensitivity to this parameter. This will also illustrate how the reaction of informal producers to a change in relative prices can alter the macro adjustment process.ls

The presence of informal activity, as well as other structural characteristics, determine how prices are formed and markets clear. For resource-based goods which face a given world price, domestic prices follow directly since export tariffs, commercial margins and the exchange rate are all fixed. With price determined in this manner and output fixed in the short run due to structural constraints, exports adjust to clear these markets. For the other formal processes, price is determined by an exogenous markup over costs which is defended by high tariff barriers and idle capacity.lh For markets limited to formal production, capacity utilization and output adjust to equate supply and demand at this price.

In other markets with both formal and informal production, market clearing is mediated by the Armington function and the makeup of the composite good. Formal sector prices are still given by a markup equation, but the price of informal output is determined endogenously in order to clear each market while maintaining full employment. For a given set of relative prices, if there is excess supply of a good produced by the informal sector, the price of this output will fall causing the informal sector’s weight in the composite commodity to increase. The price of the composite good will also fall since it is a weighed average of informal and formal sector prices. Equilibrium is reached when a price vector is found where full employment exists and all markets clear.

To understand the model’s behavior and the informal sector’s role in the adjustment process con- sider an exogenous fall in investment. For resource- based goods, the fall in domestic demand translates into greater exports since price is given by the small- country assumption and output is fixed in the short run due to structural considerations. Elsewhere formal sector firms respond to this fall in demand by cutting back production and reducing employment which translates into a larger informal sector labor

139x WORLD DEVELOPMENT

force and is allocated across the respective processes according to the labor allocation equation described above. An increase in the number of informal producers and lower demand for their output causes the price of informal goods to fall which, from the Armington function, increases the informal sector’s weight in the composite commodities. The decline in informal sector price is not uniform which causes migration within the informal sector as producers move to where relative prices have increased. Formal sector output and employment both fall. but the effect on informal sector output is ambiguous. Although the number of informal producers has increased, the sector’s output could fall if there was enough movement within the sector from high to low productivity processes.

The macro savings-investment balance now holds at the lower level of investment as all three forms of savings (private, government and foreign) fall. The government balance falls since both direct and indirect taxes depend directly on formal sector output. The trade balance improves as exports of resource- based goods increase while imported intermediate goods fall with formal production. Lower formal output is also responsible for the fall in private savings.

4. THE SOCIAL ACCOUNTING MATRIX

Before examining the simulation results, it is necessary to discuss the Social Accounting Matrix (SAM) which serves as the database for the CGE model as well as the benchmark from which the simulation results are measured. The SAM, given in Appendix B. is built from the latest Peruvian input-output tables (INE, I986a) and updated from I979 to I985 using the RAS procedure developed by Stone ( 1954) as well as additional data provided by the National Accounts (INE, l986b and 1986~) and BCR (1986). The principal challenge was to collapse the 70 processes and IO3 commodities of the National Accounts into a more workable number that reflect the major structural features of the Peruvian economy while incorporating data on the informal sector.

The SAM consists of I8 domestic goods produced by IX formal processes and six informal processes plus the noncompetitive imported good. Reading across the row of the SAM give\ the revenue received by the producer from the various sources of demand; intermediate, consumption, investment. government and export demand. This total must equal the payments made by the respective processes which are given by reading down the column. For formal sector firms total costs include intermediate cost\. noncompetitive imports, wages, profits, a depreciation term (savings by the firm), indirect taxes minus any subsi-

dies net of other taxes. Profits are determined residu- ally to balance the row and column totals. One unusual aspect of the SAM i\ that commodity flows are measured in producer prices with a separate entry for commercial services which reflects the commercial markup or the difference between producer and retail prices as explained above.

All imported goods are treated as noncompetitive with domestic production which allows them to be treated as a separate good and occupy a separate row in the SAM. Structuralist literature emphasizes the role of non competitive imports and this assumption is common in CCE models of small countries such as Peru.” Import and sales taxes occupy separate rows in the SAM and differ according to final desti- nation. Without capital flows, imports minus exports (the trade balance) equals foreign savings which is assumed to be endogenous.

There are three domestic classes or economic groups: formal sector workers in both private and stateowned enterprises. informal producers, and capitalists. Formal sector workers receive wages, pay income taxes and do not save. Informal producers receive the net product of the process they operate. and do not pay income taxes or save.ls Capitalists receive their income as a residual between the revenue and costs of privately owned firms. They pay a fixed percentage of their income in taxes. and since the model lacks a financial side. a constant savings propensity is imposed.‘” Consumption ad.justs to balance the household budget equation for each group and is allocated between 17 domestic goods and the imported good. based on household consumption surveys (INE, 1981). Several domestic commodities as well as the imported good are treated as luxuries and are only consumed by capitalists.

The government is the I’inal economic actor and receives its revenue from profits on government-run processes ( IO and I I ). indirect taxes net of subsidies. import taxes and other taxes. Government expenditure\ are distributed between domestic goods and imports where the difference between expenditures and revenue is the government deficit or surplus. Without a monetary side, the model implicitly assumes any deficit is completely monetized. The macro savings-investment balance, which must hold via Walras’s Law, can be derived so that total savings, the sum of private. government and foreign savings plus depreciation (business savings) equals the fixed level of investment.

Up to this point, the construction of the SAM has been fairly standard. This changes with the incorpo- ration of informal activity, however, as a number of assumptions must be made in order to maintain the internal consistency of the SAM and separate value- added between formal and informal sector. The first assumption excludes informal output not captured by


the National Accounts from the SAM. Although this imparts a downward bias to the size of the informal sector, it is essential in order to maintain the SAM’s internal consistency. The informal sector’s smaller size should only change the magnitude, not the direction of change, of the simulations.*” Other assumptions, built on the stylized facts of the informal sector, help divide value-added between formal and informal processes. In the model, informal processes pay no taxes, do not use imported intermediates and operate with so little capital that all depreciation is attributed to the formal sector.

While these simplifications are a starting point, more information is required in order to derive reasonable estimates for the size, income flows and production coefficients for each of the six informal processes that are consistent with the overall totals of the National Accounts. First, the labor force is sepa- rated into formal and informal sectors based on the National Accounts category of paid and unpaid employment where the latter group represents informal producers. These figures provide a reasonable size for both the total size of the informal labor force as well as the distribution between the respective processes.?’ With the informal sector limited to the six commodities described above, this rule placed more than 900,000 workers or 90% of the “unpaid,” nonagricultural labor force in the informal sector which is close to other estimates of informal activity.”

Once formal and informal sector employment are determined, their respective output can be determined from the relative labor productivities. Estimates of labor productivity, however, are spotty and subject to definitional and other problems. For example, Carbonetto and Carazo (1986) estimate productivity in the formal sector to be five times greater than the informal sector, but they define the informal sector by low productivity. Furthermore, they do not differentiate according to commodity so productivity differences could reflect differences in type of output rather than production technologies. De Soto and his ILD are another source of data on the informal sector. Although there are methodological errors in their estimates of the informal sector’s overall size (Rossini and Thomas, 1990) their figures for productivity differences between formal and informal processes for individual commodities are reasonable. Combining these estimates with the output and employment data for each commodity from the National Accounts gives the relative size of formal and informal output for each commodity. The absolute levels are then adjusted to match the total level of output. Note that this approach does not account for differences in hours worked between formal and informal enterprises as reported by Carbonetto, Hoyle and Tueros (1987) which implies

this process understates the informal sector’s actual size.

Once the size of formal and informal output is established, the value-added reported in the National Accounts must be assigned to the respective processes. This is done by incorporating certain stylized facts of the informal sector as well as several additional assumptions. From the stylized facts of the informal sector all depreciation, imported intermediates, indirect taxes and wage income can be attributed to the formal sector. Informal income, the net product of informal processes, is subtracted from total profits given in the National Accounts. Thus, the separation of value-added between formal and informal sector can be reduced to estimating informal income or net product for each of the six processes.

In this task, government data on wage and independent producer’s income are of limited use since the latter group usually includes peasants which are not part of our definition of the informal sector. In addition, most studies do not account for income dif- ferentials within the informal sector due to the commodity or service produced and the possibility that formal workers also work in the informal sector. Estimates of informal income in Peru suggest uniform methodology and definition of this sector has not been established. For example, Rizo Patron ( 198 1) has independent producers earning more than wage earners in the corresponding formal activity. Carbonetto (1985) estimates the average income in the informal sector to equal the minimum wage in the formal sector or 50% of the average formal sector wage while Carbonetto, Hoyle and Tueras (1987) put this figure at 67%. De Soto (1986) estimates informal producer’s income to be less than half of what workers make in the formal sector.

Further complicating the data issue is the requirement that figures used for the informal sector must be consistent with the overall data provided by the National Accounts while reflecting the general characteristics of the informal sector. Since data on the informal sector come from a number of sources, the actual figures used in the model had to be established via an iterative process in order to make them consistent with the National Accounts. For example, formal sector workers were initially assumed to earn twice as much as informal sector producers, and this income was subtracted from the profits recorded in the National Accounts. With all depreciation, sales tax and imported intermediates attributed to the formal sector, intermediate consumption is given as the residual between total output and value-added in the informal sector. This meant, however, that several informal processes used more domestic intermediates per unit of output than their formal counterparts, something that is strongly at odds with the literature


on the informal sector. In order to solve this problem. estimates of the productivity differences between the two processes were increased in order to reduce the absolute size of the informal sector. The income of informal producers relative to the formal workers in the corresponding process was also increased in order to increase value-added of the informal sector. Since intermediate demand is the difference between total output and value-added. both of these changes help to reduce intermediate demand by informal processes.

The final figures concerning the relative income and productivity figures for the informal sector are given in Table 2. Several figures merit special attention. First. the difference in productivity between the formal and informal process responsible for the service “commerce” is much greater than the differences for other processes. This reflects the lack of capital and seasonal nature of many r~nhularztes who swell Lima’s sidewalks, but generate very few sales. The difference in productivity is also consistent with the absence of barriers to entry to this process. Note, however. that despite much lower productivity the income of informal merchants equals 908 of formal sector wages in commerce: the same ratio as most other informal processes. This assumption can be defended in several ways. First, the nature of commerce demands relatively few skills so formal sector employers are not likely to offer a large wage premium to attract workers. Furthermore. the nature of informal commercial activity forces informal merchants to work very long hours which lowers the income differential. Finally. informal merchants also deal in wholesale trade and to the extent they receive a return on the capital used in this process, such as a vehicle. they might even earn more than formal workers.

The possibility that informal producers receive a return for the capital used in these processes also explains why informal producers of transportation services earn more than workers in the comparable formal process. The nature of this process requires a

relatively large amount of capital so when the return on capital is added to labor income, informal producers earn more than their formal sector counterparts.” Again the ability to differentiate between informal processes and incorporate stylized facts that reflect the heterogeneity of the informal sector is a clear advantage of the CGE methodology.

These revised estimates produce figures for the informal sector’s relative size and usage of intermediate goods that are more consistent with the National Accounts. Once the total intermediate cost for formal and informal process is determined as explained above, the actual composition of intermediate usage must be specified. Again, data on the input-output structure of informal enterprises are nonexistent which limits this disaggregation. Formal and informal processes producing the same good were assumed to have the same relative input-output structure so if a formal process used twice as many intermediate goods per unit of output as its informal counterpart, then each of its input-output coefficients would be double that of the informal sector. These coefficients were then adjusted slightly where casual empiricism suggested that the relative intensity of intermediate demand for certain products should differ between the two processes.

The process described above produced a balanced SAM for Peru for 1979, the base year for the input- output table. The SAM was updated to 1985. the year for this study. using more recent aggregate data while the RAS procedure was used to update the input-output coefficients.” Formal sector labor coefficients are assumed to be constant during this period, but several changes are likely to have occurred in the informal sector due to Peru’s economic problems. Although data do not exist, such changes include an increase in the relative size of the informal sector and a corresponding decrease in the relative income of these activities due to the large number of new informal sector producers. As a result. slight adjustments where made in these figures for 19X5.

5. THE SIMULATIONS

The simulation results obtained using the CGE model developed above are discussed in this section. During the period covered in these simulations the Garcia government followed a heterodox economic program built around expansionary fiscal and monetary policy, explicit income redistribution and direct price controls. The initial results of this package were encouraging, output increased by 8.5% and inflation was cut in half during Garcia’s first year in office. An alliance appeared to be developing between the government and the private sector


which seemed to have potential regarding medium- term growth. Unfortunately after two years of expansion, cracks appeared in the heterodox program and when the government failed to address these imbal- ances, the recovery collapsed and Garcia barely completed his term amid hyperinflation, tumbling output and social chaos.25

The first two simulations, an increase in exogenous demand and higher nominal wages, involve aspects of the heterodox package. Although Garcia implemented these policies simultaneously, the policy simulations are done separately in order to isolate the effects of the respective shock. In these simulations heterodox policy is shown to successfully reac- tivate production, but efforts to improve income distribution are complicated by the presence of informal activity. The last simulation examines the macroeconomic effects of capital accumulation in the informal sector. The results here suggest that policies which promote the informal sector are likely to have adverse indirect effects on informal producers through the macro adjustment process.

(a) A 10% increase in exogenous demand

The first set of simulations examines the effects of a 10% increase in government and investment demand. This corresponds to the initial heterdox shock and mini-investment boom following Garcia’s

election. The two simulations differ with respect to a, the parameter which reflects the barriers to entry for the respective informal process. In simulation B the value of a was doubled for two informal processes (commercial and diverse services) to reflect the lower entry barriers for these processes.

Both simulations indicate that expansionary policy is effective which is not surprising given the model’s basic Keynesian structure. One interesting result is that both formal and informal output increased which seems to violate the full-employment constraint since formal and informal sector employment are inversely related. This apparent inconsistency can be explained by labor migration within the informal sector as producers move from low to high productivity processes as relative prices within the informal sector change.

The initial increase in demand causes formal sector firms to increase output and draw workers from the informal sector. At the same time, however, demand for informal output is rising due to the initial shock and associated multiplier. Higher demand and lower supply drive up the price of informal output which is reflected in the 7.3% and 5.3% gain in terms of trade for the informal sector in the two simulations. The increase in informal prices, however, is not uniform since initial shock and subsequent increase in demand varies across commodities. This causes informal producers to move to informal processes where relative prices and income have increased the most. Because this shift also reflects a

Table 3. A 10% increase in government and investment demand (o/o change from base SAM)

A* BI

Total GNP Formal sector output Informal sector output

3.0 2.9 3.1 3.3 0.2 1.1

Employment Formal sector employment Informal commerce

3.6 3.4 -1.4 0.0

Savings Government deficit as % of FS outputS Trade balance

1.0 0.9 43.2 -40.2

Prices Overall price level Real exchange rate Informal sector terms of trade

1.3 -6.0

1.3

1.0 -5.3

5.3

Distribution Formal sector wages and IS Income as a proportion of total Income 2.4 2.2 IS income as a proportion of total Income 4.8 3.6 FS wages as a proportion of total Income 0.0 0.0 Change in the imputed wage of the IS relative to the FS wage rate 22.2 19.1

*all a and cr equal to one tall o = 1, some a = 1 and other a = 2 SThis value expressed in absolute terms not percentage change


movement from low to high productivity processes, total informal sector output increases despite a decline in the number of informal producers.

Migration within the informal sector also explains the difference between the results of simulation A and B. In the latter CX, was increased for informal commerce and diverse services to reflect the relatively low entrance barriers for these processes. As a result workers who migrated to more remunerative informal processes in simulation A now enter these processes. This is reflected in the constant number of informal merchants in simulation B after falling 1.4% in simulation A. Because the processes with lower entry barriers in simulation B also have lower productivity and income, the expansionary impact of the initial shock is smaller than in simulation A. This is apparent in the 3.3% increase in formal sector employment in simulation B compared to the 3.6% increase in simulation A. The smaller gain in formal sector employment is then responsible for the larger (1.1%) increase in informal output as informal producers still move to the more productive informal processes. Finally. note that the larger increase in informal output in simulation B is responsible for the smaller gain in the terms of trade for the informal sector here. These results highlight how the microeconomic responses of informal producers, as well as macroeconomic conditions, affect the structure of informal production.

The presence of informal activity also affects issues of income distribution. In both simulations the distribution of income improves as the share of income received by formal and informal sector workers increased. In simulation A. however, this share rose by 2.4% while in simulation B it was limited to 2.2% due to the smaller gain in formal sector employment and informal sector terms of trade. Within the working class the distribution of income also improved as informal producer’s income increased relative to the formal sector wage rate by 22.2% and 19.1%. respectively.

Finally, total savings increase so that the savings investment balance holds at the higher level of investment although the various types of savings respond differently. Private savings increased since this is directly related to formal sector profits which increased with formal sector output. This increase, however, is partly offset by a larger government deficit which increased from 0. I% to I .O% of formal sector output in simulation A. This combination means the trade balance must fall. Rising demand reduces exports of resource-based goods while greater formal output requires more imported-intermediates. Combined with a 6.0% appreciation in the real exchange rate, these factors produce a 43% decrease in the trade balance.

In sum. these two simulations indicate that infor-

ma1 activity does not change the basic expansionary impact of the heterodox package. Formal output increases in response to higher aggregate demand. but informal activity reduces the multiplier since informal producers move into the formal sector. The decline in the number of informal producers alters relative prices, and thus output, within the informal sector which has important distributional effects. Informal producers who either moved to the formal sector or experienced terms of trade improvements benefit. On the other hand workers who already held formal sector jobs saw their real wages decline due to the increase in the general price level ( 1.2% and 1.0% in the two simulations). With the ruling APRA party relying upon this group for political support, such a reduction in real wages was politically un- acceptable. In fact, in order to solidify his base of support, Garcia needed to increase real wages for those already employed. The consequences of such a policy within this model are examined next.

The second set of simulations examines the effects of a 10% increase in the formal sector wage rate. Wage-led growth is a common theme in structuralist models where redistributing income toward classes with higher consumption propensities sparks increased demand and output (Taylor, 1983). With Garcia’s promises to improve Peru’s distribution of income and the influence of structuralist thought on his government, this policy found a receptive audi- ence. Simulations show, however, that when informal activity is included, this policy has the exact opposite result. Higher nominal wages lead to stagflation and a deterioration in most measures of income distribution in Table 4.

The key to these surprising results is found in the behavior of the informal sector. Higher formal wages are passed along in the form of higher prices for formal output which, from the Armington function, allows the informal sector to increase its weight in the composite commodity. While higher formal wages do cause demand and formal sector output to increase, this is exactly offset in simulation A by the reduction in output reflecting lower output due to competition from the informal sector. As u, the elasticity of substitution between formal and informal output, changes, the relative magnitude of these two forces also changes. Simulation B shows that an increase in o,, reflecting greater similarity between formal and informal sector output, increases the importance of price differences and competition between sectors causing formal sector output to decline in simulation B.

The informal sector also changes the distribu-


Table 4. A 10% increase in formal sector wages (% change from base SAM)



Savings Government deficit as % of FS outputs Trade balance

Prices Overall price level Real exchange rate Informal sector terms of trade

Distribution Formal sector wages and IS Income as a proportion of total Income IS income as a proportion of total Income FS as a proportion of total Income wages Change in the imputed wage of the IS relative to the FS wage rate

*A - all a and cr equal to 1. tB-alla= l,someu= landothero=2. $C-alla= l,someu= 1 andothera=2. §This value is expressed in absolute terms, not percentage change.

A* Bt CS

0.4 0.3 0.2 0.0 -0.1 a.1 2.3 2.6 2.5

0.2 0.1 0.0 2.4 2.9 3.0

0.8 0.8 0.6 -8.6 -6.9 -5.2

3.3 3.2 3.4 -5.5 -5.3 -5.5 -0.2 4.8 -0.8

4.3 4.2 4.2 0.3 0.0 0.0 5.1 5.2 5.2

-4.8 -5.5 -5.8

tional impact of this policy. Higher nominal wages increase formal sector workers share of output by 5.1%, but informal producers are adversely affected due to the decline in their terms of trade. In simulation A, the informal sector’s terms of trade falls by 0.3% which, combined with higher nominal wages in the formal sector, results in a 4.8% decline of the informal producer’s imputed wage relative to the formal sector wage. Thus while the popular class’s share of total income increased by 4.3%, inequality within this group also increased. These results highlight the difficulty of improving the distribution of income in the presence of a large informal sector.

Simulation B and C test the model’s sensitivity to these values as well as illustrate how these parameters affect the adjustment process. In simulation B, u was doubled to show the effect of greater similarity between formal and informal output. Not surpri- singly, the expansionary impact of higher wages was reduced as the importance of competition between formal and informal output increased. From the Armington function, a higher u results in a larger share of informal output in the composite commodity for a given increase in formal sector prices. As a result, total formal sector output fell slightly (a.1 %) while informal output rose by 2.6%. The larger increase in informal output produces a greater decline in the terms of trade in simulation B, -0.8% vusus -0.3% in simulation A. This is counter intu-

itive since partial equilibrium analysis holds that as products become more homogenous, their prices should converge. The macroeconomic consequences of the initial shock, however, outweigh this effect on output prices which once again highlights the advantage of analyzing informal activity within a macroeconomic framework.

Simulation C analyzed the model’s sensitivity to barriers to entry for the various informal processes by increasing a,for two informal processes (commerce and diverse services). A higher a, increases the importance of income differences between informal processes in the labor allocation process and thus reflects lower entry barriers. This reduces the expansionary impact of higher nominal wages since the reduction of entry barriers into processes with low productivity will increase migration into these processes. For example, the number of informal merchants rose by 3.0% in simulation C compared to 2.4% in simulation A. The larger increase in these two informal processes is also responsible for the greater decline in the real income of informal producers in simulation C since these are low-income processes. The different results highlight the reaction of informal producers to a change in economic conditions and shows the importance of differentiating between informal processes as well as between the formal and informal sector.

An examination of the macro savings-investment


A*



Savings

a.1 3.3

4.6

-0.2 -6.6

Government deficit as % of FS outputt Trade balance

Prices Overall price level Real exchange rate Informal vector terms of trade

Distribution

-0.8 I .6

0.9 I .9

-5.2

Formal sector wages and IS Income as a proportion of total Income

-0.4

IS income as a proportion of total Income FS wages as a proportion of total Income Change in the imputed wage of the IS

relative to the FS wage rate

4.0 0.4

-6.4

*A - all CI and (r equal to I. tThia value is expressed in absolute terms. not percentage change.

balance indicates other potential problems with this strategy as the government deficit and foreign savings both rise. The trade balance deteriorates as the real exchange rate appreciates and domestic demand for resource-based goods increases following the rise in nominal wages. The government deficit also increases as expenditures rise in line with domestic inflation. and tax revenue stagnates along with formal output.

This simulation clearly shows how informal activity limits the potential of wage-led growth as a short-term strategy for increasing output and improving the income distribution. Higher formal sector wages and prices allow the informal sector to increase their share of the composite good which off- sets the expansionary impact of higher wages on formal output. Formal sector employment can actually decline and while the real wage increases, other measures of income inequality do not improve. The role of the informal sector in these disappointing results suggests the need to develop programs which directly focus on this sector in order to promote growth with equity. The macroeconomic effects of one such alternative are investigated in the next section.

(c) A 10% increase in ir$>rmal sector productivig

The final simulation involves a 10% increase in

labor productivity for all informal processes in order to capture the effects of programs designed to promote capital accumulation here. Such programs have been popularized by De Soto who sees the informal sector as the only alternative or “other path” to the failed statist policies of the past. In this view once government barriers facing the informal sector arc lifted, investment will flow into these processes resulting in economic growth and greater economic welfare for these producers. This simulation examines whether capital accumulation in the informal sector, as reflected in higher labor productivity, is sufficient to fulfill such promise\. As Table 5 indicates. the macroeconomic impact of such a change is likely to undermine its microeconomic logic. In this simulation total output falls. the informal sector’s terms of trade deteriorate and income distribution worsens.

The initial response to this exogenous shock is an expansion of informal output, but without new injec- tions this causes the price of informal output to fall. From the Armington function this change in relative prices leads to an increase in the informal sector‘s share and a corresponding decrease in the formal sector’s share of the composite good. This means formal sector employment decreases which leads to a further increase in informal output as displaced workers enter this sector. A second round of change\ in relative prices and formal sector output follows. At the new equilibrium formal sector output ha\ fallen by 4.X+, but this is not spread evenly across the processes. In fact some formal processes, those that do not compete with the informal sector. experience an increase in demand due to lower output prices reflecting the savings on intermediate costs.

With the decline in formal output. the government deficit is expected to increase. Table 5 indicates. however, that the government deficit. which equaled 0. I% of formal sector output in the ba\c SAM. actually moved into a small surplus (0. I %,) in

the simulation. This is the result of lower nominal expenditures reflecting the 0.9% decline in prices which more than offset the 0.3% fall in tax revenue. One reason why tax revenue held up relatively well

despite the sharp fall in formal output is that export

taxes on resource-based goods increased since exports rose as domestic demand fell. Higher export\

along with lower intermediate imports due to the for-

mal sector contraction. are responsible for the

improved trade balance. Once again. the CGE

methodology, and the corresponding disaggregation of production across industries, allows us to see this surprising result.

The results also indicate that significant changes

occurred within the informal sector following this

exogenous shock. While total informal etnployment

and production both increased. the number of infor-


mal merchants fell by 6.6% as producers fled this process. The combination of inelastic demand for commercial services and the labor-intensive nature of production caused the price and income associated with this service to fall relative to other informal processes. As a result, informal producers left this process for other informal processes where price and income held up better.

While this movement within the informal sector toward “productive” activities and away from ter- tiary processes can be interpreted favorably, the real income of informal producers is adversely affected. Individual informal producers initially benefit from greater productivity. but the subsequent indirect effects associated with the macroeconomic adjustment process are overwhelming. The terms of trade for informal output declined by 5.2% which causes the sharp deterioration in the income distribution. The only bright spot appears to be a higher real wage in the formal sector, but even this is tainted since it reflects lower prices for informal output rather than increased productivity here or gains in the distributional struggle with owners.

This simulation highlights the macroeconomic limitations of strategies that promote capital accumulation in the informal sector. An exogenous increase in productivity causes total output to fall and reduces the real income of informal producers. Informal output does increase. but this does not increase the welfare of informal producers since price of informal output falls. Without income gains for its target group. it is unlikely that such a policy will be able to generate and sustain the necessary political support. Thus despite the rhetorical appeal of this policy, those concerned with the informal sector should look elsewhere for economic strategies to help this sector.

6. CONCLUSION

Despite the large size and economic importance of the informal sector in the developing world, relatively little is known about the macroeconomic implications of these activities. Part of this reflects inherent data limitations, but the lack of a macroeconomic approach to the question of informal activity has also been responsible. This paper addresses this issue by developing a CGE model that explicitly incorporates informal production where the lack of formal employment drives this activity and the output of the two sectors are treated as imperfect substitutes. Informal output is divided into six processes and simulations show how differences within the informal sector, as between formal and informal processes, have important macroeconomic and distributional effects.

The model’s response to various exogenous shocks depends on competition between formal and informal output, inter and intrasector labor migration as well as macroeconomic conditions. The first set of simulations showed that while the informal sector did not change the model’s basic Keyneisan charac- ter, it does affect the adjustment process and have distributional consequences. The second set of simulations examined the possibilities of wage-led growth in light of Garcia’s goal of solidifying public support through improvements in the income distribution. In contrast to standard structuralist models, the results here are disappointing as both formal output and informal sector income fall as higher formal sector wages cause informal output to replace formal sector production. Workers who maintain their formal sector employment experience higher real wages, but displaced workers and informal producers both suffer losses in real income. The last simulation points out one problem with the argument that the informal sector is the key to economic growth in the developing world. Total output and informal sector income both fell following an increase in informal sector productivity.

Several general implications of this paper bear special comment. The simulations have highlighted the role of the informal sector in the adjustment process and shown how informal activity alters the effectiveness of macro policy. By disaggregating informal production, the paper allows the informal sector to react to changes in macroeconomic conditions and relative prices within the informal sector. These latter effects are often overlooked in discus- sions of the informal sector, yet they are important in order to understand the macroeconomic impact of the informal sector. The ability to capture such effects highlights one of the principal advantages of the CGE methodology for this study. The paper has also shown how the informal sector complicates distributional issues since formal sector wages and the income of informal producers often moved in opposite directions in the simulations. Such results are important in that they highlight how informal activity compounds the difficulties associated with policies that are designed to improve the income distribution in developing countries. Thus despite the political significance attached to rising real wages and rhetoric calling for aid to the informal sector, this paper argues the macroeconomic and distributional impacts of such policies are likely to be negative for much of the population. In fact, by placing informal activity within a macroeconomic framework, the paper shows that informal producers are better served by policies which reduce informal production through formal sector growth.


NOTES

I. See for example the book by Portes et al. (I 989).

2. Dervis, de Melo and Robinson (1982) provide a detailed development of the CGE methodology.

3. It is possible to include these goods in a CGE model. Gibson and Godoy (1993) develop a CGE model of Bolivia with cocaine production while Reardon (1984) includes agricultural production for own use in a CGE of Peru.

4. It should be pointed out that small contribution by the informal sector to total output of certain goods reflects the requirement that informal output must be sold. For example, to the extent that dwellings in pueblo jovenes are constructed by residents, this output would not be counted in our definition of the informal sector. While this limits our analysis, such an assumption is necessary in order to make the data requirements reasonable.

5. Weeks (1975) also defines the informal sector by its legal status. It is interesting that while de Sota works within a neoclassical framework and Weeks a Marxian, they define the informal sector in a similar manner.

6. See Carbonetto and Carazo ( 1986) Carbonetto, Hoyle and Tueros (1987) and De Soto (1986) for various estimates of the income of informal producers.

7. It is estimated that 43% of informal vendors work without a fixed location (Carbonetto, Hoyle and Robinson, 1987, p. 340).

8. Taylor ( 1979, Appendix 6) provides a good description of the linear expenditure system.

9. See Gibson, Lusteg and Taylor (1986) for a similar treatment of commerce.

IO. This is obviously a skelatized view of public enterprises, but is sufficient given this model’s focus on the informal sector.

I I For a foreign exchange constrained model of the Peru- vian economy with informal production see Kelley (1990).

12. Carbonetto. Hoyle and Tueros (1987, p. 343) estimate that 62% of the informal sector in Lima do not use machinery and that the majority of equipment that is used in these activities is also use for domestic purposes.

13. Although measurements of informal sector income differ according to definitional and methodological issues. a reasonable estimate places IS income at 67% of formal sector income (Carbonetto, Hoyle and Tueros, 1987). Of course this does not account for differences according to industry, location or length of the working day.

14. Note that with the Armington function, all purchasers of the composite commodity buy the same combination of formal and informal output of that good. While the makeup of the composite commodity can change, it is not possible to differentiate output based on whether it goes to intermediate

or final demand. Obviously some informal output serves as intermediate goods for formal firms, but this is given by the makeup of the composite commodity rather than explicit. detailed links between the two sectors.

15. This setup is sufficiently flexible to include other important characteristics of the informal sector. For example, many women who work in the informal sector also have childcare responsibilities which makes it impossible for them to work away from the home. This could be modeled by assigning some workers to certain informal processes perma- nently or dividing the informal sector between work inside or out of the home. For these workers, the relative income of each informal process would not play a role in deciding which informal process to operate. The impact of this restric- tion on the simulation results would depend on the productivity of these processes as well as how the income of these workers was affected by the exogenous shock.

16. These are standard structuralist assumptions as developed in Taylor (1979).

17. Daly (1976) and Reardon (1984). among others, make the same assumption in their CGE models of Peru.

18. This implies that if informal processes need capital, they must borrow, through intermediaries, the savings of capitalists. In actual practice the informal sector is served by a complex and well-developed system of financial interme- diation. Without a full-fledged financial side to this model, such questions cannot be analyzed.

19. This is a common assumption in CGE models and made by Rizo-Patron and Reardon in their CGE models of Peru.

20. It should be pointed out that reliable estimates of the overall size of the informal sector in Peru vary considerably due to definition, methodology and other factors. Furthermore, reliable estimates of informal production at the sectoral level i\ even more problematic. As a result, the assumption made here is certainly defensible and provides a size of the informal sectoral that is similar to other overall estimates.

21. Note this division does not correspond perfectly with the definition of the informal sector used in this paper. For example, household help would be included in the National Accounts as paid labor. but is part of the informal sector in this paper.

22. For example Carbonetto and Carazo estimate the size of the urban, informal sector in 198 I to be I .2 million. The difference however is partly attributed to the different definition of the informal sector as well as the fact informal activity in this study is limited to six processes. Estimates by ILD place the size of the informal sector much higher, but again the different definition combined with their inconsistent estimates described by Rossini and Thomas suggest these figures are not reliable.

23. Carbonetto and Carazo (I 986, p. 138) estimate the capital stock associated with various informal processes.


24. This procedure was developed by Stone (I 954) and is explained in Taylor (198 1).

25. The two major problems were the fiscal and external

REFER

Armington, P., “A theory of demand for products distin- guished by place of production,” IMF StaffPapers, Vol. 16 (1969), pp. 159-178.

Banco Central de Reserva de1 Peru (BCR), Memoria (Lima: BCR, 1986).

Bardhan, P., “Alternative approaches to development economics” in Hollis Chenery and T.N. Srinivasan (Eds.)., The Handbook of Development Economics (Amsterdam: North Holland, 1988), pp. 39-72.

Carbonetto, D. “El sector informal urbano: Estructura y evi- dencias” in German. Alarco (Ed.), Desajios pat-a la Eronomia Peruano 1985-1990 (Lima: Centro de lnvestigacion de la Universidad de1 Pacifico, 1986), pp. 203-232.

Carbonetto, D., and M. Ines Carazo de Cabellos, Heterogencidad Tecnologica y Desarrollo Economico: El Sector Informal. (Lima: lnstituto National de Planiticacion, 1986).

Carbonetto, D., Jenny Hoyle and Mario Tueros, Lima: Sector Informal (Lima: CEDEP, 1987).

Daly, J., The Political Economy of Devaluation: The Case of Peru 1975-1978. (Boulder: Westview Press, 1983).

De Soto, H., El Otro Sendero. (Lima: lnstituto de Libertad y Democracia, 1986).

Dervis, K., J. de Melo, and S. Robinson., General Equili- brium Models for Development Policy (Cambridge: Cambridge University Press, 1982).

Dombush, R., “Peru on the Brink,” Challenge (January 1988) pp. I-IO.

Gibson, B., and R. Godoy, “Alternatives to coca production in Bolivia: A computable general equilibrium approach,” World Develrjpment, Vol. 21. No. 6 (June 1993) pp. 1007-1022.

Gibson, B., and B. Kelley, “A classical theory of the informal sector,” The Manchester School, Vol. LXII, No. 1 (March, 1994). pp. 8 l-96.

Gibson, B., N. Lustig and L. Taylor, “Terms of trade and class conflict in acomputable general equilibrium model for Mexico,” Jounral of Develotmzent Studies, Vol. 23, (1986)pp.40-59. -

lnstituto de Libertad y Democracia (ILD), “La actividad economica informal en el Peru y las estructuras legales,” fndustria Peruana, No. 6 19 (1986) pp. 1 13-I 18.

Institute National del Estadistica de1 Peru (INE), Tab/as Insumo-Product0 de la Economia Peruana Aiio 1979 (Lima: INE, 1968a).

lnstituto National del Estadistica de1 Peru (INE), Cuentos Nacionales del Peru 1950-1985 Tahlas Insumo- Productor (Lima: INE, 1986b).

lnstituto National de1 Estadistica del Peru (INE), Qferta y Demanda Global 1985 (Lima: INE, 1986~).

lnstituto National de1 Estadistica de1 Peru (INE), Analysis de1 Ingreso y Gasto Familias de la ENAPROM y

deficit which lead to the rapid depletion of international reserves. See Dombush (1988) for a description of this period.

:ENCES

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Jagannathan, N.V., Informal Markets in Developing Countries (New York: Oxford University Press, 1987).

Kelley, B.. “The informal sector and alternative closure rules in a computable general equilibrium model of the Peru- vian heterodox experience,” Ph.D. dissertation (Amherst, MA: University of Massachusetts-Amherst, 1990).

Leidholm, C., and D. Mead, “Small scale industries in developing countries: Empirical evidence and policy implications,” International Development Paper, No. 9 (East Lansing: Michigan State University, 1987).

Litan. R., L. Morales-Bayro and J. Femandez-Baca, “Internal structural reforms in Peru: A promising road out of the debt crisis,” Journal of Economic Growth, Vol. I, No. 2 (1986). pp. 28-35.

Mazumdar, D., “The urban informal sector,” Working Paper #21 I (Washington, DC: World Bank, 1975).

Peattie, L., “An idea in good currency and how it grew: The informal sector,” World Development, Vol. 15, No. 7 (1987). pp. 85 I-860.

Portes, A., M. Castells and L. Benton (Eds.), The lrzformal Economy: Studies in Advanced and Less Developed Countries (Baltimore: Johns Hopkins Press, 1989).

Reardon, T., “Agricultural price policy in Peru,” Ph. D. disssertation. (Berkley, CA: University of Califomia- Berkeley, 1984).

Rizo Patron, J., Politica Economica y Grupos de Bajos Ingresos (Lima: Centro de Investigation de la Universidad de1 Pacifico, 198 I).

Rossini, R., and J. Thomas “The size of the informal sector in Peru: A critical comment on Hemando de Soto’s El Otro Sender-o, ” World Development, Vol. 18, No. I (I 990). pp. 125-135.

Sethuraman, S.V. (Ed.), The Urban Informal Sector in Developing Countries (Geneva: ILO, I98 I).

Stone, R.A., “Linear expenditure systems and demand analysis: An application to the pattern of British demand,” Economic Journal, Vol. 64 ( 1954), pp. 5 1 l-527.

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APPENDIX A: EQUATIONS OF THE MODEL

1. Supply and demand balances for domestic goods (18 equations)

24

x b,,X,= 2 a,,X,+C,+I,+G,+E,+E, ,=I ,=I

18 24 24

~(&~,b,~,-“‘+(I -6,) x b,J,m”‘)m”p’= Z a,,X,+C,+I,+G,+X, j= 19 j=I

p(S, ‘; b,,X;“+(l -6,) ‘; b,,X,m”‘)m”“‘=

19 24

I; ( 1 g,,x,+ ;: B,,D,,) ,=I j= 19 ,=I ,=I f= I

2. Consumption demand

C,h=%+(‘h,,@,(l +p,,%,)))[(l -&)y,,- ; p,(l +f,&,)E,,-P&,1 ,=I

3. Price equations

p,=p,*e (1 -t,,)(l -P,,8,,)

P, = P,

P, = 6,P, + (1 - 6,) P,,,

4. Informal sector equations

X,lX,+, = (PJP,,,)’ [(S,Kl - 6,)l”’

1,x,/L- t r,x,,=r,(P,-‘; P,,‘aJ’J j= I ,=I

5. Full-employment constraint

6. Income equations

Y, = zf (P, - ; I;,,ll,,, x, j= 19 ,=I

Y,= C 1 ; P,b,,-(1 +T,,) ; $,a,,-yI,-P/*)X,-Z/l

I ,=I I=,

i=l,2,...,12

i = 13, 14,. ., 17

i= 18

(54 equations)

i=l.2 ,.__, 17,19

(36 equations)

j=5.6....,18

i= 1,2,3,4 f=4

i=j=l.2,...,12

i=j= 13. 14,. ., 18

( 12 equations)

i=j=l3,14,...,18

j=l9,20....,24

(1 equation)

(3 equations)

j=l,2 ,..., 9, 12. 13 ,.__, 18


(3 equations) 7. Government sector

,I 17 rP = c [ 1 P,,‘a,, + w,l, + P,*m,, x, - z,

.,=I0 !=I

21 3 17 18 3

RR = 2 t,(wl, + P,,a, + P,*m,) X, + c t, Y, + Z t, P,*E, + 1 t,*P,*m,X, + C tr*P*eDT, + II8 j=l h=l i=, j=l f= I

9 = ; G, - R, ,=I

8. External balance (1 equation)

3 IX 4

P*e(CD~+~m~,=Z,*eE,+~ gk&+S* f= I j= I i=l .f=4 i=5

Total number equations = 128, total number of variables = 127 where one of the labor allocation equations for the informal sector is redundant.

Variable Name # of Variables

X; - primary output of process j C,,, - consumption demand for good i by class h

6 - export demand for resource based good i

P, - output price for process j

p, - wholesale price of good i

K - income of class k s* - foreign savings SE - government savings R’ _ total government revenue fP - profit of government-run enterprises

Parameters

20 54

4 24 18 3 I I 1 1

a, m/ 1, - b,, - 1, - G - E, - % - hi - 8 - *,J

$ - P* - P,* -

5 - t, - t* - :, - t’h -

6, - I4 8, -

QI - 5 L -

- 2 -

e - M’ -

input of good i per unit of primary output of processj import-output coefficient for process j labor-output coefficient for process j output of good per unit of primary output of process j Investment demand for good i Government demand for good i Export demand for non-resource based good i subsistence consumption of good i by class j marginal consumption propensity for good i by class h physical commercial margin on good i per demand type physical commercial margin on good i for process j international price of imports international price for resource-based good i markup in process j indirect tax on output of processj tax on imported good used in process j export tax on good i income tax rate on class h informal sector parameter i elasticity of substitution between formal-informal output constant for Armington function coefficient for informal sector labor allocation constant for informal sector labor allocation equation total labor force average savings propensity for class h total depreciation for process j exchange rate nominal wages

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28942

the informal sector and the macroeconomy: a computable general equilibrium approach for peru

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