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Report Contents Report#:EIA/DOE-0607(99)
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[1] See Energy Information Administration, Assumptions to the Annual Energy Outlook 1999, DOE/EIA-0554(99) (Washington, DC, December 1998); Model Documentation Report: Residential Sector Demand Module of the National Energy Modeling System, DOE/EIA-M067(99) (Washington, DC, December 1998); and Model Documentation Report: Commercial Sector Demand Module of the National Energy Modeling System, DOE/EIA-M066(99) (Washington, DC, December 1998). [2] Equipment that is still capable of providing energy services but has operating costs (fuel and maintenance) greater than the annualized capital and operating costs of newer equipment is called “economically obsolete.” The retirement and retrofitting of economically obsolete equipment is simulated in the CDM and adds another dimension to its potential price responsiveness. [3] The RDM simulates insulation upgrades as real energy prices increase. [4] Among the potential reasons for the generally inelastic short-run price responses of energy consumption are (1) the overall importance of energy-consuming end uses to consumers; (2) limited substitutes, particularly in the short run, when the stock of energy-consuming equipment is fixed; (3) expenditures that generally are a small percentage of household income or business expense, with the possible exception of lower income households; and (4) other market conditions—for example, when payments for rented space include some energy services. [5] “Minor” fuel projections for the commercial sector are not affected by short-run price elasticities. The minor fuels include residual oil, kerosene, liquefied petroleum gas (LPG), motor gasoline, coal, and renewable energy. In 1997, the minor fuels accounted for 4 percent of commercial delivered energy. For the residential sector, all fuels include a short-run elasticity. Long-run elasticity effects, generated by price-sensitive equipment choices, occur for electricity, natural gas, and distillate fuel oil in both the residential and commercial sectors and for LPG in the residential sector. Results for the dominant energy sources in the buildings sector—electricity, natural gas, and distillate fuel—are examined in this paper. [6] Equipment that is used only for short periods during the year (e.g., air conditioning in northern climates) will have relatively low energy consumption and thus low energy costs. In such cases, equipment choices will be less influenced by energy prices than they are in areas where equipment is used more heavily. [7] A 5-percent increase in energy prices is assumed to result in a 1-percent increase in the shell efficiency index for existing residential buildings. No downward adjustment for price declines is made to shell efficiency for existing buildings. Insulation, once in place, is not taken out. [8] For the commercial model, the same end uses subject to the short-run price elasticity response are also covered by the efficiency rebound effect. For the residential model, space conditioning is covered by the rebound effect. For discussions of the rebound effect, see J.D. Khazzoom, “Economic Implication of Mandated Efficiency Standards for Household Appliances,” Energy Journal, Vol. 1, No. 4 (1980), pp. 21-40; and J. Henly, H. Ruderman, and M.D. Levine, “Energy Saving Resulting from the Adoption of More Efficient Appliances: A Follow-up,” Energy Journal, Vol. 9, No. 2 (1988), pp 163-170. [9] Elasticities herein are computed using the logarithmic formula given by: elasticity = ln(q1/q0)/ln(p1/p0), where p0 and q0 are base prices and quantities, and p1 and q1 represent an alternative price-quantity combination. “ln” stands for natural logarithm. [10] Fuel price changes can also affect capital purchases for retiring equipment in the first year of a simulated price change; however, no attempt has been made to isolate the capital-induced component for the first year. [11] A 20-year horizon was chosen because NEMS currently runs through 2020 and the initial price increase is imposed in 2000. For equipment such as commercial boilers and residential furnaces, long-run effects could still occur after 2020. [12] Responsiveness is greater in the long run than in the short run, because all the short-run adaptations are available in the long run, in addition to possible responses of altered equipment stocks. [13] Examples of other miscellaneous uses include service station equipment, automated teller machines, telecommunications equipment, medical equipment, and elevators and escalators. [14] This relatively small difference between the short-run and long-run measured elasticities is due to the exogenous nature of the minor end use projections. The usage intensities and the penetration rates for office equipment and other end uses are based on exogenous analyses and factors that are not price sensitive. For example, computer equipment penetrates into commercial office floorspace at a rate independent of prices. In these simulations, office floorspace growth is also not price sensitive. Finally, computer energy intensity is based on projected adoption and enabling rates of Energy Star equipment and other equipment, which are also not price sensitive. Thus, across the two price scenarios, the base forecasts are the same for minor end uses before applying short-run price elasticity effects. Current-year consumption is adjusted for price effects by using the exogenous projection as the base consumption. This contrasts with the procedures for the major end uses, where both the previous year’s base (from which growth occurs) and the current year’s consumption are affected by prices. This causes a compounding effect for major end uses, which is not present for minor end uses. The difference causes the exogenously growing minor end uses to have a somewhat smaller and declining measured elasticity than otherwise. This effect does not occur in the RDM, because usage intensities of penetrating end uses are price sensitive, making the base projections a function of price. [15] For heating and cooling equipment, older residential equipment is relatively less efficient relative to current options than commercial equipment. For example, the installed base efficiency of gas furnaces averages approximately 0.63 in the NEMS model. The efficiency for new furnaces in the residential technology database range from 0.78 high as 0.96. For the commercial sector, boiler efficiencies fall in a tighter range; the installed base is estimated as 0.75 with the range for new boilers from 0.76 to 0.85. [16] The commercial model structure includes segmentation that allows a greater degree of price-induced fuel switching. [17] For illustrative purposes, the elasticity effect can be roughly calculated for aggregate residential consumption using an average elasticity of -0.26 (simple mean of three major residential fuels from Table 1, rounded). The effect is the difference between consumption in the base period (q0) and new consumption (q1). Applying the logarithmic formula, q1 = exp(elasticity*ln(p1/p0) + ln(q0)), where “ln” represents natural logarithm and “exp” is its inverse function. Note that prices affect only about 90 percent of residential energy consumption—minor fuels are modeled without price changes in this simulation. Thus, q0 is approximately 11.3*90% or 10.2. Plugging in values for the residential sector in the year 2000 yields: exp(-0.26*ln(46.6/23.3)+ln(10.2))=8.4. The approximate effect is 10.2-8.5, or 1.7 quadrillion Btu, which is very close to the result computed more precisely using individual fuel data. [18] C. Dahl, A Survey of Energy Demand Elasticities in Support of the Development of the NEMS, Contract Number DE-AP01-93EI23499 (Washington, DC, October 1993). Figure 1. Response to Price-Doubling Sensitivity Cases: Residential Sector Total Delivered Energy Consumption. Source: Energy Information Administration, Office of Integrated Analysis and Forecasting, calculated from the following price path scenarios: Reference Case Price Path, ELAST99.D102298F; Permanent Price-Doubling Case, ELAST99.D102798C; Temporary Price-Doubling Case, ELAST99.D102798D. Figure 2. Response to Price-Doubling Sensitivity Cases: Commercial Sector Total Delivered Energy Consumption. Source: Energy Information Administration, Office of Integrated Analysis and Forecasting, calculated from the following price path scenarios: Reference Case Price Path, ELAST99.D102298F; Permanent Price-Doubling Case, ELAST99.D102798C; Temporary Price-Doubling Case, ELAST99.D102798D. Figure 3. Illustration of Cross-Price Effects: Residential Sector Distillate Fuel Consumption. Source: Energy Information Administration, Office of Integrated Analysis and Forecasting, calculated from the following price path scenarios: Reference Case Price Path, ELAST99.D102298F; Natural Gas Price Increase Case, ELAST99.D110298C; All Fuel Price Increase Case, ELAST99.D110298E; Distillate Fuel Price Increase Case, ELAST99.D110298D. Figure 4. Illustration of Cross-Price Effects: Commercial Sector Distillate Consumption. Source: Energy Information Administration, Office of Integrated Analysis and Forecasting, calculated from the following price path scenarios: Reference Case Price Path, ELAST99.D102298F; Natural Gas Price Increase Case, ELAST99.D110298C; All Fuel Price Increase Case, ELAST99.D110298E; Distillate Fuel Price Increase Case, ELAST99.D110298D. |
