~ U T T E R W O R T H ~[I~'IE 1 N E M A N N

Energy Economics, Vol. 17, No. 3, pp. 231-236, 1995 Copyright © 1995 Elsevier Science Ltd

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The impact of electric power on productivity

A study of US manufacturing 1950-84

Bernard C Beaudreau

According to the historical record, the increased use of energy in general and electric power in particular stands as one of the key factors in productivity growth. Growth accountants, however, find little support for this view, rejecting claims that the productivity slowdown can be attributed to the lower rate of growth of the energy input in US manufacturing. In this study, an attempt at reconciling the historical record with the empirical facts is made. Specifically, the commonly used factor income shares in the relevant Divisia input-growth index, are replaced by the estimated output-input elasticities. The latter attribute a consider- ably larger role to electric power than previous studies indicated. These are then used to reevaluate the sources of growth in US manufacturing. Keywords: Electr ic power ; Product ivi ty growth

It is generally agreed that the electrification of US industry contributed greatly to raising productivity and output (National Bureau of Economic Research [11], Schurr [13], Rosenberg [12], Jorgenson [8,9]). For example, as early as 1929, the Committee on Recent Economic Changes, chaired by Herbert Hoover, identified the increased use of electric power as the most significant change in US industry (Na- tional Bureau of Economic Research [11]). More recently, Nathan Rosenberg observed that 'the spreading use of electric power in the 20th century has been associated with the introduction of new techniques and new arrangements which reduce to- tal costs through their saving of labor and capital' (Rosenberg [12], p 24). He concludes that 'there has been a very wide range of labor saving innovations

The author is with the Department of Economics, Univer- sit6 Laval, Qu6bec, Canada G1K 7P4.

throughout industry which have taken an electricity-using form. As a consequence, greater use of electricity is, from an historical point of view, the other side of the coin of a labor-saving bias in the innovation process' (Rosenberg [12], p 36).

In a study of 35 industrial sectors in the United States, Dale Jorgenson found that technical change was electricity using in 23 of the 35. The decline in real electricity prices prior to 1973, he argues, prompted increased electrification via the substitu- tion of electricity for other forms of energy and through the substitution of energy for other inputs - especially labor (Jorgenson [8], p 21). Electrification, he concludes, plays a fundamental role in productiv- ity growth.

Studies of the various sources of output growth, however, paint an altogether different picture of the role of energy in general and electric power in particular in the growth process (Denison [3], Gollop

231

The impact of electric power on productivity: B C Beaudreau

and Jorgenson [4], Gullickson and Harper [5]). Nowhere is this more apparent than in the recent debate over the productivity slowdown. Time-series data show that output growth, however, measured, has fallen dramatically from the mid-1970s on. For example, Gullickson and Harper [5] report that man- ufacturing output increased at an average annual rate of 4.2% from 1949-73, but decreased to 0.6% from 1973 to 1984. A number of writers pointed to the energy crisis as a cause. After all, everything seemed to fit: energy prices, including electricity, began their upward climb in 1973 which corre- sponded to the time at which productivity growth began its downward slide.

Growth accountants, however, dismissed such hy- potheses (Denison [5]). While they concurred that the rate of growth of energy consumption had fallen dramatically, it alone could account for no more than 0.10 of the decrease in output growth (ie 4.2%) (Gullickson and Harper [5]). Central to their argu- ment is the weight attributed to energy in deriving measures of total factor productivity, notably 0.02-0.04. Put differently, the share of energy in total factor income is largely insignificant. The en- ergy crisis, they surmise, could not explain the pro- ductivity slowdown.

This leaves us in a conundrum. The bulk of the historical evidence points to energy in general, and electric power in particular, as an important cause of productivity and output growth, yet, on the other hand, most, if not all, studies of the sources of growth find energy to be marginally important. Thus, either the historical record is incorrect, or previous studies have underestimated the role of energy in general and electric power in particular in the process of economic growth. In a recent study, His- nanick and Kymm [6] provide new evidence which suggests that part of the productivity slowdown can be attributed to the energy crisis. Specifically, they show that by disaggregating broadly defined energy into a petroleum component and a non-petroleum component, decreased energy use in US manufactur- ing has contributed to the productivity slowdown (Hisnanick and Kymm [6] ).

In this paper, the role of electric power in US economic growth is reexamined critically. Our start- ing point is the set of weights used in constructing the relevant Divisia index of factor inputs) Specifi- cally, most studies use factor shares in lieu of actual estimates of /3i, the relevant output-factor input elasticities. Implicit in this approach is the assump-

1The relevant Divisia input indices are defined as follows: ~.~= 1 flixi, where fli is the relevant factor output elasticity and x i is the relevant rate of growth of factor i.

tion that factor markets are perfectly competitive (Christensen and Jorgenson [2], Gollop and Jorgen- son [4] ). However, since the market for electric power in the USA is largely regulated, there is no reason to believe that the marginal value product of electric power would be equal to its price. This led us to estimate the various input elasticities directly using output and input data (Table 1). 2 Specifically, manufacturing value-added for the period 1950-84 was regressed against electric power consumption, employment and capital. 3 Our results show that indirect estimation techniques, by implicitly as- suming perfectly competitive factor markets, gener- ate downwardly biased estimates of the value-added electric power elasticity and upwardly biased esti- mates of the value-added employment and value-ad- ded capital elasticities.

The resulting set of estimates provided the basis for a wholesale revision of the role of electric power in output and productivity growth. First, we show that by replacing factor shares with actual values of the elasticities, the Solow residual disappears, as does the total factor productivity residual in conven- tionally defined productivity growth (Gullickson and Harper [5] ). The productivity slowdown, we find, is explained totally by the energy crisis.

The marginal product of electric power

As is customary in the growth literature, we assume the existence of a well-behaved, twice differentiable, monotonic and quasiconcave production function, such as (1), where Q is value-added, E P is electric power, L is employment and K is capital. 4 Christen- sen and Jorgenson [2] and Gollop and Jorgenson [4] have shown that the rate of growth of total factor productivity, @ = d T F P / T F P , can be defined as t f p = q - Veee p + v r k + vLl, where q = d Q / Q , ep = d E P / E P , l = d L / L , and k = d K / K , and v i = the weighted average of the ith factor share over the discrete time interval Vi = EP, L, K (Gullick- son and Harper [5] ):

Qt = f [ E P t , L t , K t ] (1)

2 Previous studies (eg Berndt and Wood [1] ) estimate the relevant elasticities indirectly using cost functions. 3Jorgenson [8] also disaggregates energy into an electric compo- nent and a non-electric component. 4 Implicitly, we assume that total manufacturing output and mate- rials are weakly separable, which is also known as the Leontief aggregation condition. This can be justified on a number of grounds. For example, by contrast with Berndt and Wood [1], our purpose here is not to predict the demand for energy, specifically, electric power. Second, manufacturing output and value-added were found to be highly correlated in the chosen sample period ( p = 0.9652).

232 Energy Economics 1995 Volume 17 Number 3

Table 1 Manufacturing output and input data 1950-84 a

The impact of electric power on productivity: B C Beaudreau

Q EP L K

1950 79.06 56.79 93.80 74.00 1951 84.25 62.74 99.26 77.28 1952 88.14 65.62 102.01 80.63 1953 97.34 74.69 108.23 83.78 1954 92.28 77.57 101.44 86.64 1955 104.95 93.73 106.05 89.48 1956 108.92 101.28 108.24 93.82 1957 107.13 101.94 107.77 97.89 1958 100.00 100.00 100.00 100.00 1959 112.33 109.81 104.15 101.67 1960 112.17 113.38 104.71 104,29 1961 110.96 114.91 101.99 106,69 1962 119.58 121.60 104.74 109,27 1963 126.59 127.31 105.24 112,09 1964 133.90 136.89 106.89 116,01 1965 144.58 142.17 111.85 122,09 1966 155.62 150.31 118.01 129,95 1967 157.39 158.44 119.90 137.24 1968 164.68 169.66 121.12 143.84 1969 167.78 181.79 124.20 150.74 1970 156.89 182.95 118.59 156.95 1971 157.40 187.13 112.99 161.97 1972 171.69 201.92 116.92 166.97 1973 185.22 218.46 122.36 173.05 1974 186.18 218.51 121.33 181.22 1975 166.83 206.75 111.35 187.56 1976 182.32 220.51 114.65 193.90 1977 195.95 227.51 120.05 200.81 1978 204.49 230.96 124.74 209.20 1979 208.94 234.58 128.10 217.79 1980 190.57 224.55 125.21 226.49 1981 186.87 225.72 122.67 234.84 1982 173.26 209.76 115.53 241.05 1983 179.66 214.18 113.16 244.95 1984 192.09 233.15 115.77 250.94

aThe output and input indices used in this study were derived as follows. The manufacturing value-added index (ie Q) was constructed using real value-added data for manufacturing, 1950-84 (US Department of Commerce [14, 15]); EP using total electric power consumption (purchased and generated), 1950-84 (US Department of Commerce [14, 15]), Fuels and Electric Energy; L using total employment data for manufacturing (US Department of Commerce [14, 15] ); and K using revised capital stock data for manufacturing reported in US Department of Commerce [16], Survey of Current Business.

Table 2 Factor income shares, US manufacturing value-added

Pe~od u N v K

Berndt and Wood [1] a 1947-71 0.6736 0.2902 Gullickson and Harper [5] 1949-83 0.7162 0.1590 Denison [3] b 1967-82 0.8263 0.1021 Kendrick and Grossman [10] 1948-73 0.6552 0.3448 US Dept of Commerce [15] 1967-81 0.4282 0.5233 c

~E

0.0360 0.1246

0.0450

aCost-based estimates of the relevant output elasticities. The values reported are net of materials (ie value-added). bEnergy and /o r electric power were not included. Clndirect taxes were netted from value-added.

The use of factor shares in lieu of the relevant elasticities is based on a number of assumptions, not the least of which is the existence of perfectly com- petitive factor markets. 5 Referring to Table 2, we see that broadly defined energy accounts for 3.0-12.0% of manufacturing value-added (ie or). Broken down into the relevant component parts,

because electric power accounts for approximately 50% of the total cost of purchased fuels and electric- ity (US Department of Commerce [14, 15]), it fol- lows that its share of total manufacturing value

5Among the others is a linear homogeneous production function (ie constant returns to scale).

Energy Economics 1995 Volume 17 Number 3 233

The impact o f electric power on productivity: B C Beaudreau

Table 3 KLEP regression results, 1950-84 a

Independent variables (1) (2)

Electric power (EP) 0.533046 0.658879 (10.791) (34.728)

Employment (L) 0.418822 (19.750)

Capital (K) 0.064250 (1.132)

Constant 5.294295 (17.595)

R 2 0.98474 0.97337 F (2, 32) 1032.52 1206.03

aDependent variable: manufacturing value-added (Q) Mean of dependent variable: 140.34 Number of observations: 35

-added stands at approximately 1.5-6.0%. 6 Electric power's factor share (ie 1.5-6.0%), it therefore fol- lows, should reflect its contribution to overall manu- facturing value-added. 7 Put differently, the relevant output elasticity for electric power should lie some- where between 0.015 and 0.06. As pointed out above, this stands in stark contrast with the bulk of the historical evidence described above.

In light of this, we decided to estimate the rele- vant elasticity directly. Specifically, data obtained from the US Department of Commerce's Annual Survey of Manufactures and Survey of Current Busi- ness, on value-added, electric power consumption, employment and capital in manufacturing from 1950 to 1984 were used to estimate the relevant Cobb-Douglas KLEP production function, given as Q = EP~1L ~Kt33. 8

The results, presented in Table 3, show a value for /31 , the value-added electric power elasticity, of 0.533043, which differs significantly from the electric power shares of 0.015-0.06 reported above. 9 That is, for the period extending from 1950 to 1984, as 1% increase in electric power consumption in manufac- turing resulted in a 0.53% increase in manufacturing value-added. 1° When electric power is included as the sole regressor, the relevant elasticity is 0.658879 (see column 2). In both cases, all coefficients have the relevant signs; however, /33, the estimated value-added capital elasticity, was found to be statis- tically insignificant at the 95% level. Clearly, electric power as a factor input in manufacturing is more

Table 4 Simple growth rates for output and inputs in US manufacturing, selected periods*

1950-84 1950-73 1974-84

Value-added 2.995 4.217 0.330 Aggregate input a 2.932 4.129 0.321 Electric power 4.455 6.226 0.591 Labor 0.784 1.375 - 0.503 Capital 3.564 3.651 3.378

a Formally the aggregate input rate consists of the following Divisia index: /3Eeep + f i l l + /3k k.

important than previously believed. Lastly, the esti- mated elasticities confirm the presence of constant returns to scale. Specifically, the three elasticities sum to 1.016 which is not statistically different from unity.

Accounting for the sources of growth in the US manufacturing 1950-84

Our findings led us to reexamine the sources of growth in US manufacturing. Clearly, judging from our estimates of/3 i V i = EP, L and K, the impor- tance accorded to electric power consumption (EP) in growth accounting, will increase, at the expense of both employment (L) and capital (K). Electric power consumption and hence growth in electric power consumption play a more important role output growth than previously thought (Gullickson and Harper [5]). Table 4 reports the relevant growth rates for manufacturing value added (Q), electric power (EP), labor (L) and capital (K), as well as the relevant Divisia index for aggregate input (Hisnanick and Kymm [6], Gullickson and Harper [5]) for three time intervals: 1950-84, 1950-73 and 1974-84.

Unlike previous studies which found a sizable gap between the actual rates of growth of output and aggregate input, our results show that growth in US manufacturing value-added is fully explained by growth in the relevant Divisia index of factor input growth. For the complete period of 1950-84, manu- facturing value-added increased at an average an- nual rate of 2.995%, while the aggregate input in- creased at 2.932%. For the first subperiod 1950-73,

6In 1967, 1974 and 1981 total energy costs in US manufacturing stood at US$7 691.7 million, US$19 468.3 million and US$55 255.1 million respectively. The corresponding costs of electric power (purchased and generated) are US$4398.11 million, US$9576.26 million and US$27609.85 million. Thus, the ratio of electric power to total energy in US manufacturing stood at 0.5717 in 1967, 0.49188 in 1974 and 0.4996 in 1981 [15]. 7Formally, vEe = 0.50v E. 8The data are presented in Table 1.

9Implicitly, we assume that fl0, the scalar is equal to unity (/3 o = 1). When/30 is included, restrictions on/3l,/32 and/33 are needed. Specifically, by imposing linear homogeneity, we obtained the following /30,/31,/32 and/33 estimates (t-statistic):/30 = 1.073 (11.639); /31 = 0.5372 (12.883); /32 = 0.3997 (23.377); and, /33 = 0.0630 (1.313). The corresponding R 2 is 0.984. 1°This result was found to be robust with regard to the sample period. Estimates for the period 1964-84 were not statistically different from those reported in Table 3.

234 Energy Economics 1995 Volume 17 Number 3

Table 5 Changes in labor productivity, total factor productivity, and the labor intensity ratios for the pre-1973 and post-1973 periods

1950-84 1950-73 1974-84

lp 2.211 2.842 0.834 tfp 0.077 0.111 0.002 vee(ep - 1) 1.956 2.585 0.583 vr (k - I) 0.178 0.146 0.249

manufacturing value-added increased at 4.217, while the aggregate input increased at 4.129%. Lastly, in the second subperiod, 1974-84, manufacturing value-added increased at an average annual rate of 0.3309, while the aggregate input increased at 0.3215.11

Chief among the causes of growth in manufactur- ing value-added is electric power consumption, in- creasing at an average annual rate of 4.455% over the entire period 1950-84. Per worker consumption of electric power in this period goes from 12534 kilowatt hours in 1950 to 41 688 kilowatt hours in 1984, a total increase of 232% (US Department of Commerce [14, 15]). Prior to the energy crisis (ie 1973), electric power consumption in manufacturing increased at an average annual rate of 6.226%; however, over the ensuing decade (1974-84), it had slowed to 0.591% per annum, bringing with it the growth rate in value-added.

E l e c t r i c p o w e r c o n s u m p t i o n a n d

p r o d u c t i v i t y

Gullickson and Harper [5] and Hisnanick and Kymm [6] evaluate the sources of productivity growth in US manufacturing using lp = q - l (see Equation (2)) as the appropriate measure of labor productivity. In this section, we report a series of revised estimates of the role of electric power and capital in labor productivity in US manufacturing. Table 5 summa- rizes our results. As was the case above, we find that the rate of growth of labor productivity is entirely explained by increasing capital and electric power intensities in US manufacturing, defined here as ep - l, the shift away from labor to electric power, and k - 1, the shift away from labor to capital:

lp = q - 1 ---= VEp[e p - 1] + v r [ k - 1] + tfp (2)

For the entire sample period (ie 1950-84), labor productivity increased at an average annual rate of

liThe corresponding values for t~, defined earlier, are 0.063 (1950-84), 0.088 (1950-73) and 0.0093 (1974-84).

The impact o f electric power on productivity: B C Beaudreau

2.211%. In this period, the electric power-labor ratio increased at an average annual rate of 3.6704%, which when multiplied by the relevant elasticity (ie 0.53304) yields a value of 1.956% which measures the effects on labor productivity of the substitution of labor for electric power referred to by Dale Jorgenson (Jorgenson [3]). In this period, the capi- tal-labor ratio increased at an average annual rate of 2.7801, which when multiplied by the relevant elasticity yields a value of 0.178, which measures the effects on labor productivity of the substitution of labor for capital. The sum of these two effects account for 97% of the growth in labor productivity in US manufacturing.

Prior to the energy crisis, labor productivity in- creased at an average annual rate of 2.842% of which 2.585% can be attributed to labor-electric power substitution and 0.146% can be attributed to labor-capital substitution. Together, these two ef- fects account for 96% of the overall increase in labor productivity. In the ensuing decade, labor pro- ductivity increased at an average annual rate of 0.834% of which 0.583% can be attributed to labor-electric power substitution and 0.249% can be attributed to labor-capital substitution.

C o n c l u s i o n

For years, writers have pointed to the increased use of electric power as a key factor in the growth of productivity. As such, to most observers, it seemed perfectly reasonable to assume that the productivity slowdown which began in 1973-74 was the direct result of the energy crisis. Oil prices had increased dramatically, driving up all energy prices, including the prices of electricity. Growth accountants, how- ever, dismissed such claims, arguing that while en- ergy consumption in general and electric power in particular had indeed slowed down markedly, nei- ther could explain more than 1-2% of the productiv- ity slowdown.

Our findings, however, reconcile the historical record with the empirical facts. By using direct as opposed to indirect estimates of the relevant output factor input elasticities, we were able to reconcile the historical record as described by Schurr [13], Jorgenson [8, 9], and Rosenberg [12] with the find- ings of growth accountancy. Growth in electric power consumption accounts for 79% of the growth of manufacturing value-added. This provided the nec- essary basis to reevaluate the role of energy in general and electric power in particular in the pro- ductivity slowdown. We were able to show that the decline in electric power growth accounted for the

Energy Economics 1995 Volume 17 Number 3 235

The impact of electric power on productivity: B C Beaudreau

bulk of the decline in output ano productivity growth. In fact, our results show that when energy in general and electric power in particular are attributed their rightful place in manufacturing production processes, the Solow residual disappears, as does the total factor productivity residual (ie tfp) in conventionally defined productivity growth.

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2 Christensen, L R and Jorgenson, D W 'US real product and real factor input' The Review of Income and Wealth, 1970 March

3 Denison, E F Trends in American Economic Growth 1929-1982 The Brookings Institution, Washington, DC (1985)

4 Gollop, F M and Jorgenson, D W 'US productivity growth by industry, 1948-1973' in Kendrick, J W and Vaccara, B N (eds) New Developments in Productivity Measurement and Analysis National Bureau of Economic Research, Chicago (1980).

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236 Energy Economics 1995 Vohune 17 Number 3