A review of several models indicates an appropriate price elasticity. The Energy Modeling Forum 13 (EMF 13) reviewed 9 major energy models and reported the implicit aggregate energy price elasticities. In the review of these models, EMF 13 concludes that "The models indicate that energy demand would fall by only 3 to 8% after 20 years with a 25% increase in delivered energy prices" (EMF 13, p. x). The energy price elasticity implicit in these estimates ranges from -0.12 to -0.32. elasticities are lower than those estimated for earlier decades and the EMF view is that energy price elasticities have declined. According to EMF 13 (p. 13), these low price elasticities occur because the marginal costs of energy conservation increase substantially Assuming these modeling analyses are approximately correct, energy consumption has become less responsive to changes in energy prices.

These

However, the low estimated price elasticity does not affect the EIA's projected growth rate of energy use because the EIA projects stable energy prices over the forecast years. The EIA energy projections therefore depend on other factors.

The intercept in the above equation indicates the composite autonomous influence of all non-random variables, other than energy prices and GDP, on energy use. The intercept is likely to be negative, indicating an autonomous decline in such energy use. For instance, with energy prices unchanged, a 2.0 percent growth rate for GDP and a 0.6 income elasticity would predict a 1.2 percent growth rate for energy use. If energy use increases at a rate of only 1.0 percent, the autonomous decline in energy use must be the remainder, or -0.2 percent.

This rate of decline in autonomous energy use (of 0.2%) is not the same as the decline in energy intensity, which is also declining. Autonomous energy use, measured as aggregate Btu of energy, is assumed independent of GDP and energy prices. Energy intensity, measured as the ratio of aggregate energy to GDP, is influenced by GDP trends and by

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energy prices 10 The Energy Modeling Forum notes that declines in energy intensity, unrelated to energy prices, are in the range of -0.6% to -1.0% per year. The income elasticity in the demand equation of 0.6 implies that energy consumption will increase at only 0.6 the rate of growth of GDP. The declines in the energy intensity reported by EMF include the effect of an intercept and an income elasticity less than one.

The autonomous decline in energy use, rising energy prices, and increasing GDP each contribute to explaining the decline in E/GDP. With an income elasticity less than one, economic growth produces a decline in energy intensity. During the historical period, declines in E/GDP were affected by the drastically rising energy prices of the 1970s. If energy prices remain stable during the forecast period, E/GDP would be expected to decline at a lower rate than in the past. The autonomous decline in energy use accounts for part of the decline in energy intensity during both the historical and forecast periods.

This historical behavior and future projections provide a good explanation of carbon emissions. During the historical period, carbor much slower rate (0.6 percent)

issions grew at a an total primary share of nuclear

irket was increas

energy (1.2 percent) because t power in the electric generation r ing. During the forecast period, carbon emissions grow faster (1.2 percent) than pri nary energy consumption because fossil fuels displace nuclear power in the generation market. Energy consumption also affects carbon emissions. An aggregate energy demand equation explains energy use with GDP growth, energy price trends and autonomous declines in energy use. Primary energy prices are projected to remain constant and therefore not to contribute to changes in future energy consumption trends. The projected growth rate in energy consumption of 1.0 percent per year can be explained by the effect of GDP growth of 1.14 percent and an autonomous decline in energy use of -0.14 percent per year." Overall, the growth in carbon emissions

10 In the energy demand Equation (3), the intercept, A, is autonomous energy use, but energy intensity is defined in log form as In E/GDP = In A/GDP + (ẞ1-1)În GDP + B2 InPE/GDP. The equation indicates that energy intensity declines with GDP if B1<1.

11 The effect of GDP growth is estimated as the income elasticity (0.6) times the projected the projected GDP growth rate. The autonomous energy trend of -0.14 off

is positively affected by the increasing use of fossil energy in the generation market; negatively by the assumed continuous decline in energy use, and positively by increasing GDP.

This review of energy and carbon emission trends suggests several factors that bear on climate change policy commitments. First, carbon emissions will likely increase in the future as natural gas and coal displace nuclear power in the market for electricity generation. This Reference Case result shows an increased growth rate of carbon emissions compared

with historical trends. Further, the EIA projection is for electricity to become more carbon intensive even as it obtains an increased share of the residential, commercial and industrial markets. The EIA projects constant prices for primary energy and declining prices for electricity. The effect of the declining electricity prices is to encourage its increased use. Finally, in the EIA Reference Case, real GDP is projected to grow at only 1.9 percent per year, slower than during recent history. Primary energy consumption could increase faster if real GDP increases at a faster rate than projected.

energy demand growth (1.0 percent) with constant energy

jected in the year 2000 minus emissions from fossil plants that are retired after 2000. In the EIA Reference Case, generating capability increases from 781.9 gigawatts (GW) in the year 2000 to 915.8 GW by the year 2015. In this Reference Case, almost all the capacity additions are combined-cycle natural gas plants or diesel turbines. Displacing this fossil fuel with nuclear would result in all new capacity being carbon free instead of carbon producing. Some new capacity will also be required to replace the existing capacity that will be retired. In AEO97 (p. 109), the EIA estimates that 75.8 GW of generating capacity of all types will be retired from the year 2000 to the year 2015. Using EIA data on total capacity and capacity additions by fuel type, about 37.6 GW of nuclear capacity will be retired from 2000 to the year 2015 with the remainder fossil fueled.12

Figure 4 depicts the gradual reduction in carbon emissions by the year 2015 under the reinventing nuclear case. The projected retirement of fossil fuel plants and their replacement by nuclear is insufficient to achieve either of the proposed emission reduction targets. The projected replacement of fossil fuel plants with nuclear units would not put the U.S. on a path that would achieve either potential policy target. The limited effectiveness of this policy option results because the projected retirements of fossil plants from the year 2000 to 2015 are a small share (about 4.3 percent) of the total generating capacity in the year 2000. The EIA projection of a moderate number of fossil fuel plant retirements precludes a significant reduction in carbon emissions from the electricity generation sector without the premature shutdown of other existing plants.

To meet either of the proposed climate change targets in the electricity sector, a substantial amount of generating capacity must be retired earlier than the ELA projections. The premature retirement of existing capital increases the cost of achieving the proposed targets. Retired plants would include old coal plants, but nuclear plants may also be retired prematurely. As already noted, a more expeditious retirement of nuclear units increases the cost and

12 During the forecast period, projected retirements of coal and natural gas plants (including oil) are 13.2 GW and 20.2 GW respectively. Using current ratios of total emissions to capacity by fuel, about 27.6 million metric tons per year would be reduced by retiring the coal plants and 6.2 mmt/year would be reduced by the retiring the natural gas plants for a total of 33.8 mmt/yr.

technical difficulty of achieving any emissions reduction target.

The reinventing nuclear scenario would not be sufficient to attain the policy goals being considered. No orders for nuclear units have not been placed in the last two decades and there are no prospects for orders in the foreseeable future. Furthermore, natural gas plants have low construction costs and they are regarded as highly reliable. Natural gas appears well entrenched as the fuel of choice for the next two decades, at least in the generation sector. An alternative, more realistic, scenario is defined with three assumptions: (1) net additions to generating capacity come from fossil fueled plants, (2) one-half of the retired capacity will be nuclear units and these units will be replaced by fossil fueled capacity, and (3) no carbon free generating technology has a reasonable chance of capturing even a modest share of the market for generating capacity in the next two decades. These three assumptions characterize the EIA Reference Case Forecast

Reinventing nuclear power is not a feasible scenario, but it illustrates some basic realities of attempting to meet potential climate commitments through reduced emissions from the electricity generating sector. To meet even the less stringent of the proposed targets, a large change in the capital stock of generating capacity would be required within two decades. The displacement of existing capacity by new and highly efficient capacity would result in stranded costs. Much of the existing nuclear capacity is already considered as stranded costs. This conclusion is also one of the main results of the Energy Modeling Forum 12, which focused on the costs of reducing global carbon emissions. In summarizing a result from EMF 12, Weyant states: "First, if the emissions target requires moving faster than the natural rate of capital stock turnover and technology development, significant additional adjustment costs are likely to be incurred." (Weyant, 1993, p. 38). Moreover, achieving the proposed targets is more complicated than accelerating the turnover of the capital stock, because there is no feasible 1.on-fossil fuel technology to take the place of such plants. Electricity use would have to be substantially cartailed.

Conclusion: If 100 percent of the gross additions to generating capacity were met by nuclear power - or by any other carbon-free technology - carbon emissions would not decline enough to meet the 1990 emissions level by the year 2015. Almost all pro

jected new capacity is natural gas fueled and there is no reasonable prospect for a carbon free technology to capture a major share of the generation market by the year 2015.

B. Energy Reduction via Higher Prices

Climate change policy could encourage reductions in emissions by increasing the price of energy. Higher energy prices discourage energy use, which in turn would reduce carbon emissions. A modeling exercise that considers an increase in energy prices can, at least in a qualified sense, represent alternative possible policies. For instance, a Btu tax, a carbon tax and tradable permits would each result in an increase in energy prices. The energy demand equation, expressed above as Equation (3), can be used to compute the increase in the price of energy required to reduce energy consumption to a level that will attain a carbon emissions target.

Estimating the required change in energy prices requires some preliminary calculations. The percent change in carbon emissions required to achieve each goal is obtained from Table 1. These estimates are used to infer the required change in total energy consumption. The carbon/energy ratio is projected to rise (see Figure 2) in the forecast period. However, if energy consumption were to decline instead of rise, the C/E ratio may not increase. The C/E ratio is estimated to increase from 15.77 (year 2000) to 16.05 (year 2010 and 2015), which was calculated from an EIA modeling projection where future carbon emissions were reduced to approximately their 1990 level.1 Table 6 depicts the reduction in energy consumption from the base case 2010 or 2015 level necessary to achieve proposed emission reduction levels. Energy price elasticities were obtained from EMF 13 and are estimated to range from -0.12 to 0.32. The change in energy prices necessary to achieve possible carbon emission targets ranges from 76 to over 365 percent. These estimates of high price change follow directly from the assumed price elasticities, but assume no negative feedback to the economy nor a slowing of economic growth. An energy tax of 76 percent corresponds, roughly, to a carbon tax of $133, white is consistent with other

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studies. 14 If the EMF 13 estimates of low price elasticities are applicable, then large increases in the price of energy would be required to achieve the proposed emissions reduction goals.

These energy prices increases indicate what may be required to attain a target level of energy use in the future; but these price increases would not be sufficient to maintain energy consumption at its target level. Economic growth would produce a continuously increasing demand for energy. To stabilize emissions, the use of fossil fuels would have to be stabilized. If this were accomplished by an energy tax, the tax rate would have to increase continuously over time. To achieve a zero growth rate in energy use, the price effects plus the autonomous decline in energy use, would have to offset the income effect.

These energy price increases do not indicate the costs of attaining the potential target. The types of adjustments required to achieve the emissions reductions might require reductions in consumer energy use and also the premature retirement of a large share of the energy using capital stock and the closure of some energy intensive industries. In that case, the costs of an energy price rise would be much larger than the foregone consumer surplus measured from an energy demand equation. These estimated energy price increases also do not convey the distributive impacts on households, sectors and regions. For instance, an energy tax would impose a larger burden on lower and middle income households than on high income groups. Although large increases in energy prices would apparently be required to achieve either of the proposed targets, these price increases by themselves do not convey the type of disruptions and adjustments required in energy related markets.

Conclusion: To achieve the proposed climate change targets, energy prices would have to be increased by at least 76 percent and the energy tax would have to be increased continuously thereafter. Costs would include foregone consumer surplus, the premature retirement of energy using capital and the closure of some energy intensive industries.

13 Energy Information Administration, An Analysis of Carbon Mitigation Cases, A Service Report to the U.S. Environmental Protection Agency, Washington DC, June 3,

14 The carbon tax estimate was calculated by using a world oil price of $20/tonne and noting that a tax of $11.42