An Examination of Selected Energy Tax Provisions: The Effect on Energy Markets and Carbon Dioxide Emissions

Transcription

1 An Examination of Selected Energy Tax Provisions: The Effect on Energy Markets and Carbon Dioxide Emissions Stephen P. A. Brown, Ryan T. Kennelly and Kylelar Maravich * Center for Business and Economic Research University of Nevada, Las Vegas June 25, 2012 Overview The United States has a variety of tax provisions that affect energy production and consumption. Among these tax provisions are federal gasoline and diesel fuel taxes; taxes on jet fuel; tax credits for alternative energy vehicles; tax advantages extended to master limited partnerships, which primarily affect natural gas collection systems and pipelines; and investment credits for advanced energy manufacturing facilities, which primarily benefits domestic manufacturing of wind and solar energy equipment to produce electricity. We examine the effects of these five tax provisions on energy markets and carbon dioxide (CO 2 ) emissions over a 26 year period from 2010 through To conduct the analysis, we identify how each tax provision affects the supply or demand for various energy sources. We then quantify the effects of each tax provision on U.S. energy market conditions and CO 2 emissions using a comprehensive simulation model of U.S. energy markets. The model represents the end use consumption of oil, natural gas, coal and electricity in four sectors (residential, commercial, industrial and transportation); the primary energy production of a number of different sources of energy; and the * Stephen Brown is a professor of economics, Ryan Kennelly is an economic analyst and Kylelar Maravich is a graduate assistant, all at the University of Nevada, Las Vegas. Funding for this project was provided by the National Academy of Sciences through the Center for Business and Economic Research at the University of Nevada, Las Vegas. The authors thank Maura Allaire, Adnan Aslam and Paul Beaton for providing helpful information.

2 2 transformation of primary energy into electricity. The model primarily represents U.S. energy markets, but it also captures interaction with world energy markets as appropriate. The model allows us to determine how each of the five tax provisions affects energymarket prices and quantities. The changes in market quantities are the basis for calculating how the tax provision affects CO 2 emissions. We find that each of the five tax provisions we consider reduces CO 2 emissions, but the amount varies considerably.

3 3 1. Introduction The United States has a variety of tax provisions that affect energy production and consumption. Allaire and Brown (2011) examined how U.S. energy subsidies affect energy markets and CO 2 emissions. They left unexamined a variety of other tax provisions that are not considered direct subsidies to energy production or consumption. Among these tax provisions are federal gasoline and diesel fuel taxes; taxes on jet fuel; tax credits for alternative energy vehicles; tax advantages extended to master limited partnerships, which primarily affect natural gas collection systems and pipelines; and investment credits for advanced energy manufacturing facilities, which primarily benefits domestic manufacturing of wind and solar energy equipment to produce electricity. We examine the effects of these five tax provisions on energy markets and CO 2 emissions over a 26 year period from 2010 through We identify how each tax provision affects the supply or demand for various energy sources. We then quantify the effects of each tax provision on U.S. energy market conditions and CO 2 emissions using a comprehensive simulation model of U.S. energy markets. The model we use represents the end use consumption of oil, natural gas, coal and electricity in four sectors (residential, commercial, industrial and transportation); the primary energy production of a number of different sources of energy; and the transformation of primary energy into electricity. The model primarily represents U.S. energy markets, but it also captures interaction with world energy markets as appropriate. Treating current policy as the baseline, we use the simulation model to determine what the energy market prices and quantities would have been in the absence of the tax provision we are evaluating.

4 4 The changes in market quantities are the basis for calculating the changes in CO 2 emissions. For each tax provision, the estimated change in CO 2 emissions is the result of the total effects of changes throughout the U.S. energy market. We find that each of the five tax provisions we consider reduces CO 2 emissions, but the amount varies considerably across the tax provisions. The plan for the remainder of the report is as follows. Section 2 describes the model we used to estimate the impact of each tax provision on U.S. energy markets and CO 2 emissions from 2010 through Section 3 describes how we modeled each tax provision and presents our estimates of how each tax provision affects CO 2 emissions. Section 4 examines some of the issues arising from our approach and estimates. Section 5 offers some concluding observations. 2. The Model To evaluate the various energy tax provisions, we used a comprehensive simulation model of U.S. energy markets adapted from Allaire and Brown (2011). As shown in Figure 1, the model represents end use consumption of oil, natural gas, coal and electricity in four sectors (residential, commercial, industrial and transportation); primary energy production of a number of different sources of energy; and the transformation of primary energy into electricity. The model mostly represents supply and demand relationships in U.S. energy markets, but it also captures interaction with world energy markets as appropriate. The model s coverage generally follows the approach taken by the U.S. Energy Information Administration (EIA) in constructing the National Energy Modeling System (NEMS). The model represents the integrated world oil market with limited detail outside

5 5 the United States. Because natural gas markets are less integrated on a global basis, the model represents interaction with the rest of the world through imports and exports. The limited interaction of the U.S. coal market with the rest of the world is also represented through imports and exports. For electric power, interaction with Canada and Mexico is represented by net imports. We calibrated the model to match EIA s 2012 Annual Energy Outlook Early Release (2012) so that the prevailing or projected U.S. energy market conditions for each year from 2010 through 2035 with all the existing tax provisions in place are considered business as usual. The effects of each tax policy are quantified through a counterfactual exercise that evaluates how the market would have looked in the absence of the particular tax provision being examined. Wanting to evaluate energy markets in two comparative steady states one with the tax provision always in place and the other as though the tax provision never existed we took the approach that both the business as usual cases and the counterfactuals represent complete long run adjustment to two different sets of market conditions. As such, we used long run elasticities of supply and demand in the model. As described in section below, these elasticities were adopted from Allaire and Brown (2011), who consulted a number of sources including Dahl s (2009, 2010a, 2010b, 2010c, 2010d, 2010e) extensive surveys of international energy demand elasticities. Allaire and Brown also developed elasticities through the comparison of various scenarios run with NEMS and NEMS RFF, and used judgment when necessary. 1 1 NEMS RFF is a version of NEMS developed by Resources for the Future in cooperation with OnLocation, Inc.

6 6 For each tax provision, the estimated change in CO 2 emissions is the result of the total effects of changes throughout the U.S. energy market. We sum the change in emissions across all primary fuels represented in the model. For each primary fuel source, we use CO 2 emissions coefficients to quantify the change in emissions. The coefficients for oil, natural gas and coal are from the U.S. Energy Information Administration. The coefficients for biodiesel and ethanol are calculated as adjustments to the coefficients for diesel and gasoline, respectively reflecting differences in life cycle emissions. 2.1 Details of the U.S. Energy Market Simulation Model As is the case with NEMS, the model emphasizes U.S. energy markets, but it also captures the interaction between U.S. and world energy markets with the degree of interaction varying by energy source. The model represents an integrated world oil market with limited detail outside of the United States. Because natural gas markets are less integrated on a global basis, the model represents interaction with the rest of the world through imports and exports. The limited interaction of the U.S. coal market with the rest of the world is also represented through imports and exports. The interaction with Canada and Mexico in the electric power sector is represented by net imports Oil Demand and Supply The model represents the world oil market with sectoral detail for the United States and single supply and demand equations for non U.S. oil supply and demand. Oil use for electricity generation is represented in the electricity sector described below. U.S. oil demand in each end use sector can be represented as follows: Q Doi A oi P oi o P oji j for each U.S. end use sector i; and j = g, c and e (1) j

7 7 where Q Doi represents the quantity of oil demanded in sector i, A oi is a constant, P o is the price of oil, oi is the long run price elasticity of oil demand in sector i, P j is the price of energy source j, and oji is the long run elasticity of demand for oil with respect to the price of energy source j in sector i. The four U.S. end use sectors are residential, commercial, industrial and transportation, and the subscripts o, g, c, and e represent oil, natural gas, coal and electricity, respectively. Non U.S. oil demand is represented as follows: Q Dox A ox P o ox (2) where Q Dox represents the quantity of oil demanded outside the United States, A ox is a constant and ox is the long run price elasticity of oil demand outside the United States. Oil consumption outside the United States is dependent only upon the world oil price not those for other energy sources. U.S. oil supply from each of several domestic sources can be represented as follows: Q Sou B ou P ou o for each domestic source, u (3) where Q Sou represents the quantity of oil supplied from U.S. source u, B ou is a constant, and ou is the long run elasticity of oil supply from source u. 2 Non U.S. oil supply is represented as follows: Q Soy B oy P o oy (4) where Q Soy represents the quantity of oil supplied outside the United States, B oy is a constant, and oy is the long run elasticity of non U.S. oil supply. 2 Consistent with the EIA classification, the term oil includes any liquid fuels that are close substitutes for petroleum products.

8 Natural Gas Demand and Supply The model represents the U.S. natural gas market with sectoral detail and the addition of exports and imports. Natural gas use for electricity generation is represented in the electricity sector described below. U.S. natural gas demand for each end use sector can be represented as follows: Q Dgi A gi P gi g P gji j for each U.S. end use sector i; and j = o, c and e (5) j where Q Dgi represents the quantity of natural gas demanded in sector i, A gi is a constant, P g is the price of natural gas, gi is the long run price elasticity of natural gas demand in sector i, P j is the price of energy source j, and gji is the long run elasticity of demand for natural gas with respect to the price of energy source j in sector i. Demand for natural gas exports from the United States are represented as follows Q Dgx A gx P g gx (6) where Q Dgx represents the quantity of U.S. natural gas exports, A gx is a constant and the long run price elasticity of export demand for U.S. natural gas. Exports are dependent only upon the domestic price of natural gas not other energy prices, domestic or international. U.S. natural gas supply from each of several domestic or imported sources can be represented as follows: Q Sgu B gu P gu g for domestic and imported sources, u (7) where Q Sgu represents the quantity of natural gas supplied to the U.S. market from domestic or imported source u, B gu is a constant, and gu is the long run elasticity of natural gas supply to the U.S. market from source u. gx is

9 Coal Demand and Supply The model represents the U.S. coal market with exports and imports. Coal use for electricity generation is represented in the electricity sector described below. U.S. coal demand for each end use sector can be represented as follows Q Dci A ci P ci c P cji j for each U.S. end use sector i; and j = o, g and e (8) j where Q Dci represents the quantity of coal demanded in sector i, A ci is a constant, P c is the price of coal, ci is the long run price elasticity of coal demand in sector i, P j is the price of energy source j, and cji is the long run elasticity of demand for coal with respect to the price of energy source j in sector i. Demand for coal exports from the United States are represented as follows: Q Dcx A cx P c cx (9) where Q Dcx represents the quantity of U.S. coal exports, A cx is a constant and cx is the longrun price elasticity of export demand for U.S. coal. Exports are dependent only upon the domestic price of coal not other energy prices, domestic or international. U.S. coal supply from each of several domestic or imported sources can be represented as follows: Q Scu B cu P cu c for a variety of domestic and imported sources, u (10) where Q Scu represents the quantity of coal supplied to the U.S. market from either domestic or imported source u, B cu is a constant, and cu is the long run elasticity of coal supply to the U.S. market from source u.

10 Electricity Demand and Supply The model represents the U.S. electricity market with the addition of net imports. The electricity sector also represents additional demand for oil, natural gas and coal, which are used for the production of electricity. U.S. electricity demand for each end use sector can be represented as follows: Q Dei A ei P ei e P eji j for each U.S. end use sector i; and j = o, g and c (11) j where Q egi represents the quantity of electricity demanded in sector i, A ei is a constant, P e is the price of electricity, ei is the long run price elasticity of electricity demand in sector i, P j is the price of energy source j, and eji is the long run elasticity of demand for electricity with respect to the price of energy source j in sector i. U.S. electricity supply from each of several domestic or imported sources can be represented as follows: Q Sej C j (P e /P j ) ej for j = o,g and c (12) Q Sel C l P el e for l = nuclear, hydro, wind, solar, net imports (13) where Q Sej represents the quantity of electricity supplied from fossil energy source j, Q Sel represents the quantity of electricity supplied from source l, C j and C l are constants, P e is the price of electricity, P j is the price of fossil energy source j, ej is the long run elasticity of electricity supply from fuel j, and el is the long run elasticity of electricity supply from source l. In addition, the model represents the consumption of fossil energy to produce electricity as follows: Q Dje K j Q Sej for j = o,g and c (14)

11 11 where Q Dje represents the quantity of energy source j used to produce electricity and K j is a constant expressing the rate at which energy source j is converted to electric power. Thus, the demand for a particular fossil energy source to produce electricity is a function of its conversion rate, the supplies of electric power from other sources, and the overall demand for electricity Energy Market System Equilibrium To bring the energy market system to equilibrium, the model sets four energy market prices P o, P g, P c and P e such that the quantities of oil, natural gas, coal, and electricity demanded equal the quantities supplied in each respective market: Q Doe Q Dox Q Doi Q Soy Q Sou (15) i u Q Dge Q Dgi Q Dgx Q Sgu (16) i u Q Dce Q Dci Q Dcx Q Scu (17) i u Q Dei Q Sej Q Sel i j l (18) where the subscript on the quantities, Q, are defined as follows: D represents the demand, S represents supply, o represents oil, g represents natural gas, c represents coal, e represents electricity, x variously represents either consumption in the rest of the world or exports, i represents a domestic sector (residential, commercial, industrial, transportation or electric power generation) in which energy is used, u represents various sources of a particular form of energy either domestic, imported or globally, j represents various fossil energy

12 12 sources (oil, natural gas and coal) used to produce electricity, and l represents electricity provided through various non fossil sources or net imports Model Elasticities As described above, the model is built with supply and demand functions that rely on elasticities. Wanting to evaluate how the market might have looked had the tax provision not existed, we used the same approach as Allaire and Brown and represented both the business as usual cases and the counterfactuals as complete long run adjustment to two different sets of market conditions. For that reason, we used the long run elasticities of supply and demand developed by Allaire and Brown. To develop these elasticities, Allaire and Brown conducted a review of the economics literature with empirical estimates of the requisite elasticities, consulted Dahl s (2009, 2010a, 2010b, 2010c, 2010d, 2010e) extensive surveys of international energy demand elasticities, investigated various scenarios run with NEMS and NEMS RFF, and used judgment. As shown in Table 1, Serletis et al. (2010) provided a point of departure for residential and commercial demand elasticities. The Serletis et al. estimates of the elasticities of U.S. energy demand by fuel for the residential and commercial sectors with cross elasticities, with the own price elasticities generally conforming to those found in the Dahl surveys. In a number of cases, however, the Serletis et al. estimates of cross elasticities yield results that Allaire and Brown consider improbable. For instance, use of the raw estimated cross elasticities for residential natural gas and electricity consumption with respect to the price of oil (as estimated by Serletis et al.) yielded an increase in total 3 The model assumes no CO 2 emissions are associated with the small amount of U.S. net electricity imports.

13 13 residential energy consumption when the price of oil is increased, because the estimated gains in natural gas and electricity consumption were greater than the estimated decline in petroleum product consumption. As a result, Allaire and Brown adjusted the cross elasticities to eliminate these untoward effects. Following Allaire and Brown, we combined the Serletis et al. estimates for residential and commercial sector demand for petroleum products because the quantity of oil products consumed in these two sectors is relatively small. For the industrial sector, Allaire and Brown relied on modeler judgment, scaling the cross elasticities to yield probable interfuel substitution. For the transportation sector, Allaire and Brown used the Dahl surveys, inferences from runs of NEMS and NEMS RFF and judgment to develop elasticities. For interaction with international energy markets, Allaire and Brown developed elasticities from Dahl or used modeler judgment to yield what seem to be reasonable market responses. Because the economics literature provides no recent empirical estimates of energy supply elasticities, Allaire and Brown relied heavily on inferences from NEMS RFF supplemented by Brown and Huntington (2003) and modeler judgment to develop the elasticities shown in Tables 2 and 3. These estimates include elasticities of primary energy supply as well as those for producing electricity with various energy sources Model Calibration and Use Using EIA s 2012 Annual Energy Outlook Early Release (2012) for reference quantities and prices, we calibrated the model so that the prevailing or projected U.S. energy market conditions for each year from 2010 through 2035 are considered business as usual with all of the existing tax provisions in place. For a given set of elasticities and

14 14 market prices and quantities representing each year from 2010 through 2035, the parameters A, B, C and K are set so that each equation meets the prevailing or projected market conditions in the reference years and each energy market clears under business as usual. The effects of each tax provision are quantified through a counterfactual simulation exercise that assessed how the market would have looked in the absence of the particular tax provision being examined. For each tax provision, we calculate how the provision directly affects a given supply or demand curve for each year from 2010 through 2014, and then use the altered supply or demand curves in the simulation exercise. 2.2 CO 2 Emissions For each tax provision, the change in CO 2 emissions is the result of the total effects of changes throughout the U.S. energy market. n CO 2 Emissions E j Q Dj (19) j1 where E j is the CO 2 emissions associated with one unit of primary fuel j and Q Dj is the quantity of primary fuel j consumed in the United States. For each tax provision, we calculate the differences between the baseline case with the subsidy in place and the case with the subsidy removed for each primary energy source. We sum the change in emissions across all primary fuels represented in the model. For each primary fuel source, we use the relevant CO 2 emissions coefficient shown in Table 4 to quantify the change in emissions. The coefficients for oil, natural gas and coal are from the U.S. Energy Information Administration. The coefficients for biodiesel and ethanol are calculated as adjustments to coefficients for diesel and gasoline, respectively

15 15 reflecting differences in life cycle emissions between biodiesel and diesel and between ethanol and gasoline. In the former case, we used data from EIA to make the adjustment. In the latter case, we followed Allaire and Brown by using data from Tyner et al. (2010) to make the adjustment. 2.3 Modeling the Energy Tax Provisions For each tax provision, we make appropriate changes to the demand or supply curve(s) affected by the tax provision. We then use the simulation model to determine what the energy market prices and quantities would have been in the absence of the tax provision. The changes in market quantities are the basis for calculating the changes in CO 2 emissions. The energy tax provisions we evaluate fall into three broad categories: those changing energy supply, those changing energy demand and those affecting energy efficiency. Such tax provisions can increase or decrease CO 2 emissions. Taxes on energy sources with low CO 2 emissions can result in an overall increase in CO 2 emissions, while taxes on energy sources with high CO 2 emissions can result in an overall reduction in CO 2 emissions. We treat energy efficiency subsidies as stimulating investments that yield a payback in reduced energy consumption Fuel Taxes Although fuel taxes can be thought of as being applied to either producers or consumers, we exploit a principle of economics that subsidies to consumers and producers have equivalent market effects, and model all taxes as a reduction in demand. 4 4 See Gruber (2011).

16 16 Accordingly, we treated the fuel taxes as increasing the price paid by the consumer(s) of the relevant fuel(s) at the market equilibrium. To determine the effect of an individual fuel tax on market prices and quantities and CO 2 emissions, we subtract the per unit tax at the existing market price and quantity and generated a new demand curve for the fuel in question. We then use the altered demand curve in the simulation model to determine what energy market prices and quantities would have prevailed in the absence of the tax. For a tax provision affecting multiple fuels, we made changes to several demand curves before using the model to determine what energy market prices and quantities would have been without the tax Tax Policies Affecting Energy Efficiency and Alternative Energy We modeled tax provisions promoting energy efficiency as a form of an annuity that reduced expenditure on relevant fuels (such as gasoline). Two important issues arise in the examination of subsidies for energy efficiency investments. A substantial percentage of government subsidy payments go to individuals who would have made the investments anyway, and many end users seem to demand unusually high rates of return on their investments. We adopt the approach taken by Allaire and Brown (2011). After consulting a number of the participants in a recent Energy Modeling Forum study on energy efficiency, Allaire and Brown made several adjustments to the annuity calculations to reflect actual decisions rather than estimates of the engineering potential for energy efficiency. 5 First, Allaire and Brown assume that half the government spending has no effect in reducing energy consumption because those end users would have undertaken the investment anyway. Second, Allaire and Brown reflect the idea that 5 See EMF (2011) and McKibbin et al. (2010).

17 17 consumers who actually undertake energy efficiency investments demand short payback periods by calculating the annuity with a discount rate of 18 percent and a projected lifetime of 20 years for buildings and 15 years for appliances. We follow Allaire and Brown by evaluating the investment with a discount rate of 18 percent, but we use projected lifetimes of five years for automobiles and seven years for alternative energy equipment. Using average prices, we then calculate by how much the subsidy reduced the quantity demanded or increased the quantity supplied of relevant energy sources at the prevailing market prices. 6 For investments in energy efficiency that reduce demand, we added the quantity at the prevailing market price and generated a new demand curve for the fuel. For alternative energy equipment that increased supply, we subtracted the quantity supplied at the prevailing market price and generated a new supply curve for the energy source. We then used the altered demand or supply curve in the simulation model to determine what the energy market prices and quantities would have been in the absence of the energy efficiency or alternative energy subsidies. 3. The Estimated Effects of Various Energy Tax Provisions We examine five somewhat unrelated energy tax provisions. These include federal gasoline and diesel fuel taxes; taxes on jet fuel; tax credits for alternative energy vehicles; tax advantages extended to master limited partnerships, which primarily benefit natural gas collection systems and pipelines; and investment credits for advanced energy manufacturing facilities, which primarily benefits domestic manufacturing of wind and solar energy equipment to produce electricity. 6 Because our model is strictly of energy demand and supply, it excludes consideration of a rebound effect in which the gains in energy efficiency create an incentive for expansion of the application in such a way that energy consumption and CO 2 emissions decrease by less than might be initially expected.

18 U.S. Federal Highway Taxes According to the EIA, gasoline for use by motorists is taxed by an average cents per gallon in the United States. Of this amount, cents is federal tax. The remaining cents per gallon consists of state and local taxes. Similarly, the EIA reports that diesel fuel for use by motorists is taxed by an average of cents per gallon in the United States. Of this amount, cents is federal tax. The remaining cents per gallon is state and local taxes. We model the effects of the federal taxes on gasoline and diesel fuel. Recognizing that the baseline case has the taxes in place, the counterfactual case examines the consequence of eliminating federal taxes on gasoline and diesel fuel. This counterfactual case sees an increase in demand for the use of petroleum products in the transportation sector because end users are willing to pay a higher price for gasoline and diesel fuel in the absence of the taxes. As a result of assumed inflation in the 2012 Annual Energy Outlook, the real value of the highway fuel tax declines over time. Because the baseline case uses 2010 prices, in 2010 we apply taxes of 18.4 cents and 24.4 cent for gasoline and diesel, respectively. In 2015, the respective gasoline and diesel taxes decline to cents and cents as measured in 2010 dollars. In 2035, the respective gasoline and diesel taxes are cents and cents as measured in 2010 dollars. Comparing the counterfactual case with the baseline, we find that the federal gasoline and diesel fuel taxes reduce U.S. consumption of petroleum products in the transportation sector. Because the effect of the tax is absorbed across the global oil market, the effect of the tax is to reduce the world oil price by 0.91 percent in As inflation

19 19 erodes the real value of the tax, it has less effect on world oil prices. For the years 2015, 2020, 2025, 2030 and 2035 we see reductions in world oil price of only 0.55 percent, 0.43 percent, 0.35 percent, 0.28 percent and 0.24 percent, respectively The Effects of Federal Highway Taxes on CO 2 Emissions With limited possibilities for interfuel substitution in the transportation sector, and the tax generating a small decline in petroleum prices in other sectors of the economy, we find the substitution of petroleum products for natural gas and coal consumption in other sectors results in a small overall reduction in the use of natural gas and coal. We estimate that the federal highway fuel taxes reduced U.S. CO 2 emissions by million metric tons and world CO 2 emissions by million metric tons in 2010 (Figure 2). The U.S. federal highway fuel taxes reduce world CO 2 emissions by less than those for the United States primarily because the tax pushes oil away from the United States. With only small reductions in production, most of the oil pushed from the United States is consumed in other countries. The effects on non U.S. consumption of coal and natural gas are in the opposite direction, but are much smaller in magnitude. Projections at five year intervals from show U.S. CO 2 emissions reduced by million, million, million, million, and million metric tons, respectively. At the same five year intervals, world CO 2 emissions are reduced by million, million, million, million and million metric tons, respectively. As a point of comparison, the EIA estimates U.S. energy related CO 2 emissions were 5,634 million metric tons in The 2012 Annual Energy Outlook projects U.S. energy

20 20 related CO 2 emissions at 5,434 million, 5,549 million, 5,618 million, 5,695 million and 5,806 million metric tons in 2020, 2025, 2030 and 2035, respectively Revenue Effects of Federal Highway Taxes As the real value of the federal highway fuel tax declines, the estimated revenues generated by the taxes steadily decrease from 2010 to 2035, as measured in constant 2010 dollars. In 2010, the estimated revenue generated by the highway fuel tax was $35.89 billion (Figure 3). 7 Projected revenue decreases to $34.54 billion in 2015, $31.01 billion in 2020, $27.68 billion in 2025, $24.81 billion in 2030, and $22.84 billion in Welfare Effects of Federal Highway Taxes We measure the welfare effects of the federal highway fuel tax using Harberger triangles. Because inflation erodes the effectiveness of federal highway fuel taxes, the welfare costs steadily decline from In 2010, the welfare cost of the federal highway fuel taxes was $ million (Figure 4). In 2015, 2020, 2025, 2030 and 2035 the respective welfare costs are estimated at $ million, $ million, $ million, $ million and $ million. 3.2 Taxes on Jet Fuel The United States applies two different tax rates on jet fuel. The commercial aviation sector pays a federal tax of 4.4 cents per gallon on aviation fuel. The noncommercial aviation sector pays a federal tax of 21.9 cents on jet fuel. We examine the effects of the current tax structure on CO 2 emissions and how increasing the tax for commercial use of jet fuel to the non commercial rate would affect CO 2 emissions. 7 Unless otherwise stated, all reported revenue and costs estimates are in 2010 dollars.

21 Existing Taxes on Jet Fuel We first examine the effects of existing taxes for jet aviation fuel. Recognizing that the baseline case has the taxes in place, the counterfactual case examines the consequence of reducing the federal taxes on jet fuel to zero from their current and projected values of 4.4 cents for commercial aviation and 21.9 cents for non commercial aviation. As a result of assumed inflation in the 2012 Annual Energy Outlook, the real value of the jet fuel tax declines over time. Because the baseline case uses 2010 prices, in 2010 we apply taxes of 4.4 cents and 21.9 cents for commercial and non commercial jet fuel tax, respectively. In 2015, however, the respective commercial and non commercial taxes decline to 4.08 cents and cents, as measured in 2010 dollars. In 2035, the respective commercial and non commercial taxes are 2.77 cents and cents as measured in 2010 dollars. In comparison to the baseline case, the counterfactual case shows an increase in demand for the use of petroleum products in the transportation sector because aviators are willing to pay a higher price for jet fuel in the absence of the tax. Consequently, we find the current aviation tax slightly reduces U.S. demand for petroleum products in the transportation sector. The effect of the tax is distributed across a much larger world oil market, and we find the tax reduces the world oil price by percent in With projected inflation, the tax has less effect on world oil prices over time. For the years 2015, 2020, 2025, 2030 and 2035 we estimate reductions in world price of oil at percent, percent, percent, percent and percent, respectively.

22 The Effects of Jet Fuel Taxes on CO 2 Emissions With limited possibilities for interfuel substitution in aviation, and the tax generating a decline in petroleum prices for other uses, we find the substitution of petroleum products for natural gas and coal consumption in other sectors results in a slight overall reduction in the use of natural gas and coal. We estimate that the jet fuel tax reduced U.S. CO 2 emissions by 3.37 million metric tons and world CO 2 emissions by 1.88 million metric tons in 2010 (Figure 5). Projections for 2015, 2020, 2025, 2030 and 2035 show U.S. CO 2 emissions to be reduced by 2.18 million, 1.88 million, 1.68 million, 1.49 million and 1.33 million metric tons, respectively. For the same five year intervals world CO 2 emissions are reduced by 1.20 million, 1.03 million, 0.91 million, 0.81 million and 0.72 million metric tons, respectively Revenue Effects of Jet Fuel Taxes As the real value of the jet fuel tax declines, the estimated revenues generated by the taxes steadily decrease from 2010 to 2035, as measured in constant 2010 dollars. In 2010, the estimated revenue generated by the jet fuel tax was $ million (Figure 6). Projected revenue decreases to $ million in 2015, $ million in 2020, $ million in 2025, $ million in 2030, and $ million in Welfare Effects of Jet Fuel Taxes We measure the welfare effects of the existing jet fuel tax using Harberger triangles. Because inflation erodes the effectiveness of the jet fuel taxes, the welfare costs steadily decrease from In 2010, the welfare cost of the existing jet fuel taxes was $950 thousand (Figure 7). For 2015, 2020, 2025, 2030 and 2035 the respective welfare costs are

23 23 estimated at $583 thousand, $465 thousand, $387 thousand, $314 thousand and $253 thousand Increasing Taxes on Commercial Jet Fuel We also examine the effects of increasing the tax on commercial jet fuel to the same rate paid by non commercial aviators. This counterfactual case examines the consequence of increasing the federal taxes on commercial jet fuel from 4.4 cents to 21.9 cents. Again, the real value of the tax declines over time. In 2010, the additional tax amounts to 17.5 cents per gallon of jet fuel. By 2015, the additional tax amounts to only cents in 2010 dollars. In 2035, it is only cents. The effect of increasing the tax on commercial jet fuel would be to reduce the demand for petroleum products in the U.S. transportation sector. As the effect of the increased jet fuel tax is absorbed across the global oil market, we can expect reductions in the world price of oil by percent in Each year, the additional tax would have less effect on the world oil price. For the years 2015, 2020, 2025, 2030 and 2035, we see that increasing the tax on commercial jet fuel would reduce the world oil price by percent, percent, percent, percent and percent, respectively The Effects of Increased Jet Fuel Taxes on CO 2 Emissions Raising the tax on commercial jet fuel to the same rate paid by non commercial aviators also would reduce CO 2 emissions. Had these new taxes been in place in 2010, we estimate that U.S. CO 2 emissions would have been 9.30 million metric tons less and world CO 2 emissions would have been 5.20 million metric tons less (Figure 8). Projections for 2015 find increasing the tax on commercial jet fuel to the non commercial rate would reduce U.S. CO 2 emissions by 6.05 million metric tons and world CO 2 emissions by 3.35

24 24 million metric tons. Projections for 2020, 2025, 2030 and 2035 show U.S. CO 2 emissions to be reduced by 5.21 million, 4.64 million, 4.13 million, and 3.69 million metric tons, respectively. For the same five year intervals world CO 2 emissions are reduced by 1.03, 0.91, 0.81, and 0.72 million metric tons Revenue Effects of Increased Jet Fuel Taxes As would be expected, we find real revenues from higher taxes on commercial jet fuel would decline over time. In 2010, the estimated revenue generated by the increased commercial jet fuel tax would have been $3.54 billion, but the revenue estimate for 2015 is $3.36 billion (Figure 9). Projected revenues for 2020, 2025, 2030 and 2035 are $3.13 billion, $2.91 billion, $2.70 billion and $2.51 billion, respectively Welfare Effects of Increased Jet Fuel Taxes We measure the welfare effects of the increasing the commercial jet fuel tax using Harberger triangles. Because inflation would erode the effectiveness of the jet fuel taxes, the welfare costs steadily decrease from In 2010, the welfare cost of an increased commercial jet fuel tax would have been $7.30 million (Figure 10). For 2015, 2020, 2025, 2030 and 2035, the respective welfare costs are estimated at $4.51 million, $3.60 million, $2.99 million, $2.42 million and $1.96 million. 3.3 Tax Credits for Alternative Energy Vehicles As part of the Energy Policy Act of 2005, the United States offered a tax credit for the purchase of alternative energy vehicles. The credit expired at the end of In 2010, $800 million were claimed under the tax credit. In 2011, the figure was $400 million. Because the purchase of an alternative energy vehicle reduces future gasoline consumption, we modeled the tax credit as an investment that reduced expenditure on

25 25 gasoline. Following Allaire and Brown, we assume that half the government spending has no effect in reducing energy consumption because consumers would have purchased the vehicles. We also followed Allaire and Brown by assuming the consumers who actually undertake the energy efficiency investments demand short payback periods by calculating the annuity with a discount rate of 18 percent and a projected lifetime of five years for automobiles. In contrast with the parameters used to represent decision making, we follow Jackson (2001) and assume that automobiles are actually scrapped at annual rates of 6.34 percent from 2010 to 2014, and 6.56 percent from 2015 onward. Using this investment approach with the average price of gasoline at $2.76 for 2010, we estimate the $800 million that the U.S. government spent on these tax credits in 2010 reduced daily gasoline usage by 2,925 barrels in that year. As these vehicles are scrapped, however, the fuel savings from this investment declines in subsequent years. Similarly, with an average price of gasoline at 2011 at $3.43, we find the $400 million that U.S. government spent on these tax credits in 2011 reduced daily gasoline usage by 1,153 barrels in that year. The fuel savings from this investment also declines in future years as the vehicles are scrapped. For 2010, we estimate the policy yielded a decrease in gasoline demand of 2,925 barrels per day. Allowing for some scrapping of vehicles purchased in 2010, we estimate the policy yielded a decrease in gasoline consumption of 3,893 barrels per day in Allowing for continued scrapping of the alternative fuel vehicles, we project daily demand reductions of 2,989, 2,129, 1,516, 1,080 and 769 for 2015, 2020, 2025, 2030 and 2035, respectively.

26 26 Recognizing that the baseline case has the investment tax credit in place, the counterfactual case examines the consequence of increasing U.S. daily gasoline demand for each year from 2010 through This counterfactual case yields an increase in demand for the use of petroleum products in the transportation sector for each year, as consumers would buy more gasoline had they not been induced to purchase alternative fuel vehicles by the tax credit. We find the tax credit for alternative energy vehicles reduces U.S. demand for petroleum products in the transportation sector. Because the effect of the tax credit is absorbed across a large global oil market, the subsidy reduces the world oil price only slightly, by percent in 2010 and in As the alternative fuel vehicles purchased in 2010 and 2011 are scrapped, the effect of the tax credit on world oil prices diminishes. For the years 2015, 2020, 2025, 2030 and 2035, we see reductions in world oil price of only percent, percent, percent, percent and percent, respectively The Effects of Tax Credits for Alternative Fuel Vehicles on CO 2 Emissions With limited possibilities for interfuel in the transportation sector, and the tax credit generating a slight decline in petroleum prices for other uses, we find the substitution of petroleum products for natural gas and coal consumption in other sectors results in a slight overall reduction in the use of natural gas and coal. We estimate that the tax credit reduced U.S. CO 2 emissions by 424 thousand metric tons and world CO 2 emissions by 232 thousand metric tons in 2010 (Figure 11). The respective estimates for 2011 are 571 thousand metric tons and 318 thousand metric tons. Projections for 2015, 2020, 2025, 2030 and 2035 show U.S. CO 2 emissions to be reduced by 435 thousand, 321 thousand, 233

27 27 thousand, 157 thousand and 121 thousand metric tons, respectively. For the same fiveyear intervals world CO 2 emissions are reduced by 240 thousand, 175 thousand, 125 thousand, 82 thousand, and 69 thousand metric tons, respectively Revenue Effects of Tax Credits for Alternative Fuel Vehicles In 2010, the government saw a reduction in tax revenue of $800 million as the result of the tax credit. In 2011, the figure was $400 million. With the credit expired, future revenue losses are not expected Welfare Effects of Tax Credits for Alternative Fuel Vehicles We measure the welfare effects of tax credits for alternative fuel vehicles using Harberger triangles. We model the market distortion (and associated welfare costs) as following the changes in gasoline demand brought about by the alternative fuel vehicles. As the alternative fuel vehicles are scrapped, the demand for gasoline returns to normal and welfare costs steadily decrease. In 2010 and 2011, the welfare cost of the tax credit was $15.0 thousand and 32.4 thousand, respectively (Figure 12). For 2015, 2020, 2025, 2030 and 2035, the respective welfare costs are estimated at $21.3 thousand, $13.6 thousand, $7.5 thousand, $3.5 thousand and $2.1 thousand. 3.4 The Preferential Tax Treatment of Master Limited Partnerships The United States offers preferential tax treatment for master limited partnerships. In the energy sector, master limited partnerships are found throughout the natural gas collection and pipeline industries. They also may develop in shale gas production. The tax advantages of master limited partnerships are similar to those of S Corporations, which Denis and Sarin (2002) find yields a percent increase in share value over C Corporations. Accordingly, we determined that competitive pressures would

28 28 mean that moving natural gas from the wellhead to the city gate through collection and pipeline systems owned by master limited partnerships would reduce the cost of delivering natural gas by 15 percent. Similar reductions would be realized in transporting imported natural gas from its importation port to city gate. Without any reliable information about the actual extent of master limited partnerships in the natural gas industry, we consider two cases: 50 percent penetration of master limited partnerships in natural gas collection and pipelines; and 100 percent penetration of master limited partnerships in natural gas collection and pipelines. We assume no penetration of master limited partnerships into natural gas production although many analysts consider it a future possibility. Recognizing that the baseline case represents a world with master limited partnerships in place, our counterfactual cases examine the consequence of eliminating such partnerships. Accordingly, we model master limited partnerships as increasing natural gas supply. The extent of the effect on natural gas prices depends on the particular counterfactual case Partial Penetration of Master Limited Partnerships With partial (50 percent) penetration of master limited partnerships, the price of natural gas is 1.22 percent lower in Similarly, we find natural gas prices reduced by 1.03 percent, 1.09 percent, 1.03 percent, 0.97 percent and 0.94 percent in 2015, 2020, 2025, 2030 and 2035, respectively. The variation is the result of projected differences between wellhead and delivered prices of natural gas and in the market share of U.S. natural gas imports/exports in the baseline case.

29 29 The increased natural gas supply results in an overall increase in energy consumption and the substitution of natural gas for other energy sources, with coal and some renewables backed out of the electric power sector. Oil consumption is reduced in the industrial, commercial, residential and electric power sectors. A slightly lower oil price generates increased use of oil for transportation. The master limited partnerships also induce the United States to export more (or import less) natural gas. Much of the oil, coal and natural gas resources pushed out of the United States are consumed elsewhere in the world The Effects of Partial Penetration of Master Limited Partnerships on CO 2 Emissions All these effects combine to reduce U.S. CO 2 emissions. We estimate that limited penetration of master limited partnerships reduced U.S. CO 2 emissions by 3.31 million metric tons (Figure 13). Projections for 2015, 2020, 2025, 2030 and 2035 show U.S. CO 2 emissions to be reduced by 2.29 million, 2.18 million, 2.00 million, 2.01 million and 2.11 million metric tons, respectively. The variation in effects is mostly the result of changes in the cost of delivering natural gas found in the baseline case. Although the increased use of natural gas displaces domestic use of oil and coal, it also makes carbon based energy more abundant worldwide. As U.S. energy consumption increased, it becomes somewhat less carbon intensive. In contrast, world energy consumption increases and becomes more carbon intensive. Consequently, estimated CO 2 emissions increase outside the United States. For 2010, we estimate that total world CO 2 emissions are reduced by only 0.75 million metric tons. For 2015, we estimate total world CO 2 emissions are increased by 0.17 million metric tons. For the five year intervals from 2020 to 2035, the respective

30 30 reductions in total world CO 2 emissions are 0.13 million, 0.09 million, 0.32 million and 0.42 million metric tons Revenue Effects of Partial Penetration of Master Limited Partnerships The estimated loss in revenue re sulting from 50 percent penetration of master limited partnerships into the natural gas pipeline business varies with market conditions but generally rises with natural gas prices. In 2010, the estimated revenue loss was $3.12 billion (Figure 14). The projected revenue losses for 2015, 2020, 2025, 2030 and 2035 are $2.38 billion, $2.47 billion, $2.52 billion, $2.59 billion and $2.85 billion, respectively Welfare Effects of Partial Penetration of Master Limited Partnerships The welfare cost of 50 percent penetration of master limited partnerships into the pipeline business also varies with market conditions. In 2010, the estimated welfare cost was $11.36 million (Figure 15). At five year intervals from 2015 to 2035 the respective welfare costs are $6.19 million, $5.39 million, $4.48 million, $4.21 million and $4.01 million Full Penetration of Master Limited Partnerships With full penetration of master limited partnerships, the price of natural gas is 2.45 percent lower in In 2015, 2020, 2025, 2030 and 2035 we find natural gas prices reduced by 2.06 percent, 2.18 percent, 2.06 percent, 1.94 percent and 1.88 percent, respectively. The variation is the result of projected differences between wellhead and delivered prices of natural gas and in the market share of U.S. natural gas imports/exports in the baseline case.

31 The Effects of Full Penetration of Master Limited Partnerships on CO 2 Emissions As we found with 50 percent penetration of master limited partnerships in the natural gas pipeline industry, the increase in natural gas supply increases U.S. energy consumption, but reduces its carbon intensity. Outside the United States, however, energy consumption and carbon intensity are both increased. We estimate that limited penetration of master limited partnerships reduced U.S. CO 2 emissions by 6.63 million metric tons (Figure 16). Projections for 2015, 2020, 2025, 2030 and 2035 show U.S. CO 2 emissions to be reduced by 4.61 million, 4.39 million, 4.02 million, 4.04 million and 4.26 million metric tons, respectively. The variation in effects is mostly the result of changes in the cost of delivering natural gas found in the baseline case. For 2010, we estimate that total world CO 2 emissions are reduced by only 1.52 million metric tons. For 2015, we estimate total world CO 2 emissions are increased by 0.30 million metric tons. For the five year intervals from 2020 to 2035, the respective reductions in total world CO 2 emissions are 0.28 million, 0.19 million, 0.67 million and 0.86 million metric tons Revenue Effects of Full Penetration of Master Limited Partnerships The estimated loss in revenue resulting from 100 percent penetration of master limited partnerships into the natural gas pipeline business is exactly double that for 50 percent penetration. In 2010, the estimated revenue loss was $6.24 billion (Figure 17). The projected revenue losses for 2015, 2020, 2025, 2030 and 2035 are $4.77 billion, $4.93 billion, $5.05 billion, $5.19 billion and $5.70 billion, respectively.

32 Welfare Effects of Full Penetration of Master Limited Partnerships The welfare cost of 100 percent penetration of master limited partnerships into the pipeline business is more than double that of 50 percent penetration. Marginal welfare costs rise as the market distortion is increased. In 2010, the estimated welfare cost was $26.23 million (Figure 18). At five year intervals from 2015 to 2035 the respective welfare costs are $16.49 million, $14.17 million, $10.55 million, $9.56 million and $8.74 million. 3.5 Investment Tax Credits for Advanced Energy Manufacturing Facilities The American Recovery and Reinvestment Act of 2009 offered a 30 percent tax credit for investment in advanced energy property. A total of $2.3 billion was allocated. Investors submitted applications for $10.9 billion in tax credits; $8.1 billion were determined to be eligible; and $2.3 billion of credits were awarded. These credits are claimed as the investments come online. Of the awarded tax credits, $0.5 billion were claimed in 2010, and another $0.4 billion were claimed in Another $0.2 billion, $0.1 billion and $0.1 billion in tax credits are expected to be claimed in 2012, 2013 and 2014, respectively. We modeled the tax credit as an investment that provides renewable electric power. Following Allaire and Brown, we assume that half of the government spending has no effect in providing electricity because the investment would have occurred anyway. We also followed Allaire and Brown by assuming the investors who actually build the electric power generating equipment demand short payback periods by calculating the annuity with a discount rate of 18 percent and a projected lifetime of seven years for advanced energy property. In contrast with the parameters used in decision making, we assume the equipment has a useful life of 15 years and that depreciation is one hoss shay. With the

33 33 idea that claims for tax credits reflect the timing of investment, we assume that the first year of usage occurs in the year for which the tax credit is claimed. The subsidy increases electric power supply from non fossil sources. In 2010, we estimate an increase in electricity supply of 1.02 billion kilowatt hours (kwh). With additional equipment coming online, we see further gains in supply from 2011 through We estimate the subsidy yields a supply increase of 2.73 billion kwh for the years 2014 through After that, we begin to see the equipment retired, and less is added to electricity supply. The increased supply falls to 0.22 billion kwh in After that, the subsidy yields no additional electricity supply. As electricity supply is increased, electricity prices are reduced. We estimate an electricity price reduction of percent in For the five year intervals from 2015 to 2025, the respective reductions in electricity prices are percent, percent and percent. With the equipment retired by 2030, there is no change in electricity prices in 2030 and The Effects of Investment Tax Credits for Advanced Energy Manufacturing Facilities on CO 2 Emissions The net effect of additional electricity is to reduce overall energy prices and increase U.S. and world energy consumption. Less fossil energy is used in the U.S. electric power sector, and a little more is used in other U.S. sectors. Reduced electricity prices dampen the effect of fossil energy shifting into other sectors, and total fossil energy consumption is reduced. The net effect is a reduction in U.S. CO 2 emissions. 8 Ignoring potential redundancy with renewal portfolio standards, we estimate the tax credits for advanced 8 We note, however, that the subsidy may be redundant with renewable portfolio standards and have no effect on energy markets or CO 2 emissions.

34 34 energy manufacturing facilities reduce U.S. CO 2 emissions by 0.57 million, 1.40 million, 1.37 million, and 1.35 million metric tons in 2010, 2015, 2020 and 2025, respectively (Figure 19). Much of the fossil energy that is pushed out of the United States is used elsewhere in the world. The net effect is that total world oil CO 2 emissions are reduced by less than those of the United States. We estimate the U.S. tax credits for advanced energy manufacturing facilities reduce total world CO 2 emissions by 0.48 million, 1.13 million, 1.16 million, and 1.13 million metric tons in 2010, 2015, 2020 and 2025, respectively Revenue Effects of Investment Tax Credits for Advanced Energy Manufacturing Facilities In 2010, the government saw a reduction in tax revenue of $500 million as the result of the tax credit for advanced energy manufacturing facilities. In 2011, the figure was $400 million. With the credit expired, future revenue losses are not expected. Another $200 million, $100 million and $100 million in tax credits are expected to be claimed in 2012, 2013 and 2014, respectively. No further revenue losses are expected Welfare Effects of Investment Tax Credits for Advanced Energy Manufacturing Facilities We measure the welfare effects of tax credits for advanced energy manufacturing facilities using Harberger triangles. We model the distortion in the market (and associated welfare costs) as increasing with the additional supply of electric power provided, and then decreasing as the equipment is retired. For five year intervals from 2010 through 2025, the respective welfare costs are estimated at $44.4 thousand, $303.4 thousand, $283.2 thousand and $272.8 thousand (Figure 20).

35 35 4. Some Issues Arising from the Estimates When considering our estimates, a number of issues arise. One is use of long run analysis. Another is the potential bias that may occur in summing up estimates for individual policies. Another is the overall sensitivity of the estimates to the assumed elasticities. Yet another is the sensitivity of the energy efficiency results to the modeling assumptions. 4.1 Use of Long Run Analysis For long existing tax provisions, the approach of using long run adjustment has the advantage of helping to correct for the mismatch between the timing of the tax provisions and their effects on U.S. energy markets. For instance, through their effects on the capital stock of vehicles, gasoline taxes can affect consumption and CO 2 emissions many years later. Taking a steady state approach, we examine the general effect of energy tax provisions on CO 2 emissions over time although the effects may be realized over a number of years. Our approach of using long run elasticities in estimating the market responses raises a potential issue for relatively new tax policies particularly those promoting energy efficiency in the 2009 economic stimulus package. Can the estimated responses made with long run elasticities represent relatively new programs? Recognizing that the initial shift in demand or supply does not depend on the elasticities and that we are interested in CO 2 emissions, which are related to the quantities of energy consumption, the answer is a qualified yes. For each energy source, the quantity estimates made with long run elasticities will be substantially similar to those made with short run elasticites if the ratio of the short run supply elasticity to the long run supply elasticity is substantially similar to

36 36 the ratio of the short run demand elasticity to the long run demand elasticity. Such conditions generally hold for energy markets. 4.2 Combining Individual Estimates The effects of each tax provision are evaluated by using the model to find the energy market conditions that would have prevailed had that subsidy not existed. The counterfactual for each subsidy is evaluated independently. As such, any totals for combinations of subsidies should be regarded as upper bound estimates. Because the tax programs do not overlap by very much, however, the reported totals are likely to be fairly close to estimates obtained by combining individual tax provisions in a single analysis. 4.3 Sensitivity of the Results to Model Elasticities The estimated results are dependent on the elasticities assumed for the analysis. 9 Had we modeled energy demand as more elastic, tax provisions that increase or decrease CO 2 emissions would have a larger estimated impact. Similarly, had we modeled the supply for those energy sources that produce CO 2 emissions as more elastic, the estimated impact of the tax provisions directly affecting the use of those sources would show a greater impact on CO 2 emissions. On the contrary, had we modeled the supply of energy sources that do not produce CO 2 emissions as more elastic, tax provisions affecting the use of CO 2 producing energy sources would show a smaller impact on CO 2 emissions. 4.4 Sensitivity of the Energy Investment Assumptions Estimates of the potential gains from investment in energy efficiency or alternative energy efficiency found in studies such as McKinsey (2009) and the actual response of market participants seem to be quite divergent. If such investments are seen as an annuity, 9 The scope of the project prevented us from undertaking a formal sensitivity analysis of the elasticities.

37 37 consumers seem to demand extremely short payback periods. The difference between the potential and the practice has variously been attributed to market barriers, uncertainty, consumer behavior, and hidden lifestyle changes. In addition, a substantial portion of government expenditure on subsidies goes to individuals or companies who would have made the investments anyway. Because they were interested in capturing the actual response of consumers to tax policies that provide incentives for investments in energy efficiency rather than engineering potential, Allaire and Brown consulted a number of modelers participating in a recent Energy Modeling Forum study on energy efficiency. After doing so, Allaire and Brown made several adjustments in treating energy efficiency subsidies as annuities. 10 First, they assume that half the government spending has no effect in reducing energy consumption because that investment would have been undertaken anyway. Second, they reflect the idea that consumers who actually make the investments demand short payback periods by calculating the annuity with a discount rate of 18 percent and a projected lifetime of 20 years for buildings and 15 years for appliances. We take a similar approach by using a discount rate of 18 percent and projected lifetimes of five and seven years for automobiles and advanced energy manufacturing facilities, respectively. The estimated effects of the energy investment subsidies are sensitive to the assumptions we made about how market participants likely responded to them. In particular, assuming that only 45 percent of the government spending has no effect on consumer behavior rather than 50 percent would increase the effectiveness of the energy investment programs in reducing CO 2 emissions by almost 10 percent. In contrast, 10 See Energy Modelling Forum (2011) and McKibbin et al. (2010).

38 38 using a higher discount rate, such as 36 percent rather than 18 percent would increase the required energy savings needed to justify the investment, which would imply a greater energy savings and a greater reduction in CO 2 emissions than we estimate. Subsidies for investment in improved energy efficiency are generally thought to reduce CO 2 emissions. In some cases, however, the improved efficiency creates a sufficient incentive for expansion of the application such that the energy savings is not as big as might be initially expected. For instance, an increase in automobile energy efficiency may lead people to drive more and partially offset the gains in energy efficiency. This phenomenon is sometimes called a rebound effect. 11 Because we do not use a behavioral model, we cannot take into account the rebound effect, and must take solace in the Haas and Schipper (1998) finding that the rebound effect is relatively small. Were the actual rebound effect about 15 to 25 percent, the energy savings from energy efficiency subsidies would be reduced by a little less than 15 to 25 percent. The reductions in CO 2 emissions would be correspondingly smaller. 5. Conclusions We have examined five somewhat unrelated energy tax provisions including federal gasoline and diesel fuel taxes; taxes on jet fuel; tax credits for alternative energy vehicles; tax advantages extended to master limited partnerships, which primarily affect natural gas collection systems and pipelines; and investment credits for advanced energy manufacturing facilities, which primarily benefits domestic manufacturing of wind and solar energy equipment to produce electricity. To do so, we used a simulation model that represents U.S. energy markets integrated in global context. The model captures the effects 11 See Greening et al. (2000).

39 39 that the various tax provisions have on energy production, energy consumption and interfuel substitution across various sectors of the U.S. economy With the model, we determined that all five of the tax provisions reduce CO 2 emissions. The tax credits for alternative energy vehicles and advanced energy manufacturing facilities have relatively little effect on energy markets and CO 2 emissions. Gasoline and diesel fuel taxes have sizable effects. The jet fuel tax and the tax advantages of master limited partnerships are moderate in their effects.

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