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Energy in Transition, 1985-2010: Final Report of the Committee on Nuclear and Alternative Energy Systems 11 Methods and Analysis of Study Projections CONAES asked several of its panels to develop models of energy and the economy to make plain the interrelations among variables influencing the supply of and demand for the various forms of energy. These models were applied to sets of assumptions about, for example, the growth rate of the economy, changing prices for energy over the next three decades, and consumer response, to picture some plausible states of affairs in the year 2010 and the course of their development. Some of the resulting scenarios are described here to illustrate key interrelations and assumptions. There is always the danger in presenting models that numerical results will be taken literally. CONAES emphasizes that many uncertain assumptions must be made to construct models, and a great deal must be simplified or left out of consideration. Judgment alone decides whether some factors are important and whether others can be safely neglected, at least in a first approximation. Models cannot predict the future, but simply represent statements contingent on the consequences of assumptions and public policies. Nor can the consequences be regarded as rigorously deduced conclusions from a set of explicitly stated assumptions. Many detailed judgments accompany reason in these cases, judgments about the costs of new technologies, the rate of future resource discoveries, or the likely responses of myriads of producers and consumers to the general political climate and to government regulation. Many of the assumptions themselves are the subjects of wide disagreement among experts. For example, the Demand and Conservation Panel assumed an annual average growth rate for the gross national product (GNP) of 2 percent between 1975 and 2010, and defended this as their assessment of the most probable
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Energy in Transition, 1985-2010: Final Report of the Committee on Nuclear and Alternative Energy Systems rate of future economic growth, but most of the economists involved in this study find it implausibly low. All the scenarios are “surprise free” in the sense that they ignore discontinuities such as embargoes, revolutions, natural disasters, international conflicts, and domestic strikes. The value of models lies in the following. They allow “thought experiments” to be conducted on the likely consequences of specific policies such as supply constraints, energy taxes, mandatory efficiency standards, or price regulation. They allow testing of the sensitivity of outcomes (such as the rate of growth in energy consumption, or the relative consumption of various fuels) to varying input assumptions (such as economic growth rates, prices, population, work-force participation, or life-style preferences). They provide an accounting device that helps ensure internal consistency among the projections. They depict qualitative relations among the various factors affecting energy supply and demand. It is important to caution that the models do not usually prove qualitative statements, but rather illustrate them schematically. CONAES has employed three different kinds of scenarios, each designed to answer different kinds of questions. The Modeling Resource Group (MRG)1 employed econometric models to estimate the consequences of various economic and policy assumptions for total energy consumption. These are equilibrium models in which prices are determined endogenously through the interaction of supply and demand schedules for energy resources (using optimization techniques that simulate a competitive market). The MRG investigated the effect on GNP of various policies and levels of energy consumption, modifying supply and demand schedules for such hypothetical possibilities as high or low discovery rates for resources and Btu taxes (i.e., taxes per Btu of primary energy input). The group used econometric models to compute the total net cost to the economy of limitations on various energy supply technologies (e.g., on the expansion of nuclear power, the development of oil shale resources, or the mining of coal). The work of the MRG was largely self-contained, as reported in detail in their report, and has not been used in the other models, although some comparisons between the MRG results and those of the other models are presented in this chapter. The Demand and Conservation Panel focused on the demand for net energy delivered to the point of consumption (final demand), separated by different energy forms (i.e., electricity, gaseous fuels, liquid fuels, and coal). In the Demand and Conservation Panel’s models, energy prices are exogenous and are assumed to increase at various rates between 1975 and
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Energy in Transition, 1985-2010: Final Report of the Committee on Nuclear and Alternative Energy Systems 2010. The effects of prices on the final demand for each energy form were estimated by a combination of econometric and technological models, as explained in greater detail below. Different technological models were used for each end-use sector (buildings, transportation, and industry). Specifically, the optimum design for energy-consuming equipment was chosen for each price scenario in such a way that the discounted lifetime cost of each piece of equipment is minimized over time for that particular price assumption, taking into account the normal replacement rate for the equipment, Little or no technological innovation was assumed, other than the application of well-known engineering principles. Having obtained a set of final energy demands for each form of energy, the Demand and Conservation Panel then estimated the primary fuel requirement needed for conversion to the final fuel form, taking into account conversion efficiency and transportation or transmission losses, as well as processing losses. In the case of synthetic liquids and gases derived from coal, the partition between natural and synthetic fuels was estimated crudely on the basis of judgments by industry consultants about the availability of the synthetics technologies. Initial estimates were corrected in a second iteration by negotiation between the Demand and Conservation Panel and the Supply and Delivery Panel. It had been hoped that the Supply and Delivery Panel would be able to generate supply curves for each primary fuel, i.e., curves of available supply as a function of price and time. This did not prove feasible. In the opinion of the panel, the political climate for energy resource development is a more influential factor than price in determining investment in energy exploration and development and, thus, future supplies. Price was included in the definition of political climate, but was not the most important factor. The Supply and Delivery Panel expressed the opinion that the energy required for any of the Demand and Conservation Panel’s scenarios could be produced for little more than twice the 1975 OPEC price (measured in 1975 dollars), and that much higher prices than this to producers would not bring forth large additional domestic supplies. Not all experts would agree to this assumption. For example, some believe that large unconventional natural gas supplies would be forthcoming at sufficiently high prices.2 The Supply and Delivery Panel projected three different “climate” scenarios: business as usual, enhanced supply, and national commitment The scenario for each primary energy source was defined somewhat differently, according to the source’s characteristics. For each scenario, the panel estimated the amount of each form of primary energy likely to be produced in 1990 and in 2010 under the corresponding assumptions. The next step for CONAES was to try to match the Supply and Delivery Panel’s supply projections with the Demand and Conservation Panel’s
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Energy in Transition, 1985-2010: Final Report of the Committee on Nuclear and Alternative Energy Systems TABLE 11–1 Scenario Projections Used in the CONAES Study Scenario Source Description Demand scenariosa: A*, A, B, B′, C, D Demand and Conservation Panelb A, B, C, and D explore the effects of varied schedules of prices for energy at the point of use, from an average quadrupling between 1975 and 2010 (scenario A) to a case (scenario D) in which the average price of energy falls to two thirds of its 1975 value by 2010. Basic assumptions include 2 percent annual average growth in GNP, and population growth to 280 million in the United States in 2010. Scenario A* is a variant of A that takes additional conservation measures into account. Scenario B′ is a variant of B, projecting the effect on energy consumption of a higher annual average rate of growth in GNP (3 percent). Supply scenarios: Business as usual, enhanced supply, and national commitment Supply and Delivery Panelc Projections of energy resource and power production under various sets of assumed policy and regulatory conditions. Business-as-usual projections assume continuation without change of the policies and regulations prevailing in 1975; enhanced-supply and national-commitment projections assume policies and regulatory practices to encourage energy resource and power production. Study scenarios: I2, I3, II2, II3, III2, III3, IV2, IV3 (correspondence between study scenarios and demand scenarios: I2=A*, II2=A, III2=B, III3=B′, IV2=C; scenario D was not used) Staff of the CONAES study Based on the demand scenarios; integrations of the projections of demand from the demand scenarios and projections of supply from the supply scenarios. A variant of each price-schedule scenario was projected for 3 percent annual average growth of GNP. MRG scenarios Modeling Resourced Group Estimates of the economic costs of limiting or proscribing energy technologies in accordance with various policies.
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Energy in Transition, 1985-2010: Final Report of the Committee on Nuclear and Alternative Energy Systems estimated requirements for final energy. This was accomplished by carrying forward the process initiated by these two panels (and consulting with them as necessary): starting with the scenarios of demand (and a variant for each at 3 percent annual average growth of GNP), estimating the mix of primary fuels likely to meet those requirements (taking into account conversion and transmission losses), then readjusting the requirements to bring the assumed supply policies into line with the political climate likely to accompany the corresponding scenario of demand. For example, the prices and policies leading to projections of greatly moderated demand for energy would most likely correspond to policies that constitute business as usual for supply. The assumptions leading to higher projections of demand would most likely correspond to the conditions for enhanced supply. Thus, the demand called for by a scenario of low energy consumption was initially matched with a business-as-usual supply scenario. If this did not provide enough energy to meet demand, the enhanced-supply scenario was tried. For the scenarios of high energy consumption, some national-commitment supply scenarios were permitted. The study scenarios do not employ exactly the same fuel mixes as the Demand and Conservation Panel’s scenarios to fill the required end-use demands. This results in slightly different primary energy requirements because of the differences in assumed energy-conversion efficiencies. Small differences, usually not more than 10 percent, may be observed between the primary energy inputs (total energy consumption) in the study scenarios and the scenarios computed by the Demand and Conservation Panel. In the following sections, we describe the assumptions and methods of the Demand and Conservation Panel and the Supply and Delivery Panel, and we present the comparisons of supply and demand incorporated in the study scenarios. This is followed by a separate discussion of the scenarios of the MRG and by a comparison of the results of the MRG with the study aScenario D, a projection of energy consumption in 2010 at prices averaging two-thirds the 1975 prices for energy at the point of consumption, is not taken up in this chapter. bSource: National Research Council, Alternative Energy Demand Futures to 2010, Committee on Nuclear and Alternative Energy Systems, Demand and Conservation Panel (Washington, D.C.: National Academy of Sciences, 1979). cSource: National Research Council, U.S. Energy Supply Prospects to 2010, Committee on Nuclear and Alternative Energy Systems, Supply and Delivery Panel (Washington, D.C.: National Academy of Sciences, 1979). dSource: National Research Council, Supporting Paper 2: Energy Modeling for an Uncertain Future, Committee on Nuclear and Alternative Energy Systems, Synthesis Panel, Modeling Resource Group (Washington, D.C.: National Academy of Sciences, 1978).
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Energy in Transition, 1985-2010: Final Report of the Committee on Nuclear and Alternative Energy Systems scenarios. Table 11–1 summarizes the scenarios discussed in this chapter for ready reference. ANALYSIS AND SCENARIOS WORK OF THE DEMAND AND CONSERVATION PANEL3 The work of the Demand and Conservation Panel relied primarily on assessments of the technological possibilities for moderating the consumption of energy in the transportation, buildings, and industrial sectors of the economy. The panel projected the extent to which these technological possibilities might be realized under various assumed sets of prices for energy at the point of use. An integrating model for the economy in the year 2010 was used to adjust these sectoral figures for consistency with one another and with final demand. The levels of energy consumption projected by the panel for 2010 range from about half today’s per capita consumption to levels twice as high. In projecting the consumption of energy over the next three decades, the panel chose to fix some demand-shaping variables and to allow others to vary. It was most interested in the effects of changing prices for energy and various policies that would stimulate or discourage energy-conserving practices. Accordingly, the panel fixed the growth rate of GNP (experimenting, however, with a variant), population, and work-force participation, and its scenarios of energy consumption were determined by response to four sets of energy prices. The panel assumed that the decisions of consumers (both industrial and commercial) on the purchase of energyconsuming equipment would be economically rational for each assumed set of prices, and that consumers would seek to minimize the total lifetime cost of such equipment. Policy variables were also simulated in two additional scenarios to test the effects of vigorous conservation accompanied by some voluntary changes in patterns of living, working, and buying (in one case), and a higher rate of economic growth (in the other). Population Growth The panel assumed the Series II projection of population growth by the Bureau of the Census in all scenarios. This projection assumes a reversal of the downward trend in fertility (Figure 11–1), resulting in a population of 279 million people in the United States in 2010. The Series III projection, assuming a continued downward trend in fertility, gives a population of 250 million people in 2010. If the Series III projection were realized, the panel estimates that total energy consumption in 2010 would be lower by
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Energy in Transition, 1985-2010: Final Report of the Committee on Nuclear and Alternative Energy Systems about 10 percent in all the scenarios. (Series I, II, and III projections by the Bureau of the Census are pictured in Figure 11–2.) Any assumption of future population growth must be considered arbitrary. The panel points out that the effects of illegal immigration can only be guessed, although they could well be the most significant source of demographic uncertainty. Work-Force Participation and Other Trends The panel assumed that the work force in the United States would grow in the direction indicated by prevailing trends: at a lower rate in the future than in the past, and in accordance with recently declining fertility rates and the consequent size of younger-age cohorts, which govern the rate of growth of the labor force. The panel also assumed that the participation of women in the work force would continue to grow. The trend toward shorter working days and fewer working days per year was presumed to extend into the future at about the same rate as in the recent past. Growth of GNP Gross national product was used in this study as a measure of economic activity, and in an extended (if not wholly satisfactory) sense as an indicator of national well-being, Over the 30-yr period from 1945 to 1975, GNP grew at an average annual rate of 2.7 percent.* The rate of increase from year to year varied (from 1950 to 1970, the average annual rate was 3.5 percent). The panel assumed that over the next 30 years, the growth of GNP would be rapid in the near term, owing in part to recovery from the 1974 recession and in part to the rapid growth of the labor force in the 1970s stemming from the postwar baby boom. Beginning in the mid-1980s, growth would slow with declining additions to the labor force. The panel selected an average annual growth rate for GNP of 2 percent over the next 30 years.† At this rate, GNP approximately doubles by 2010. One scenario was projected for an annual average growth rate of 3 percent, resulting in a near tripling of GNP (2.8 times the 1975 total) by 2010 (scenario B′). Figure 11–3 * Statement 11–1, by R.H.Cannon, Jr.: Over the entire 33-yr period 1946 to present, GNP has followed a 3.4 percent growth curve remarkably closely. During the war years 1940–1945, it was much higher. † Statement 11–2, by R.H.Cannon, Jr.: Since World War II, GNP has followed a 3.4 percent growth line remarkably closely. Using 2 percent predestines dangerously low energy demand projections.
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Energy in Transition, 1985-2010: Final Report of the Committee on Nuclear and Alternative Energy Systems FIGURE 11–1 Total estimated fertility rates in the United States from 1800 to 1976. Source: U.S. Department of Commerce, Bureau of the Census, Estimates of the Population of the United States and Components of Change: 1940–1976, Population Estimates and Projections Series P-25, No. 706 (Washington, D.C.: U.S. Government Printing Office, 1977). illustrates the two paths, which are approximately linear rather than exponential,‡ and the inset shows the corresponding compound growth rates used by the panel for the subperiods from 1975 to 2010. The rate of economic growth selected by the panel prompted discussion within the committee and among other participants in the study. Most of the economists express reservations about its likelihood, feeling that a 2 percent average rate of growth would not be consistent with the assumption of full employment. Others point to recent trends of declining growth in productivity and suggest that the growing investment in environmental protection and related areas of health and safety, as well as the shift of employment from the manufacturing to the service sector, will continue to reinforce the trend of declining growth in productivity. ‡ Statement 11–3, R.H.Cannon, Jr.: Constant growth-rate curves on this (linear) plot are concave upward. Continuing the rate we’ve had since 1946 leads to a $5,200 billion GNP in 2010.
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Energy in Transition, 1985-2010: Final Report of the Committee on Nuclear and Alternative Energy Systems FIGURE 11–2 Estimates and projections of the total population of the United States from 1950 to 2010, showing Bureau of the Census alternative projections from 1975. Source: Adapted from U.S. Department of Commerce, Bureau of the Census, Estimates of the Population of the United States and Components of Change: 1940–1976. Population Estimates and Projections Series P-25, No. 706 (Washington, D.C.: U.S. Government Printing Office, 1977). The Modeling Resource Group used an average annual rate of growth for GNP of 3.2 percent/yr as their base case, but also showed an alternative low value, corresponding to an average of about 2 percent a year, with even greater deceleration. D/C Panel MRG-Low 1975–1980 2.7 3.7 1980–1990 2.3 2.7 1990–2000 1.8 1.2 2000–2010 1.6 0.5 The Modeling Resource Group generated its high, low, and base-case projections for the growth of GNP by projecting the changes that might be expected in three determinants of potential GNP over the period 1975–2010. Those leading to the lower rate of growth are the following. Work-force participation declining from 0.73 (its average value from 1950 to 1975) to 0.70 in 2010. Unemployment averaging 6 percent.
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Energy in Transition, 1985-2010: Final Report of the Committee on Nuclear and Alternative Energy Systems FIGURE 11–3 Past and projected GNP growth in the United States from 1940 to 2010 (billions of 1975 dollars). Source: Adapted from National Research Council, Alternative Energy Demand Futures to 2010, Committee on Nuclear and Alternative Energy Systems, Demand and Conservation Panel (Washington, D.C.: National Academy of Sciences, 1979), p. 60. Growth in productivity shrinking from 1.57 percent per annum in 1975 to zero by 2010. Growth rate of the potential labor force and immigration slowing to 0.2 percent a year after 2010. Other studies examining the relation of energy consumption and the domestic economy have projected different rates of growth for GNP. The
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Energy in Transition, 1985-2010: Final Report of the Committee on Nuclear and Alternative Energy Systems Energy Policy Project of the Ford Foundation,4 for example, projected three scenarios to the year 2000 (in 1974). In that study, the zero-energy-growth and technical-fix scenarios assumed that GNP would rise at a rate of 3.5 percent/yr from 1975 to 1985, and at a rate of 3.1 percent/yr from 1985 to 2000. The historical-growth scenario assumed that GNP would rise at a rate of 3.6 percent/yr over the first 10-yr period, and at a rate of 3.3 percent/yr from 1985 to 2000. Exxon Corporation5 assumed that GNP would grow over the 4-yr period from 1976 to 1980 at an annual rate of 4.2 percent, and from 1980 to 1990 at an annual rate of 3.4 percent, but warns, “A reasonable range of error in estimating long-term economic growth might be perhaps ±0.5 percent per year.” The Edison Electric Institute6 set out three patterns of economic growth to the year 2010—high, moderate, and low. The high-growth case has GNP rising by 4.2 percent/yr; the moderate case, by 3.5–3.7 percent/yr; and the low case, by 2.3 percent/yr. The institute considers the moderate case to be the most likely. (Table 11–34 gives the annual average GNP growth rates projected by CONAES and other energy studies.) CONAES did not attempt to select a “best” growth rate, but rather estimated the growth of energy consumption for both 2 percent and 3 percent growth rates in GNP from 1975 to 2010. It is important to recognize that several other estimates are higher than this range and would lead to higher energy consumption for a given set of price assumptions. The scenarios of the Demand and Conservation Panel cannot be regarded as bracketing all the possibilities. Energy Prices As recapitulated below, the demand scenarios (presented in chapter 2) assume energy prices held constant (scenario C), doubled (B and B′), or quadrupled (A and A*) by 2010. These are average prices of net delivered energy. The panel assumed specific prices for each source of energy by 2010, displayed in Table 11–2, under the categories of these average prices. The relative prices given in Table 11–2 were intended to reflect approximate parity in dollars per million Btu, with adjustments for the relative cleanliness, convenience, and thermodynamic qualities of fuel. Natural gas is thus priced above distillates, and coal below petroleum. Deregulation of prices was assumed in these projections. Unless otherwise specified, the panel’s overall assumption was that demand would be met at these prices. (Scenarios A* and A, for example, specify a prohibition against the use of natural gas for industrial boilers.) The assumed prices listed in Table 11–2 for the year 2010 represent those seen by consumers at the final stage of end-use, expressed in 1975 dollars. The relative increase is the same for all consumers, industrial and
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Energy in Transition, 1985-2010: Final Report of the Committee on Nuclear and Alternative Energy Systems substitution of capital for energy is 0.3, then a 50 percent reduction in energy inputs would lower GNP just 4 percent* if the capital input fraction is held constant, but would lower GNP 11 percent if capital is allowed to adjust to maintain a constant rate of return. The greater the reduction postulated, the greater the difference in effect on GNP between the two assumptions, as illustrated in Figure 11–11.34 The critical parameter that describes the quantitative effect of all energy-saving substitutions taken together, and thereby determines the feedback from energy use to GNP, is the long-term price elasticity of demand for energy. In a complete model, a matrix of price elasticities would be used to express the change in aggregate demand for each fuel in terms of the price change for each fuel. In most of the work presented here, however, this complex of effects was represented by a single price elasticity representing the ratio of the percentage change in aggregate demand for all (price-weighted) forms of primary energy to the percentage change in the average (consumption-weighted) price of primary energy. The test of the validity of this gross price elasticity would be how well the simple aggregate model, with a single primary energy, can be made to simulate the behavior of a more complex model with many fuels and many economic sectors. Estimates of the Feedback from Energy Consumption to Real Income Three of the models employed by the Modeling Resource Group (DESOM, ETA, and Nordhaus) minimize the discounted economic cost of meeting a set of demands for energy over a long period (subject to technological constraints and a limited range of consumer and producer behavior). In the DESOM model, the path of demand for energy is given a priori (the aggregate price elasticity of demand for primary energy is zero). In the ETA and Nordhaus models, the path of demand is obtained by maximizing the discounted sum of economic benefits to the consumer and subtracting the discounted sum of costs incurred by the producer. The optimization features of these three models enabled the MRG to estimate the economic costs (excluding those of research and development) of limiting or proscribing energy technologies in accordance with various policies. The results are displayed in Table 11–36. Scenarios 2–6 represent alternative policies that restrict the amount of energy supplied to the economy of the United States by limiting the use of one or two energy technologies. For DESOM, the scenario entries represent the increase (over the base case) in the minimal discounted sum of year-by- * Statement 11–6, by R.H.Cannon, Jr.: Or $176 billion. Our current costs for foreign oil, for example, are about one fourth of this and are driving a harrowing inflation.
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Energy in Transition, 1985-2010: Final Report of the Committee on Nuclear and Alternative Energy Systems FIGURE 11–11 Effect on the economy of energy scarcity in 2010, under two alternative assumptions about capital. Source: Energy Modeling Forum, Energy and the Economy (Stanford, Calif.: Stanford University, Institute for Energy Studies, September 1977), p. 16. year, constant-dollar costs to achieve the a priori path of demand for energy under each policy alternative. For ETA and Nordhaus, the scenario entries represent the decrease (below the base case) in the maximal discounted sum of year-by-year benefits minus costs of the paths of energy consumption in an open, competitive energy market (simulated by the same maximization). These costs (DESOM) or losses of benefits minus costs (ETA and Nordhaus) cut into the real income that might be spent for nonenergy goods and services. The Modeling Resource Group assumed that the long-term effects of gradual and foreseeable restrictions on the supply of energy could be estimated if the percentage of total capital and labor put to work is independent of energy supply restrictions. Under that assumption. Table 11–36 can be read as discounted sums of precisely the year-by-year implications for real income of restricted energy supplies (without crediting the gains for the environment or public health). Figure 11–12 depicts the results for the ETA and Nordhaus models. The ratio set out on
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Energy in Transition, 1985-2010: Final Report of the Committee on Nuclear and Alternative Energy Systems TABLE 11–36 Estimated Differences in Net Economic Benefits from Six Technology Mixes and Net Economic Costs of Five Alternative Policies to Reduce Environmental Impacts (billions of 1975 dollars) Policy Alternatives Shortfall Below Base Case of Benefits Minus Costsa DESOMb (Costs Only) ETAb Nordhausb 1. Base case (0) 0 0 2. Moratorium on all advanced converters and fast breeder reactorc (43) 8 2 3. Moratorium on all nuclear technologies (105) 46 136 4. Coal and shale limits (914) 159 64 5. Moratorium on all advanced converters and fast breeder reactor, and coal and shale limits (1012) 181 72 6. Nuclear moratorium and coal and shale limits (2325) 358 457 aIn all policy scenarios, total benefits and costs are the sums of year-by-year benefits and costs, discounted to 1975 at 6 percent per annum. DESOM computes only discounted costs, through 2025, ETA computes discounted benefits and costs through 2050, and Nordhaus computes them through 2060. For each year, benefits estimate the value to the consumer of total amounts of energy consumed, on an incremental basis. For further explanations, see National Research Council, Supporting Paper 2: Energy Modeling for an Uncertain Future, Committee on Nuclear and Alternative Energy Systems, Synthesis Panel, Modeling Resource Group (Washington, D.C.: National Academy of Sciences, 1978), sect. III.8. bThe main features of the models used are described in the caption for Figure 11–10. cFor ETA and SRI, this policy includes a moratorium on light water reactors with plutonium recycle; for the other models it does not. the horizontal axis is the “total energy consumption (in primary energy equivalents) for 2010 projected by scenario” to the “total energy consumption (in primary energy equivalents) for 2010 projected by the base case.” The ratio on the vertical axis is the “discounted sum of year-by-year levels of GNP minus the discounted sum of year-by-year losses in income given by scenario to the discounted sum of year-by-year levels of GNP projected by MRG.” The Modeling Resource Group concluded that the feedback effect from restrictions on energy supplies to GNP is small Apart from two points, the feedback effect is at most 2 percent of GNP, even with energy supplies restricted to 50 percent of their levels in the base case.* There are some differences in this result among the models, and the * See statement 11–7, by R.H.Cannon, Jr., Appendix A.
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Energy in Transition, 1985-2010: Final Report of the Committee on Nuclear and Alternative Energy Systems FIGURE 11–12 Estimates of the long-term feedback from aggregate energy consumption on undiscounted GNP for 2010. Nordhaus points represent policies of successive curtailments of the growth rate of energy use. Y′ on vertical axis is the ratio of undiscounted GNP in 2010 to that for the Modeling Resource Group’s base case. Source: National Research Council, Supporting Paper 2: Energy Modeling for an Uncertain Future, Committee on Nuclear and Alternative Energy Systems, Synthesis Panel, Modeling Resource Group (Washington, D.C.: National Academy of Sciences, 1978), p. 109. Modeling Resource Group concluded that these variations could most adequately be explained by the value each assumes (explicitly or implicitly) for the price elasticity of demand (see Table 11–37).35* Table 11–38 gives the results of assuming a “conservation tax” on energy in the ETA model that holds consumption to a constant level of 70 quads throughout the 1975–2010 period. For the Nordhaus model, as illustrated in Figure 11–12, successively more stringent limits are placed on the growth of energy consumption to achieve zero growth. Optimization determines the fuel mix at any given time in the period. Any reduction in energy consumption that can be brought about without adding to the price reduces the conservation tax necessary to balance supply and demand, but the effects of various nonprice policies cannot be estimated from historical data. It must also be emphasized that the tax proceeds are assumed to be plowed back into the economy. If the tax were imposed, for example, by OPEC, this assumption would be violated to the extent that OPEC revenues were not offset by increased * See statement 11–8, by R.H.Cannon, Jr., Appendix A.
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Energy in Transition, 1985-2010: Final Report of the Committee on Nuclear and Alternative Energy Systems TABLE 11–37 Estimated Price and Income Elasticities of Demand for Aggregate Energy in Three Models Energy Modelsa Elasticity of Demand for Aggregate Energy with Respect to: Price Income DESOM smallb 0.75 ETA (price elasticity, −0.25) −0.25 1 ETA (price elasticity, −0.5) −0.50 1 Nordhaus −0.40c,d 0.90d aThe main features of the models used are described in the caption for Figure 11–10. bSince DESOM does not incorporate energy price responses by end-use consumers, its price elasticity reflects only the adjustment (small in absolute value) of the process mix between primary extraction and end use. cMade comparable to ETA price elasticities. dAverage of elasticities measured at historical 1970–1972 prices and at 2010 prices of the Nordhaus model base-case projection. Source: Adapted from National Research Council, Supporting Paper 2: Energy Modeling for an Uncertain Future, Committee on Nuclear and Alternative Energy Systems, Synthesis Panel, Modeling Resource Group (Washington, D.C.: National Academy of Sciences, 1978), p. 110. imports from the United States, and to this extent, the effect on GNP would be greater—up to the fraction of total GNP that constitutes payments for primary energy, probably not more than 5 percent The MRG results on the size of feedback effects confirm earlier results by other investigators and add further insight into the effect of the price elasticity of demand for energy. The first feedback study based on an econometric model (to the year 2000) was made by Hudson and Jorgenson36 and was presented by the same authors37 in greater detail for the years 1980 and 1985. Using a conservation tax (referred to by the authors as a “Btu tax”), this latter effort calculated that a tax of $0.50 per million Btu in 1980, compressing total energy input by 7.8 percent, decreases GNP by only 0.42 percent, all relative to the no-tax base case. A few differences between the assumptions underlying these estimates and those made in the applications of the ETA and Nordhaus models should be noted. The Hudson-Jorgenson (H-J) model is an equilibrium model covering the entire economy (with four nonenergy sectors and five energy sectors). This aspect of the H-J model allows a more detailed
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Energy in Transition, 1985-2010: Final Report of the Committee on Nuclear and Alternative Energy Systems TABLE 11–38 Estimates of the Long-Term Feedback from Aggregate Energy Consumption on Cumulative Discounted Real Gross National Producta Upper Limits on Growth Rate of Energy Consumption (percent per annum) Implied Conservation Tax in 2010 (1975 dollars per million Btu) Nordhaus ETA Price Elasticity Equal to −0.25 Price Elasticity Equal to −0.50 b b b b b b None 0 1.000 1.000 1.000 1.000 1.000 1.000 1.5 0.34 0.893 0.999 — — — — 1.0 1.02 0.751 0.997 — — — — 0.5 1.98 0.631 0.995 — — — — 0.0 3.19 0.531 0.991 — — Upper bound of 70 quadsc c — — 0.419 0.711 0.419 0.982 aTotal discounted GNP, $35 trillion for Nordhaus, $40.4 trillion for ETA (1975 dollars), calculated over the horizon of the model. bis the ratio of aggregate energy consumption in 2010 in the indicated scenario to that of the base case. is the ratio of cumulative discounted GNP in the indicated scenario to that of the base case. cPrice elasticity, −0.50 only; tax for electricity, 126 mills/kwh; tax for oil and gas, 8.9 dollars per million Btu. Source: Adapted from National Research Council, Supporting Paper 2: Energy Modeling for an Uncertain Future, Committee on Nuclear and Alternative Energy Systems, Synthesis Panel, Modeling Resource Group (Washington, D.C.: National Academy of Sciences, 1978), p. 109.
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Energy in Transition, 1985-2010: Final Report of the Committee on Nuclear and Alternative Energy Systems tracing of the effects on energy-consuming industries of a tax-induced reduction in energy use. In comparing the conservation-tax rates of the H-J, ETA, and Nordhaus models, it should be kept in mind that in the H-J model the tax is levied on the Btu content of energy as it leaves the energy sector for use by other sectors. In the ETA and Nordhaus analyses, the tax is implicitly levied on the use of primary energy or energy equivalent. This can be read as a levy on Btu content at the point of entry into the energy-producing and energy-conversion sectors. The principal difference is that in the Modeling Resource Group’s analyses, the implicit tax on electricity is relatively much higher than in the H-J model owing to the low primary or secondary conversion efficiency of electrical generation. In summary, the Modeling Resource Group considered only two types of policies: restricting the use of one or two energy technologies, and imposing a blanket tax on all forms of energy. It should be emphasized again that a tax on energy as such, whether on primary or ready-to-use forms, is not a suitable device for balancing the economic costs of curtailing energy use against the environmental benefits or other policy gains. Practical tax proposals to accomplish ends such as these would have to be tailored with care. The CONAES study has not investigated this issue. Qualitatively, the results would be similar to those shown for the blanket Btu or conservation tax, but would lead to a different mix of primary energy sources. DISCUSSION One of the puzzles emerging from the models and analyses of this study is the difference in shape of the curves projecting energy consumption over the next three decades. Those of the Demand and Conservation Panel (reflected in the curves of the study scenarios) show a considerable degree of saturation. They rise rapidly in the early part of the period 1975–2000 and level off late in the period. The curves of the Modeling Resource Group tend to be more nearly uniform over the same period. The Demand and Conservation Panel’s results were computed from a model based on prices of net delivered energy, while those of the Modeling Resource Group were computed on the basis of the price elasticity of demand for primary energy. As the price of primary energy rises, it constitutes an increasing proportion of the price of secondary energy. A model that assumes a constant price elasticity of demand for primary energy will correspond to a model in which the price elasticity of demand for secondary energy falls as prices rise. The model of the Demand and Conservation Panel, on the other hand, corresponds to a model that assumes a constant price elasticity of demand for secondary energy. This
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Energy in Transition, 1985-2010: Final Report of the Committee on Nuclear and Alternative Energy Systems implies that the curves of the panel’s projections should bend more than those of the Modeling Resource Group with rising prices, and that the difference between the two will be more marked with greater assumed increases in the total price of energy. It is difficult to make a confident choice between the two price elasticities, particularly as to which yields more realistic results. It is important to note a factor that could make the lower-energy-growth scenarios easier to achieve than implied here. The energy conservation shown in all the scenarios is achievable by the application of known technology or of technological principles that have already been demonstrated. It does not incorporate contributions to energy efficiency from major technological innovation. Given a favorable political and economic climate for innovations in energy efficiency, substantial opportunities exist to develop and market ingenious new energy-conserving technologies. In not allowing for human ingenuity, the scenarios may understate the actual potential for moderating the consumption of energy. The ingenious use of information technologies (including microprocessors) to direct and control energy more selectively is still in its infancy and may have more potential than can now be envisaged. Such a favorable development could offset any shortfall from the conservation estimated in the scenarios, especially if energetically promoted by a combination of aggressive private marketing and highly supportive public policies. NOTES 1. National Research Council, Supporting Paper 2: Energy Modeling for an Uncertain Future, Committee on Nuclear and Alternative Energy Systems, Synthesis Panel, Modeling Resource Group (Washington, D.C.: National Academy of Sciences, 1978). 2. See, for example, American Gas Association, Gas Supply Review 5 (1977); National Research Council, Supporting Paper 4: Geothermal Resources and Technology in the United States, Committee on Nuclear and Alternative Energy Systems, Supply and Delivery Panel, Geothermal Resource Group (Washington, D.C.: National Academy of Sciences, 1979) and Gordon J.MacDonald, The Future of Natural Gas (McLean, Va.: Mitre Corp., 1979). 3. See also chapter 2 of this report, and for a detailed account see National Research Council, Alternative Energy Demand Futures to 2010, Committee on Nuclear and Alternative Energy Systems, Demand and Conservation Panel (Washington, D.C.: National Academy of Sciences, 1979). 4. Ford Foundation, Energy Policy Project, A Time to Choose: America’s Energy Future (Cambridge, Mass.: Ballinger Publishing Co., 1974). 5. Exxon Corporation, “World Energy Outlook,” in Exxon Background Series, Public Affairs Department (New York: Exxon Corporation, April 1978), p. 7. 6. Edison Electric Institute, Economic Growth in the Future, executive summary, Committee on Economic Growth, Pricing and Energy Use (New York: Edison Electric Institute, February 1976), p. 13.
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Energy in Transition, 1985-2010: Final Report of the Committee on Nuclear and Alternative Energy Systems 7. Institute for Energy Studies, Energy and the Economy, Energy Modeling Forum Report no. 1, vols. 1 and 2 (Stanford, Calif.: Stanford University, 1977). 8. Demand and Conservation Panel, op. cit. 9. Ibid., chap. 3. 10. E.Hirst, W.Lin, and J.Cope, An Engineering-Economic Model of Residential Energy Use, (Oak Ridge, Tenn.: Oak Ridge National Laboratory (ORNL/TM-5470), July 1976); and E.Hirst et al., An Improved Engineering-Economic Model of Residential Energy Use, (Oak Ridge, Tenn.: Oak Ridge National Laboratory (ORNL/CON-8), April 1977). 11. Demand and Conservation Panel, op. cit., chap. 3. 12. J.R.Jackson and W.S. Johnson, Commercial Energy Use: A Disaggregation by Fuel, Building Type, and End Use (Oak Ridge, Tenn.: Oak Ridge National Laboratory (ORNL/CON-14), February 1978). 13. J.R.Jackson, S.M.Cohn, J.Cope, and W.S.Johnson, The Commercial Demand for Energy: A Disaggregated Approach (Oak Ridge, Tenn.: Oak Ridge National Laboratory (ORNL/CON-15), April 1978). 14. Demand and Conservation Panel, op. cit., chap. 5. 15. For the sectoral analysis, “mass transportation” was assumed to include school buses, local and intercity buses, subways, and elevated railways. 16. Demand and Conservation Panel, op. cit., chap. 4. 17. Ibid., chap. 6 and app. A; see also C.W.Bullard and R.A.Herendeen, Energy Impact of Consumption Decisions (University of Illinois at Urbana: Center for Advanced Computation (CAC Document no. 135), October 1974), reprinted in Proceedings of the Institute of Electrical and Electronics Engineers 63 (March 1975):484–493. 18. The Department of Commerce issues these data at irregular intervals. 19. Demand and Conservation Panel, op. cit., chap. 6 and app. A. 20. See the report of the Consumption, Location, and Occupational Patterns Resource Group of the Synthesis Panel. 21. National Research Council, U.S. Energy Supply Prospects to 2010, Committee on Nuclear and Alternative Energy Systems, Supply and Delivery Panel (Washington, D.C.: National Academy of Sciences, 1979). 22. Since the work of the Supply and Delivery Panel was mostly done in 1976, “existing policies” generally refer to those of that period. The effects of policy changes since that date (though not expected to be large) are generally favorable to slightly enhanced supplies. 23. The Supply and Delivery Panel did not assess the quantitative trade-offs among supply sources implicit in this warning. 24. National Research Council, Supporting Paper 6: Domestic Potential of Solar and Other Renewable Energy Sources, Committee on Nuclear and Alternative Energy Systems, Supply and Delivery Panel, Solar Resource Group (Washington, D.C.: National Academy of Sciences, 1979). 25. U.S. Department of Energy, Annual Report to Congress, 1978, vol. 3, Energy Information Administration (Washington, D.C.: U.S. Department of Energy, 1979). 26. Conservation Foundation Letter, July 1979, pp. 2–3. 27. The study scenarios were developed by J.M.Hollander and R.Silberglitt. 28. Edison Electric Institute, op. cit. 29. “29th Annual Electrical Industry Forecast,” Electrical World, September 15, 1978, pp. 68–69. 30. The Modeling Resource Group undertook two tasks. The task not described here is a systematic examination of the economic desirability of government-funded research and development of various energy technologies. See Modeling Resource Group, Supporting Paper 2, op. cit.
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Energy in Transition, 1985-2010: Final Report of the Committee on Nuclear and Alternative Energy Systems 31. As defined by the Modeling Resource Group, “nuclear moratorium” is construed as allowing the operation of existing light water reactors and the completion of those under construction. The MRG estimates that this policy would result in no new additional nuclear capacity after 1983, but would permit 70 GWe of nuclear capacity by that year. The nuclear power plants would be retired after about 30 years of operation. 32. See the appendix to chap. 2, “A Word about GNP,” and W.Nordhaus and J.Tobin, “Is Growth Obsolete?” in Economic Growth (New York: Columbia University Press, 1972). 33. Modeling Resource Group, Supporting Paper 2, op. cit. 34. Energy Modeling Forum, Energy and the Economy, Institute for Energy Studies (Stanford, Calif.: Stanford University, September 1977). 35. Demand for aggregate energy, measured in primary energy equivalents. 36. Ford Foundation, op. cit., app. F. 37. “U.S. Energy Policy and Economic Growth, 1975–2000,” The Bell Journal of Economics and Management Science 2 (Autumn 1974):461–514, especially section 6.
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