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Industrial energy efficiency: A look at the data
Socio-Eeon Plan. Sri., Vol. 14. pp. 251-256 Pergamon Press Ltd.. 1980. Printed in Gnar Britain
INDUSTRIAL ENERGY EFFICIENCY: A LOOK AT THE DATA NOEL D. URIt Department
of Energy, Office of Energy Use Analysis, Energy Use Technologies Division, Washington, DC 20461 U.S.A. (Receiued 18 April
1980)
Abstract-It is extremely difficult to make a precise, quantitative assessment of the impact of the myriad of factors affecting the improvement in industrial energy efficiency. It is certainly not comect to conclude that housekeeping measures alone have led to the observed improvement. Changing product mix among four digit SIC industries within the same two digit classification, variations in capacity utilization (returns to scale) and energy price increases as well as technological innovations have all contributed to part of the realized reduction in energy use per dollar value added over the period of investigation. Unfortunately, data limitations as well as modeling weaknesses prohibit an exact delineation of the impact of each of the factors on the increase in energy efficiency. The best that can be done-and quite convincingly so-is to qualitatively show that unequivocally these factors had an impact on the efficiencv with which enerev was used in the manufacturingprocess for the ten most energy intensive industries in the per&d 1971-76. -’
INTRODUCTION
Recent
years
have
seen a marked
improvement
in industrial energy efficiency. (See Leff et a!.[11 for a survey of this area.) The amount of energy needed to produce a unit of output (measured in nominal terms) has fallen precipitously in almost all industries. The extent of this improvement in the ten most energy intensive two digit SIC industries is given in Table I. The origin of this improvement is not as transparent as its existence. To be sure, a portion of the achieved reduction in energy intensity can be attributed to housekeeping measures[2]. This, however, is not the sole explanation for the observed amelioration. The distinct possibility exists that some of this efficiency improvement is illusory. That is, first, the product mix from industries within the two digit SIC categories is changing so that the output the less energy intensive industries is growing relative to the output of the less efficient and consequently while it is true efficiency is increasing this component of the increase is not attributable to conservation efforts. Second, the dramatic escalation in the price of energy has provided a considerable incentive to conserve. These effects must be netted out before any inference can be made concerning the efficacy of the argument that non-price induced conservation is responsible for the observed industrial energy efficiency improvement. Third, the level of economic activity has fluctuated over the period for which the energy efficiencies are computed. To the I extent that industries within the two digit SIC categorization are differentially impacted (that is, for example if the relatively energy inefficient four digit SIC industries are affected the most) then the reported efficiency improvement will be misleading. Given these considerations, the objective of this paper is to attempt to sort out the effects alluded to here to the degree possible with the objective of more fully under-
tThe views expressed are those of the author and do not necessarily represent the policies of the department of energy or the views of other department of energy staff members.
standing conservation over the historical period as well as using the results to evaluate the potential for future conservation of energy in the industrial sector. The data used in the analysis are from the Annual Survey of Manufacturers (ASM) collected by the Bureau of the Census. These data are the most reliable at the annual industry specific level. Other existing energy annual data series typically use the ASM as a starting point. The survey years considered include 1971 and 1974-76. Preliminary data for 1977 are available but only at the two digit SIC level. Since much of the concern is focused on a more disaggregated level, data for 1976 is the most recent used. One final comment before proceeding with the essence of the paper is needed. It concerns an objective measurement of energy efficiency. There are a myriad of potential measures each with its deficiency. (See The Conference Board(31 for a discussion.) For the purposes at hand, the value defined as Btu’s per dollar value-added is used to measure energy efficiency both between industries within the same two digit SIC category and between industries in different two digit SIC categories. The Btu’s are denominated in millions and the dollar value-added is in thousands of constant 1971dollars. The measure has the slight defect in that during periods of economic downturn the fixed cost component of the value of each unit of output will rise (as total fixed cost is spread over a few number of units of output) and consequently the value-added measure tends to understate the magnitude of fluctuations in economic activity. As a result the full effect of changes in the level of economic activity is not being removed from the efficiency measure. PRICE EFFECTS
As noted in portant effects
the foregoing discussion, one of the imon efficiency has been the impact of price. An indication of this impact can ostensibly be obtained by looking at the actual percentage change in the price of energy per Btu (in real terms) times the price elasticity of the demand for energy. (The price elasticity is defined to 251
N. D. URI
252 Table
1. Change
in industrtria!energy
efficiency”’
(ten most energy
intensive
industries”‘)
Annual Averaqe Chawe (%I
1976 Effi-
1.
Pet.rolem
am3 cixl
2.
primry mtals
products
(SIC 29)
rrdustries (SIC 33)
0.155
45.23
11.35
0.121
1.47
0.30
1.672
3.59 3.36
3.
stone, clay, Glass products (SIC 32)
0.105
4.
Paper and Allied Products (SIC 26)
0.095
15.71
5.
Chfmicals and Allied Products (SIC 28)
0.073
15.86
3.39 4.92
6.
l&tile Mill Prcducts (SIC 22)
0.029
22.28
7.
Focd and Kimlred PXdUctS
(SIC 20)
0.012
23.59
5.24
8. Fabricated Metal Products (SIC 34)
0.016
20.00
4.36
9.
0.009
22.52
4.97
10. Machinery excluding electrical (SIC 35) 0.007
34.82
8.20
71) (2) (3)
Tran~rtation
Fquiprent (SIC 37)
Efficiency is defined as the number of Btu's consumed relative to the dollar value added in constant dollars. Ranked by 1976 energy intensities. In trillions of Btu's per millions of dollars.
equal the percentage change in the quantity of energy demanded relative to the percentage change in price. Implicit in this definition is the assumption that all other factors affecting the demand for energy (e.g. the level of economic activity) are constant.) The essential ingredient in this evaluation is an accurate measure of the price elasticity. A large number of studies exist measuring the price elasticity of industrial demand at the aggregate level for specific fuels. Taylor[4] has a nice summary of some of these. At the more disaggregated level, the availability of studies is limited. It is typically the case that one estimation technique or functional specification is applied to a given two digit SIC industry (there appears to be only one study that goes below the two digit level (Uri[S])). The result is a conglomeration of elasticity estimates that have little more in common than the definition of elasticity. There are a few exceptions, however. Estimates by Norman and Russell[6] and Halvorsen[7], of the price elasticity of demand for energy exist at the two digit SIC level. Both use a methodological approach based on the theory of producer optimization. Various specifications of cost and profit functions are employed (the translog price possibility frontier is very popular). The data for the most part are obtained from or based on the ASM or the Census of Manufacturers and the period 195C74. The price elasticity estimates obtained range between -1.20 and -0.36 across industries. A straightforward application of the definition of elasticity would yield the anticipated reduction in energy demand resulting from the higher energy prices. Actual real price changes in energy to the various two-digit SIC industries as computed from the ASM are given in Table 2. They have been quite significant ranging from a high of 152.7% for petroleum and coking products to a low of 49.3% for transportation equipment. The issue that becomes immediately transparent is that if the elasticity estimates are accepted and given the magnitude of the energy price rise, a significantly greater reduction is energy consumption should have been observed. Thus, for example, Norman and Russell obtain an elasticity estimate of -0.09 for food and kindred products. (Halvorsen
Table Industry
2. Change
cl)
in energy
price:
% Change Price(2) 1971-1976
1.
SIC 29
152.7
2.
SIC 33
61.4
3.
SIC 32
72.4
4.
SIC 26
82.8
5.
SIC 28
94.4
6.
SIC 22
75.8
7.
SIC 20
64.5
8.
SIC 34
83.0
9.
SIC 37
49.3
10. SIC
1971-76
35
65.1
(1)
Ranked
(2)
Real
in order
percent
of 1976 energy
intensities.
change.
obtained a value of approx. -1.1 averaged across fuels.) This combined with the price increase of 64.5% should have resulted in a 58% reduction in the demand for energy. What was actually observed, however, was only a 24% reduction in energy demand. Note that, as suggested previously, the price elasticity is based on a ceteris paribus assumption. The level of output is held constant because the efficiency measure is denominated in Btu’s per one dollar value-added (i.e. per unit). Other factors potentially important in influencing the demand for energy (e.g. weather and natural gas availability) are not held constant in the efficiency measure. Their inclusion, however, would not account for the sizeable disparity observed here. This leads to the conclusion that rather (1) the elasticities were incorrectly measured, (2) they were incorrectly interpreted or (3) they have changed from the estimation period. There is no in-
Industrial
energy efficiency:a look at the data
dication that they are incorrectly measured. Norman and Russell use eleven different functional specifications and come up with fairly consistent estimates of price elasticities for the various two digit SIC industries. Additionally, the other industry specific studies alluded to previously indicate price elasticities similar to those of Norman and Russell. When interpreting demand elasticities the issue of short-term vs long-term responsiveness of the quantity demanded to price changes becomes relevant. Since none of the specifications reflect the lag in the adjustment process, the estimated elasticities properly reflect something between the two extremes (short-term and long-term). The recognition of this does not provide a resolution to the problem of quantitatively associating energy demand changes and price changes. The impact of energy price changes in 1971 would be substantially exhausted by 1976. But, there were price changes in 1972-75 also affecting the quantity of energy demanded that must be considered. The effect of a price change between 1975 and 1976 would properly be looked upon as a short-run consideration whereas the effects of price changes in the other years are more properly evaluated as mid- to long-run phenomena. The substance of these observations is just that a precise quantitative assessment of this issue is not possible. (Note that a theoretical structure for assessing the dynamic nature of industrial energy demand has been suggested but not yet empirically implemented (Berndt et al. [S]).) The resolution of the dilemma also must partly lie in the fact that the elasticities have changed and changed quite significantly between the estimation interval and the period of current investigation (1971-76). To the extent that various four digit SIC industries within a given two digit category have differing technological (and institutional) capabilities of responding to energy price variations and given that there has been a changing product mix, then the hypothesis that price elasticies have been changing can be accepted. There is a potential additional problem. If four digit SIC firms have adopted new energy efficient technologies to the maximum degree, then it is simply not possible for them to respond to further increases in the price of energy. This will be translated into smaller price elasticities. Unfortunately, given the paucity of the data at the present time, it is not possible to objectively examine this. This excursion into considering the effect of price on the demand for energy in the industrial sector has led to the conclusion that it is difficult, if not impossible, to say something quantitative about the impact. What must be done is to resort to a more qualitative analysis and look at the shifting product mix and derive the inferences from these observations.
253
international economic growth and contraction in addition to changing consumer preferences. At the process level, there is little flexibility in the short run for reoptimizing the mix of the factors of production (capital, labor, energy and materials) in response to a change in the price or availability of any of them. Improved process control and plant operation (i.e. housekeeping measures) are generally the first action to be undertaken. These de facto constitute moving onto, or very near to, the production possibility frontier. Over a larger horizon, switching to alternative fuels and gradual replacement of depreciated process components with more energy-efficient ones will occur. Over this longer period, process technologies will change by significant, discontinuous magnitudes as research and development efforts are focused on improving energy efficiency. At the process level, then, the interrelationship between energy demand and product demand would be expected to alter over time as the relative prices of the factors of production change. How quickly and the extent to which this change is observed depends upon (a) the size of the change in the cost of the factors of production (i.e. energy relative to the others) and (b) the ability of individual agents to take advantage of new technologies. This gives rise to a major consideration. As increased energy costs are translated into higher product prices, the quantity demanded of these products will decrease. The quantity demanded (i.e. sales) of energy intensive products will fall relative to less energy intensive products. For the latter group, sales might actually rise. This depends, of course, on the strength of the substitution effect. Aggregate measures of industrial output (at the two digit SIC level, for example) might continue to grow at, or near, historical rates disguising the underlying change in the composition of output. As economic activity slackens, the extent to which an energy intensive industry can offset a reduction in sales by reducing energy costs depends primarily on how easily it can substitute other factors of production for it, essentially capital (see Uri [9]). As access to money in the capital markets becomes more difficult (because of the slackening of economic activity) so does the ability of the industry to make fundamental process changes. The relationship of energy use to output becomes increasingly inflexible resulting in an increase in the vulnerability of the industry to subsequent energy price variations. Summarily, the elements affecting the energy demand in the industrial sector can be characterized as follows: (a) factors which determine the demand for products and consequently the level and composition of output; (b) process factors which determine the energy-efficiency CHANGING PROWCT MIX for a given level of production; (c) the time element which affects the rate of technological innovation and (a) Theoretical considerations” Before looking at the data it is useful to understand the adoption; (d) financial factors including access to capital nature of demand for energy in the industrial sector. The markets. Given these considerations, one can conclude that demand for energy in the industrial sector is a derived demand. That is, it comes from the demand for the there is every reason to believe that, in light of what has product for which energy is used to produce. To the transpired in the energy market, changing energy efficiency at the aggregate level (two digit SIC) should be extent that production technologies remain unchanged over short periods of time, industrial energy demand is observed. (This will hold assuming that the production derived from the complex workings of domestic and functions at the four digit SIC level differ across industries.) To gain an appreciation of this, observed “Some of these considerations are more fully discussed in behavior over the period 1971-76 is examined in the next Reay[lO], Dumas[I 11, Marlayll21and Williamsonll31. section.
254
N. D.
(b) Empirical observations b The most efficient way of investigating the changing energy efficiencies at the four digit SIC level is to look at them in the context of what happened relative to the two digit industry average. In this regard, the two digit industries will be examined in decreasing order of 1976 efficiency levels.’ I. SIC 20The petroleum and coal products industry is dominated by one four digit SIC industry-SIC 2911 (petroleum refining). (It accounted for 87% of the value of output in 1976.) Its average rate of growth in value added (9.3% per year) exceeded the 2 digit average (8.2%). The primary users of energy in the refining process are the distillation columns and strippers and splitters (which separate the crude oil into the numerous end products.) There was a very large improvement in efficiency for this four digit industry, averaging 12.5 improvement per year over the period 19771-76and negligible improvement for the other four digit industries. (The main sources of efficiency improvements were increased utilization of refinery capacity, expanded waste heat recovery and improved furnace efficiencies [ IO].) In the case of this two digit industry, a small portion of the efficiency improvement reflected the relative growth in SIC 291I output but the largest component was due to technological and returns to scale (capacity utilization) considerations. 2. SIC 33-The primary metals industry is one of the best examples of changing product mix. Total value added over the period of investigation increased by 2.4% annually but output in the two dominant four digit SIC industries-SIC 331I (blast furnaces and steel mills) and SIC 3357 (nonferrous wire drawing) which accounted for 55% of the value added in I976-decreased by 1.2% while efficiency actually deteriorated by 1.6%. Other four digit industries-notably SIC 3315 (steel wire products), SIC 3316 (cold finishing of steel shapes), SIC 3321 (gray iron foundries), SIC 3331 (primary copper), SIC 3334 (primary aluminum) and SIC 3341 (secondary nonferrous metalstaccounting for 26% of value added in 1976 improved their efficiencies (those noted here improved their efficiencies by about 4.5%) while expanding their output (these six expanded by 4.8%). The overall efficiency of these six industries was about 30% above the combined efficiency of SIC 3211 and SIC 3357. The combination of improved efficiencies of these six industries and their increased level of production were the major reasons why one did not see an overall deterioration in industry efficiency between 1971 and 1976. 3. SIC 32-The stone, clay and glass products industry does not have a dominant four digit SIC industry that lost ground relative to other industries in the classification. None of the four digit SIC industries accounted, for more than 15% of the output. There was, however, a change in the overall product mix in four of the more energy intensive industries. In particular, output in SIC 3221 (glass containers), SIC 3255 (clay refractories), SIC 3259 (structural clay products), and SIC 3272 (concrete products) remained virtually unchanged over the period 1971-76 while output in SIC 3229 (pressed and blown glass), SIC 3273 (ready-mixed concrete), SIC 3295
bAll of the percentages in this section are annual averages unless otherwise noted. ‘In trillions of Btu’s oer million of dollars.
URI
(minerals, ground or treated) and SIC 32% (mineral wool) increased by about 6%. Additionally, these latter industries in the aggregate had about a 25% higher efficiency level than the former. Again incorporated in the changed two digit SIC efficiency was this element of changing product mix. One interesting caveat is that SIC 3296 directly benefitted from the increased awareness of energy use. Mineral wool is used as a light density insulation material and SO the demand for its product expanded as concern for energy conservation evolved. 4. SIC 2bChanging product mix and differing energy efficiencies characterizes the paper and allied products industry. Three four digit SIC industries-SIC 261I (pulp mills), SIC 2643 (bags), and SIC 2647 (sanitary paper products) accounting for 20% of 1976 value added grew at more than 2.5 times the industry average. This coupled with their much larger efficiency (approx. 42% better) had the distinct effect of biasing upward the measured improvement in efficiency indicated by housekeeping factors alone. The efficiency of these four digit SIC industries increased faster than the two digit average (8% per year vs 3.3%) partly because of increased capacity utilization and possibly because of technological factors. The latter include operation of boilers at maximum efficiency, conducting preventive maintenance on rotating machinery components, installation of more efficient pulping equipment, etc. 5. SIC 2PChemicals and allied products is another of the two digit SIC industries dominated by a few large four digit SIC industries. (Six four digit SIC industries accounted for 72% of the value added in 1976.) Again changing product mix characterizes some of the efficiency improvement. Output of the large four digit SIC industries grew at approximately the annual two digit industry average (4%) with the exception of SIC 2869 (industrial organic chemicals) which grew at twice that rate. This four digit industry combined with the growth in output of SIC 2812 (alkalies and chlorine) at l4%, SIC 2831 (biological products) at 11% and SIC 2833 (medicinals) at 17% had an annual efficiency improvement of 11% vs an improvement of 3% for the chemicals and allied products industry as a whole. The significant improvement in overall industry performance is reflecting primarily the improvement in the efficiency of these four industries. Some of the improvement is attributable to expanded capacity utilization (in the case of SIC 2831 and SIC 2833 which witnessed an expanded product demand) and some came about through improvements in the production techniques. Specifically, it was found that heat loads in the distillation stage could be reduced without affecting the quality of the final product. The increase in efficiency of SIC 2812 from 0.474 to 0.218 between 1971 and 1976 best exemplifies this. 6. SIC 22-The notable aspect of textile mill products output is the impact that the relatively energy intensive industries SIC 2221 (weaving mills, manmade fibers) and SIC 2262 Finishing plants, manmade fibers) had. Both had growths in energy efficiencies above the industry n0r.m (27 and l4%, over the period WI-76 respectively) whde at the same time increasing their overall (aggregate) share of output from 21 to 28% between 1971 and 1976. Some of this shift (increase in share) was stimulated by the increase in the price of natural fibers arising _ from increased labor and material costs which de facto shifted the demand for manmade fibers. The impact of c.. .__I .I tecnnology was ralrly even across four digit industries-
Industrial energy efficiency: a look at the data
the principal improvement coming in drying at textile plants where more effective heat recovery and prior mechanical treatment using mangles and vacuum slots to reduce water content to a minimum were instituted. The differential efficiency improvement (above the industry average) for SIC 2221 and SIC 2262 apparently resulted from return to scale considerations and some housekeeping measures including the avoidance underloading, reducing water temperatures, and re-using hot water. 7. SIC 2kGrowth in the production of food and kindred products was fairly homogeneous over tlie period of investigation. One interesting phenomena, however, involved a reduction in the level of output in SIC 2082 (malt beverages) by 3.7% with corresponding deterioration in efficiency of 3.7%. This industry was simply moving away from its production frontier (i.e. optimal level of production given capacity). Beyond this there did not appear to be any significant change in the product mix. Some innovations were adopted-including a reduction in the amount of water used in processing, use of pressure cooking instead of ambient cooking and continuous processing--that had the overall effect of improving efficiency. 8. SIC 34-The four digit SIC industries in the fabricated metal products industry are relatively energy efficient. A relatively small number of firms did not dominate the total value added at the two digit SIC level. The only significant factors were growth in output of SIC 3462 (iron and steel forgings) and SIC 3479 (metal coating, allied services) at three times the SIC 34 average (these two four digit SIC industries accounted for 5%,of total value added in 1976) and relatively large efficiency improvements in SIC 3444 (sheet metal work), SIC 3462 (iron and steel forging), SIC 3463 (nonferous forgings) and SIC 3494 (valves and pipe fittings) at four to five times the industry average. The improvements in efficiency were essentially the result of increases in temperature and pressure and improvements in charging and furnace control technology. There was not an appreciable change in the product mix and the growth in output was not of sufficient magnitude (industry average of 1.8% per year) to indicate that more efficient utilization of capacity was anything more than passive in improving the efficiency of the industry as a whole. 9. SIC 37-The transportation equipment industry is dominated by the four digit SIC 371I (motor vehicle and car bodies) and by SIC 3714 (motor vehicle parts, accessories) industries. In 1976 they were responsible for 75% of total industry output. In the case of SIC 3711, it grew at approximately the industry average while SIC 3714 grew at twice the industry average over the period of investigation (1971-76). There was a significant improvement in the market share of SIC 3714 from 2% in 1971 to 35% in 1976. Coincidentally its efficiency improved 32% reflecting in part the improvement coming from increased utilization of capacity. Other four digit SIC industries expanded their relative share of output while simultaneously experiencing an improvement in energy efficiency. Specifically, SIC 3713 (truck and bus bodies), SIC 3715 (truck trailer), and SIC 3732 (boat building and repairing) expanded an average at an annual rate of 9% (vs 5% for the industry as a whole) while efficiency improved at a rate of 14% (vs 5% for the industry). (They accounted for 5% of industry output in 1976.) Further these industries had an average 27% higher efficiency level than the industry average.
255
Changed product mix clearly affected the apparent improvement in energy efficiency. IO. SIC 35-The same type of occurrences characteristic of most of the other two digit SIC industries investigated are present in the machinery (except electrical) industry. Five four digit SIC industries-SIC 3533 (oil field machinery), SIC 3541 (machine tools, metal cutting), SIC 3559 (special industry machinery), SIC 3573 (electronic computing equipment) and SIC 3579 (oflice machines, typewritersbxhibited sizeable increases in output (an average of 13.5% vs the industry average of 6%) while at the same time realizing some improvements in energy efficiency (10% vs an industry average of 8%). This differential had an impact on the overall average given that these four digit SIC industries accounted for 33% of the value added in 1976. In addition to the disparity in growth rates between these specific four digit SIC industries and the industry average, these four digit SIC’s averaged about a 1% better efficiency level than SIC 35 in the aggregate. An additional interesting phenomenon was the sizeable decline in the level of output of SIC 3534 (elevators and moving stairways) of 14.5% annually over the period 1971-76. Correspondingly, the energy efficiency fell (became worse) by 7.3% per year as there was movement away from the production possibility frontier. Again the combination of technological improvements leading to higher energy efficiencies (continuous processing, between use of process steam by adding insulation and reducing leaks, etc.), capacity utilization considerations and variations in the product mix led to the change in the observed improvement in the energy efficiency for the production machinery. CONCLUSlON
It is extremely difficult to make a precise, quantitative assessment of the impact of the myriad of factors affecting the improvement in industrial energy efficiency. It is certainly not correct to conclude that housekeeping measures alone have led to the observed improvement. Changing product mix among four digit SIC industries within the same two digit classification, variations in capacity utilization (returns to scale) and energy price increases as well as technological innovations have all contributed to part of the realized reduction in energy use per dollar value added over the period of investigation. Unfortunately, data limitations as well as modeling weaknesses prohibit an exact delineation of the impact of each of the factors on the increase in energy efficiency. The best that can be done-and quite convincingly so-is to qualitatively show that unequivocally these factors had an impact on the efficiency with which energy was used in the manufacturing process for the ten most energy intensive industries in the period 1971-76.
REFERENCES I. l-l. S. Leff, R. S. Mack and J. F. Bodine, PotentialforFuture Energy Conservation. Institute for Energy Analysis, Oak Ridge Associated Universities, Oak Ridge (Feb. 1980). 2. Department of Energy, Annual Report, Industrial Energy Eficiency
Progmm,
July
19774kcember
0111, Washington (Dec. 197%. 3. The Conference Board, Energy turing.
Consumption
Ballinger,Cambridge,Mass.(1977).
1978.
DOE/W
in hnufac-
2%
N. D. URI
4. L. D. Tavlor. The demand for energy-a survey. In International kudies in the Demand for-Energy (Edited by W. Nordhaus). North-Holland, Amsterdam (1977). _._._ 5. N. D. Uri: Interfuel substitution in the primary metals industries. Energy
J(S), 591-598. (Oct. 1978).
6. M. R. Norman and R. R. Russell, Development of Methods for Forecasting the National Industrial Demand for Energy. Electric Power Research Institute, Palo Alto (July 1976). 7. R. Halvorsen, Econometric Models of U.S. Energy Demand. D. C. Heath and Company, Lexington, Mass. (1978). 8. E. R. Berndt, M. A. Fuss and L. Waverman, Dynamic Models of the Industrial Demand for Energy. Electric Power Research Institute, Palo Alto (Nov. 1977).
view. Processed 9. N. D. Uri, Factor substitutability-another (March 1980). Energy Conservation. Pergamon 10. D. A. Reay, Industrial Press, Oxford (1977). Response. D. C. Heath and II. L. J. Dumas, The Conservation Co. Lexington, Mass. (1976). 12. R. C. Marlay, Industrial Energy Use and Conservation. Office of Conservation and Solar Application, Department of Energy, Washington (Sept. 1979). 13. R. D. Williamson, Energy Use in the U.S. Residential and Industrial Sectors in the Year 2000. Institute for Energy Analysis, Oak Ridge Associated Universities, Oak Ridge (Feb. 1980).
INDUSTRIAL ENERGY EFFICIENCY: A LOOK AT THE DATA NOEL D. URIt Department
of Energy, Office of Energy Use Analysis, Energy Use Technologies Division, Washington, DC 20461 U.S.A. (Receiued 18 April
1980)
Abstract-It is extremely difficult to make a precise, quantitative assessment of the impact of the myriad of factors affecting the improvement in industrial energy efficiency. It is certainly not comect to conclude that housekeeping measures alone have led to the observed improvement. Changing product mix among four digit SIC industries within the same two digit classification, variations in capacity utilization (returns to scale) and energy price increases as well as technological innovations have all contributed to part of the realized reduction in energy use per dollar value added over the period of investigation. Unfortunately, data limitations as well as modeling weaknesses prohibit an exact delineation of the impact of each of the factors on the increase in energy efficiency. The best that can be done-and quite convincingly so-is to qualitatively show that unequivocally these factors had an impact on the efficiencv with which enerev was used in the manufacturingprocess for the ten most energy intensive industries in the per&d 1971-76. -’
INTRODUCTION
Recent
years
have
seen a marked
improvement
in industrial energy efficiency. (See Leff et a!.[11 for a survey of this area.) The amount of energy needed to produce a unit of output (measured in nominal terms) has fallen precipitously in almost all industries. The extent of this improvement in the ten most energy intensive two digit SIC industries is given in Table I. The origin of this improvement is not as transparent as its existence. To be sure, a portion of the achieved reduction in energy intensity can be attributed to housekeeping measures[2]. This, however, is not the sole explanation for the observed amelioration. The distinct possibility exists that some of this efficiency improvement is illusory. That is, first, the product mix from industries within the two digit SIC categories is changing so that the output the less energy intensive industries is growing relative to the output of the less efficient and consequently while it is true efficiency is increasing this component of the increase is not attributable to conservation efforts. Second, the dramatic escalation in the price of energy has provided a considerable incentive to conserve. These effects must be netted out before any inference can be made concerning the efficacy of the argument that non-price induced conservation is responsible for the observed industrial energy efficiency improvement. Third, the level of economic activity has fluctuated over the period for which the energy efficiencies are computed. To the I extent that industries within the two digit SIC categorization are differentially impacted (that is, for example if the relatively energy inefficient four digit SIC industries are affected the most) then the reported efficiency improvement will be misleading. Given these considerations, the objective of this paper is to attempt to sort out the effects alluded to here to the degree possible with the objective of more fully under-
tThe views expressed are those of the author and do not necessarily represent the policies of the department of energy or the views of other department of energy staff members.
standing conservation over the historical period as well as using the results to evaluate the potential for future conservation of energy in the industrial sector. The data used in the analysis are from the Annual Survey of Manufacturers (ASM) collected by the Bureau of the Census. These data are the most reliable at the annual industry specific level. Other existing energy annual data series typically use the ASM as a starting point. The survey years considered include 1971 and 1974-76. Preliminary data for 1977 are available but only at the two digit SIC level. Since much of the concern is focused on a more disaggregated level, data for 1976 is the most recent used. One final comment before proceeding with the essence of the paper is needed. It concerns an objective measurement of energy efficiency. There are a myriad of potential measures each with its deficiency. (See The Conference Board(31 for a discussion.) For the purposes at hand, the value defined as Btu’s per dollar value-added is used to measure energy efficiency both between industries within the same two digit SIC category and between industries in different two digit SIC categories. The Btu’s are denominated in millions and the dollar value-added is in thousands of constant 1971dollars. The measure has the slight defect in that during periods of economic downturn the fixed cost component of the value of each unit of output will rise (as total fixed cost is spread over a few number of units of output) and consequently the value-added measure tends to understate the magnitude of fluctuations in economic activity. As a result the full effect of changes in the level of economic activity is not being removed from the efficiency measure. PRICE EFFECTS
As noted in portant effects
the foregoing discussion, one of the imon efficiency has been the impact of price. An indication of this impact can ostensibly be obtained by looking at the actual percentage change in the price of energy per Btu (in real terms) times the price elasticity of the demand for energy. (The price elasticity is defined to 251
N. D. URI
252 Table
1. Change
in industrtria!energy
efficiency”’
(ten most energy
intensive
industries”‘)
Annual Averaqe Chawe (%I
1976 Effi-
1.
Pet.rolem
am3 cixl
2.
primry mtals
products
(SIC 29)
rrdustries (SIC 33)
0.155
45.23
11.35
0.121
1.47
0.30
1.672
3.59 3.36
3.
stone, clay, Glass products (SIC 32)
0.105
4.
Paper and Allied Products (SIC 26)
0.095
15.71
5.
Chfmicals and Allied Products (SIC 28)
0.073
15.86
3.39 4.92
6.
l&tile Mill Prcducts (SIC 22)
0.029
22.28
7.
Focd and Kimlred PXdUctS
(SIC 20)
0.012
23.59
5.24
8. Fabricated Metal Products (SIC 34)
0.016
20.00
4.36
9.
0.009
22.52
4.97
10. Machinery excluding electrical (SIC 35) 0.007
34.82
8.20
71) (2) (3)
Tran~rtation
Fquiprent (SIC 37)
Efficiency is defined as the number of Btu's consumed relative to the dollar value added in constant dollars. Ranked by 1976 energy intensities. In trillions of Btu's per millions of dollars.
equal the percentage change in the quantity of energy demanded relative to the percentage change in price. Implicit in this definition is the assumption that all other factors affecting the demand for energy (e.g. the level of economic activity) are constant.) The essential ingredient in this evaluation is an accurate measure of the price elasticity. A large number of studies exist measuring the price elasticity of industrial demand at the aggregate level for specific fuels. Taylor[4] has a nice summary of some of these. At the more disaggregated level, the availability of studies is limited. It is typically the case that one estimation technique or functional specification is applied to a given two digit SIC industry (there appears to be only one study that goes below the two digit level (Uri[S])). The result is a conglomeration of elasticity estimates that have little more in common than the definition of elasticity. There are a few exceptions, however. Estimates by Norman and Russell[6] and Halvorsen[7], of the price elasticity of demand for energy exist at the two digit SIC level. Both use a methodological approach based on the theory of producer optimization. Various specifications of cost and profit functions are employed (the translog price possibility frontier is very popular). The data for the most part are obtained from or based on the ASM or the Census of Manufacturers and the period 195C74. The price elasticity estimates obtained range between -1.20 and -0.36 across industries. A straightforward application of the definition of elasticity would yield the anticipated reduction in energy demand resulting from the higher energy prices. Actual real price changes in energy to the various two-digit SIC industries as computed from the ASM are given in Table 2. They have been quite significant ranging from a high of 152.7% for petroleum and coking products to a low of 49.3% for transportation equipment. The issue that becomes immediately transparent is that if the elasticity estimates are accepted and given the magnitude of the energy price rise, a significantly greater reduction is energy consumption should have been observed. Thus, for example, Norman and Russell obtain an elasticity estimate of -0.09 for food and kindred products. (Halvorsen
Table Industry
2. Change
cl)
in energy
price:
% Change Price(2) 1971-1976
1.
SIC 29
152.7
2.
SIC 33
61.4
3.
SIC 32
72.4
4.
SIC 26
82.8
5.
SIC 28
94.4
6.
SIC 22
75.8
7.
SIC 20
64.5
8.
SIC 34
83.0
9.
SIC 37
49.3
10. SIC
1971-76
35
65.1
(1)
Ranked
(2)
Real
in order
percent
of 1976 energy
intensities.
change.
obtained a value of approx. -1.1 averaged across fuels.) This combined with the price increase of 64.5% should have resulted in a 58% reduction in the demand for energy. What was actually observed, however, was only a 24% reduction in energy demand. Note that, as suggested previously, the price elasticity is based on a ceteris paribus assumption. The level of output is held constant because the efficiency measure is denominated in Btu’s per one dollar value-added (i.e. per unit). Other factors potentially important in influencing the demand for energy (e.g. weather and natural gas availability) are not held constant in the efficiency measure. Their inclusion, however, would not account for the sizeable disparity observed here. This leads to the conclusion that rather (1) the elasticities were incorrectly measured, (2) they were incorrectly interpreted or (3) they have changed from the estimation period. There is no in-
Industrial
energy efficiency:a look at the data
dication that they are incorrectly measured. Norman and Russell use eleven different functional specifications and come up with fairly consistent estimates of price elasticities for the various two digit SIC industries. Additionally, the other industry specific studies alluded to previously indicate price elasticities similar to those of Norman and Russell. When interpreting demand elasticities the issue of short-term vs long-term responsiveness of the quantity demanded to price changes becomes relevant. Since none of the specifications reflect the lag in the adjustment process, the estimated elasticities properly reflect something between the two extremes (short-term and long-term). The recognition of this does not provide a resolution to the problem of quantitatively associating energy demand changes and price changes. The impact of energy price changes in 1971 would be substantially exhausted by 1976. But, there were price changes in 1972-75 also affecting the quantity of energy demanded that must be considered. The effect of a price change between 1975 and 1976 would properly be looked upon as a short-run consideration whereas the effects of price changes in the other years are more properly evaluated as mid- to long-run phenomena. The substance of these observations is just that a precise quantitative assessment of this issue is not possible. (Note that a theoretical structure for assessing the dynamic nature of industrial energy demand has been suggested but not yet empirically implemented (Berndt et al. [S]).) The resolution of the dilemma also must partly lie in the fact that the elasticities have changed and changed quite significantly between the estimation interval and the period of current investigation (1971-76). To the extent that various four digit SIC industries within a given two digit category have differing technological (and institutional) capabilities of responding to energy price variations and given that there has been a changing product mix, then the hypothesis that price elasticies have been changing can be accepted. There is a potential additional problem. If four digit SIC firms have adopted new energy efficient technologies to the maximum degree, then it is simply not possible for them to respond to further increases in the price of energy. This will be translated into smaller price elasticities. Unfortunately, given the paucity of the data at the present time, it is not possible to objectively examine this. This excursion into considering the effect of price on the demand for energy in the industrial sector has led to the conclusion that it is difficult, if not impossible, to say something quantitative about the impact. What must be done is to resort to a more qualitative analysis and look at the shifting product mix and derive the inferences from these observations.
253
international economic growth and contraction in addition to changing consumer preferences. At the process level, there is little flexibility in the short run for reoptimizing the mix of the factors of production (capital, labor, energy and materials) in response to a change in the price or availability of any of them. Improved process control and plant operation (i.e. housekeeping measures) are generally the first action to be undertaken. These de facto constitute moving onto, or very near to, the production possibility frontier. Over a larger horizon, switching to alternative fuels and gradual replacement of depreciated process components with more energy-efficient ones will occur. Over this longer period, process technologies will change by significant, discontinuous magnitudes as research and development efforts are focused on improving energy efficiency. At the process level, then, the interrelationship between energy demand and product demand would be expected to alter over time as the relative prices of the factors of production change. How quickly and the extent to which this change is observed depends upon (a) the size of the change in the cost of the factors of production (i.e. energy relative to the others) and (b) the ability of individual agents to take advantage of new technologies. This gives rise to a major consideration. As increased energy costs are translated into higher product prices, the quantity demanded of these products will decrease. The quantity demanded (i.e. sales) of energy intensive products will fall relative to less energy intensive products. For the latter group, sales might actually rise. This depends, of course, on the strength of the substitution effect. Aggregate measures of industrial output (at the two digit SIC level, for example) might continue to grow at, or near, historical rates disguising the underlying change in the composition of output. As economic activity slackens, the extent to which an energy intensive industry can offset a reduction in sales by reducing energy costs depends primarily on how easily it can substitute other factors of production for it, essentially capital (see Uri [9]). As access to money in the capital markets becomes more difficult (because of the slackening of economic activity) so does the ability of the industry to make fundamental process changes. The relationship of energy use to output becomes increasingly inflexible resulting in an increase in the vulnerability of the industry to subsequent energy price variations. Summarily, the elements affecting the energy demand in the industrial sector can be characterized as follows: (a) factors which determine the demand for products and consequently the level and composition of output; (b) process factors which determine the energy-efficiency CHANGING PROWCT MIX for a given level of production; (c) the time element which affects the rate of technological innovation and (a) Theoretical considerations” Before looking at the data it is useful to understand the adoption; (d) financial factors including access to capital nature of demand for energy in the industrial sector. The markets. Given these considerations, one can conclude that demand for energy in the industrial sector is a derived demand. That is, it comes from the demand for the there is every reason to believe that, in light of what has product for which energy is used to produce. To the transpired in the energy market, changing energy efficiency at the aggregate level (two digit SIC) should be extent that production technologies remain unchanged over short periods of time, industrial energy demand is observed. (This will hold assuming that the production derived from the complex workings of domestic and functions at the four digit SIC level differ across industries.) To gain an appreciation of this, observed “Some of these considerations are more fully discussed in behavior over the period 1971-76 is examined in the next Reay[lO], Dumas[I 11, Marlayll21and Williamsonll31. section.
254
N. D.
(b) Empirical observations b The most efficient way of investigating the changing energy efficiencies at the four digit SIC level is to look at them in the context of what happened relative to the two digit industry average. In this regard, the two digit industries will be examined in decreasing order of 1976 efficiency levels.’ I. SIC 20The petroleum and coal products industry is dominated by one four digit SIC industry-SIC 2911 (petroleum refining). (It accounted for 87% of the value of output in 1976.) Its average rate of growth in value added (9.3% per year) exceeded the 2 digit average (8.2%). The primary users of energy in the refining process are the distillation columns and strippers and splitters (which separate the crude oil into the numerous end products.) There was a very large improvement in efficiency for this four digit industry, averaging 12.5 improvement per year over the period 19771-76and negligible improvement for the other four digit industries. (The main sources of efficiency improvements were increased utilization of refinery capacity, expanded waste heat recovery and improved furnace efficiencies [ IO].) In the case of this two digit industry, a small portion of the efficiency improvement reflected the relative growth in SIC 291I output but the largest component was due to technological and returns to scale (capacity utilization) considerations. 2. SIC 33-The primary metals industry is one of the best examples of changing product mix. Total value added over the period of investigation increased by 2.4% annually but output in the two dominant four digit SIC industries-SIC 331I (blast furnaces and steel mills) and SIC 3357 (nonferrous wire drawing) which accounted for 55% of the value added in I976-decreased by 1.2% while efficiency actually deteriorated by 1.6%. Other four digit industries-notably SIC 3315 (steel wire products), SIC 3316 (cold finishing of steel shapes), SIC 3321 (gray iron foundries), SIC 3331 (primary copper), SIC 3334 (primary aluminum) and SIC 3341 (secondary nonferrous metalstaccounting for 26% of value added in 1976 improved their efficiencies (those noted here improved their efficiencies by about 4.5%) while expanding their output (these six expanded by 4.8%). The overall efficiency of these six industries was about 30% above the combined efficiency of SIC 3211 and SIC 3357. The combination of improved efficiencies of these six industries and their increased level of production were the major reasons why one did not see an overall deterioration in industry efficiency between 1971 and 1976. 3. SIC 32-The stone, clay and glass products industry does not have a dominant four digit SIC industry that lost ground relative to other industries in the classification. None of the four digit SIC industries accounted, for more than 15% of the output. There was, however, a change in the overall product mix in four of the more energy intensive industries. In particular, output in SIC 3221 (glass containers), SIC 3255 (clay refractories), SIC 3259 (structural clay products), and SIC 3272 (concrete products) remained virtually unchanged over the period 1971-76 while output in SIC 3229 (pressed and blown glass), SIC 3273 (ready-mixed concrete), SIC 3295
bAll of the percentages in this section are annual averages unless otherwise noted. ‘In trillions of Btu’s oer million of dollars.
URI
(minerals, ground or treated) and SIC 32% (mineral wool) increased by about 6%. Additionally, these latter industries in the aggregate had about a 25% higher efficiency level than the former. Again incorporated in the changed two digit SIC efficiency was this element of changing product mix. One interesting caveat is that SIC 3296 directly benefitted from the increased awareness of energy use. Mineral wool is used as a light density insulation material and SO the demand for its product expanded as concern for energy conservation evolved. 4. SIC 2bChanging product mix and differing energy efficiencies characterizes the paper and allied products industry. Three four digit SIC industries-SIC 261I (pulp mills), SIC 2643 (bags), and SIC 2647 (sanitary paper products) accounting for 20% of 1976 value added grew at more than 2.5 times the industry average. This coupled with their much larger efficiency (approx. 42% better) had the distinct effect of biasing upward the measured improvement in efficiency indicated by housekeeping factors alone. The efficiency of these four digit SIC industries increased faster than the two digit average (8% per year vs 3.3%) partly because of increased capacity utilization and possibly because of technological factors. The latter include operation of boilers at maximum efficiency, conducting preventive maintenance on rotating machinery components, installation of more efficient pulping equipment, etc. 5. SIC 2PChemicals and allied products is another of the two digit SIC industries dominated by a few large four digit SIC industries. (Six four digit SIC industries accounted for 72% of the value added in 1976.) Again changing product mix characterizes some of the efficiency improvement. Output of the large four digit SIC industries grew at approximately the annual two digit industry average (4%) with the exception of SIC 2869 (industrial organic chemicals) which grew at twice that rate. This four digit industry combined with the growth in output of SIC 2812 (alkalies and chlorine) at l4%, SIC 2831 (biological products) at 11% and SIC 2833 (medicinals) at 17% had an annual efficiency improvement of 11% vs an improvement of 3% for the chemicals and allied products industry as a whole. The significant improvement in overall industry performance is reflecting primarily the improvement in the efficiency of these four industries. Some of the improvement is attributable to expanded capacity utilization (in the case of SIC 2831 and SIC 2833 which witnessed an expanded product demand) and some came about through improvements in the production techniques. Specifically, it was found that heat loads in the distillation stage could be reduced without affecting the quality of the final product. The increase in efficiency of SIC 2812 from 0.474 to 0.218 between 1971 and 1976 best exemplifies this. 6. SIC 22-The notable aspect of textile mill products output is the impact that the relatively energy intensive industries SIC 2221 (weaving mills, manmade fibers) and SIC 2262 Finishing plants, manmade fibers) had. Both had growths in energy efficiencies above the industry n0r.m (27 and l4%, over the period WI-76 respectively) whde at the same time increasing their overall (aggregate) share of output from 21 to 28% between 1971 and 1976. Some of this shift (increase in share) was stimulated by the increase in the price of natural fibers arising _ from increased labor and material costs which de facto shifted the demand for manmade fibers. The impact of c.. .__I .I tecnnology was ralrly even across four digit industries-
Industrial energy efficiency: a look at the data
the principal improvement coming in drying at textile plants where more effective heat recovery and prior mechanical treatment using mangles and vacuum slots to reduce water content to a minimum were instituted. The differential efficiency improvement (above the industry average) for SIC 2221 and SIC 2262 apparently resulted from return to scale considerations and some housekeeping measures including the avoidance underloading, reducing water temperatures, and re-using hot water. 7. SIC 2kGrowth in the production of food and kindred products was fairly homogeneous over tlie period of investigation. One interesting phenomena, however, involved a reduction in the level of output in SIC 2082 (malt beverages) by 3.7% with corresponding deterioration in efficiency of 3.7%. This industry was simply moving away from its production frontier (i.e. optimal level of production given capacity). Beyond this there did not appear to be any significant change in the product mix. Some innovations were adopted-including a reduction in the amount of water used in processing, use of pressure cooking instead of ambient cooking and continuous processing--that had the overall effect of improving efficiency. 8. SIC 34-The four digit SIC industries in the fabricated metal products industry are relatively energy efficient. A relatively small number of firms did not dominate the total value added at the two digit SIC level. The only significant factors were growth in output of SIC 3462 (iron and steel forgings) and SIC 3479 (metal coating, allied services) at three times the SIC 34 average (these two four digit SIC industries accounted for 5%,of total value added in 1976) and relatively large efficiency improvements in SIC 3444 (sheet metal work), SIC 3462 (iron and steel forging), SIC 3463 (nonferous forgings) and SIC 3494 (valves and pipe fittings) at four to five times the industry average. The improvements in efficiency were essentially the result of increases in temperature and pressure and improvements in charging and furnace control technology. There was not an appreciable change in the product mix and the growth in output was not of sufficient magnitude (industry average of 1.8% per year) to indicate that more efficient utilization of capacity was anything more than passive in improving the efficiency of the industry as a whole. 9. SIC 37-The transportation equipment industry is dominated by the four digit SIC 371I (motor vehicle and car bodies) and by SIC 3714 (motor vehicle parts, accessories) industries. In 1976 they were responsible for 75% of total industry output. In the case of SIC 3711, it grew at approximately the industry average while SIC 3714 grew at twice the industry average over the period of investigation (1971-76). There was a significant improvement in the market share of SIC 3714 from 2% in 1971 to 35% in 1976. Coincidentally its efficiency improved 32% reflecting in part the improvement coming from increased utilization of capacity. Other four digit SIC industries expanded their relative share of output while simultaneously experiencing an improvement in energy efficiency. Specifically, SIC 3713 (truck and bus bodies), SIC 3715 (truck trailer), and SIC 3732 (boat building and repairing) expanded an average at an annual rate of 9% (vs 5% for the industry as a whole) while efficiency improved at a rate of 14% (vs 5% for the industry). (They accounted for 5% of industry output in 1976.) Further these industries had an average 27% higher efficiency level than the industry average.
255
Changed product mix clearly affected the apparent improvement in energy efficiency. IO. SIC 35-The same type of occurrences characteristic of most of the other two digit SIC industries investigated are present in the machinery (except electrical) industry. Five four digit SIC industries-SIC 3533 (oil field machinery), SIC 3541 (machine tools, metal cutting), SIC 3559 (special industry machinery), SIC 3573 (electronic computing equipment) and SIC 3579 (oflice machines, typewritersbxhibited sizeable increases in output (an average of 13.5% vs the industry average of 6%) while at the same time realizing some improvements in energy efficiency (10% vs an industry average of 8%). This differential had an impact on the overall average given that these four digit SIC industries accounted for 33% of the value added in 1976. In addition to the disparity in growth rates between these specific four digit SIC industries and the industry average, these four digit SIC’s averaged about a 1% better efficiency level than SIC 35 in the aggregate. An additional interesting phenomenon was the sizeable decline in the level of output of SIC 3534 (elevators and moving stairways) of 14.5% annually over the period 1971-76. Correspondingly, the energy efficiency fell (became worse) by 7.3% per year as there was movement away from the production possibility frontier. Again the combination of technological improvements leading to higher energy efficiencies (continuous processing, between use of process steam by adding insulation and reducing leaks, etc.), capacity utilization considerations and variations in the product mix led to the change in the observed improvement in the energy efficiency for the production machinery. CONCLUSlON
It is extremely difficult to make a precise, quantitative assessment of the impact of the myriad of factors affecting the improvement in industrial energy efficiency. It is certainly not correct to conclude that housekeeping measures alone have led to the observed improvement. Changing product mix among four digit SIC industries within the same two digit classification, variations in capacity utilization (returns to scale) and energy price increases as well as technological innovations have all contributed to part of the realized reduction in energy use per dollar value added over the period of investigation. Unfortunately, data limitations as well as modeling weaknesses prohibit an exact delineation of the impact of each of the factors on the increase in energy efficiency. The best that can be done-and quite convincingly so-is to qualitatively show that unequivocally these factors had an impact on the efficiency with which energy was used in the manufacturing process for the ten most energy intensive industries in the period 1971-76.
REFERENCES I. l-l. S. Leff, R. S. Mack and J. F. Bodine, PotentialforFuture Energy Conservation. Institute for Energy Analysis, Oak Ridge Associated Universities, Oak Ridge (Feb. 1980). 2. Department of Energy, Annual Report, Industrial Energy Eficiency
Progmm,
July
19774kcember
0111, Washington (Dec. 197%. 3. The Conference Board, Energy turing.
Consumption
Ballinger,Cambridge,Mass.(1977).
1978.
DOE/W
in hnufac-
2%
N. D. URI
4. L. D. Tavlor. The demand for energy-a survey. In International kudies in the Demand for-Energy (Edited by W. Nordhaus). North-Holland, Amsterdam (1977). _._._ 5. N. D. Uri: Interfuel substitution in the primary metals industries. Energy
J(S), 591-598. (Oct. 1978).
6. M. R. Norman and R. R. Russell, Development of Methods for Forecasting the National Industrial Demand for Energy. Electric Power Research Institute, Palo Alto (July 1976). 7. R. Halvorsen, Econometric Models of U.S. Energy Demand. D. C. Heath and Company, Lexington, Mass. (1978). 8. E. R. Berndt, M. A. Fuss and L. Waverman, Dynamic Models of the Industrial Demand for Energy. Electric Power Research Institute, Palo Alto (Nov. 1977).
view. Processed 9. N. D. Uri, Factor substitutability-another (March 1980). Energy Conservation. Pergamon 10. D. A. Reay, Industrial Press, Oxford (1977). Response. D. C. Heath and II. L. J. Dumas, The Conservation Co. Lexington, Mass. (1976). 12. R. C. Marlay, Industrial Energy Use and Conservation. Office of Conservation and Solar Application, Department of Energy, Washington (Sept. 1979). 13. R. D. Williamson, Energy Use in the U.S. Residential and Industrial Sectors in the Year 2000. Institute for Energy Analysis, Oak Ridge Associated Universities, Oak Ridge (Feb. 1980).