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Energy Market and Economic Impacts of S.1766, the Low Carbon Economy Act of 2007 |
1. Background and Scope of the Analysis This service report was prepared by the Energy Information Administration (EIA), in response to an August 1, 2007, request from Senators Bingaman and Specter.1 The Senators asked EIA to estimate the economic impacts of S. 1766, the Low Carbon Economy Act of the 2007, a bill that would regulate emissions of greenhouse gases (GHGs) through an allowance cap-and-trade system.2 Under S. 1766, a cap for covered GHG emissions would be set at approximately 2006 levels in 2020, 1990 levels by 2030, and at least 60 percent below 1990 levels by 2050. Covered sources include carbon dioxide (CO2) from fossil fuels, the fluorinated gases reported by United Nations conventions (hydrofluorocarbons, perfluorocarbons, sulfur hexafluoride), and nitrous oxide from adipic and nitric acid production. Other anthropogenic GHG sources, including other sources of nitrous oxide and emissions of methane, would not be subject to the caps directly, but some reductions could be credited as emissions offsets. S. 1766 requires regulated entities to submit allowances or qualifying domestic offsets that equal their emissions from covered sources. Each allowance represents a metric ton of CO2-equivalent emissions. The allowance requirements for coal apply directly to large coal-consuming facilities, while other emissions are regulated on an “upstream” basis to reduce administrative costs. The upstream regulated entities include petroleum refiners, natural gas processors, importers of refined oil products and natural gas, and producers and importers of non-CO2 GHGs. Energy-related allowance requirements are based on the CO2 released, assuming complete combustion of the fuels supplied, and the bill provides offset credits to reimburse nonfuel uses that sequester the carbon, sequestration through carbon capture and storage (CCS), and exports. Offset credits are also provided for projects that reduce non-covered GHG emissions, such as methane captured at landfills and coal mines. While there are incentives to encourage agricultural carbon sequestration, it does not count as an offset. Initially, about three-fourths of the emissions allowances are distributed for free to covered entities, carbon-intensive manufacturing industries, State governments, and as incentives for agricultural carbon sequestration, CCS, and early actions. The remaining allowances are auctioned, with the auction share growing over time. Of the shares auctioned, half are auctioned in the issue year and half are auctioned 4 years in advance.3 Allowances are tradable and may be banked for future use if not used in the year for which they were issued. Proceeds of the auction are allocated for technology programs, climate adaptation programs, and low-income assistance. To control compliance costs, regulated entities may meet any portion of their allowance obligation with a “Technology Accelerator Payment” (TAP). The TAP price would effectively provide a ceiling on the price of allowances.4 The TAP price is set at $12 per metric ton of CO2 equivalent in 2012 and grows at 5 percent per year after accounting for inflation. Expressed in constant 2005 dollars–the price units used in this report–the TAP price would start at $10.42 in 2012 and rise to $25.07 in 2030.The share of allowances auctioned ultimately depends on how many allowances are distributed for agricultural sequestration and CCS. The bill initially allots 5 percent of total allowances for agricultural sequestration and 8 percent for CCS. However, if these initial pools are oversubscribed and additional allowances are needed to provide these incentives, the allowances are taken from the auction pool, reducing the number of allowances that are auctioned. The supplemental, or “bonus” incentive for CCS provides additional allowances for sequestered CO2 emissions at plants over their first 10 years of operation. The CCS bonus rate, which is multiplied by the number of tons sequestered to calculate the number of allowances to be granted in addition to the offset for sequestration, declines from 3.5 in 2012 to 0.9 in 2030. The attractiveness of these incentives and the initial level of the bonus rate suggest that the designated pool of 8 percent of the allowances could easily be oversubscribed, reducing the number of allowances that will be auctioned. Methodology The analysis of energy sector and energy-related economic impacts of the various GHG emission reduction proposals in this report is based on results from EIA’s National Energy Modeling System (NEMS), used for projections in the Annual Energy Outlook 2007 (AEO2007).5 NEMS projects emissions of energy-related CO2 emissions resulting from the combustion of fossil fuels, representing about 84 percent of total U.S. GHG emissions today. For this report, an updated Reference case based on the AEO2007 assumptions was prepared using NEMS with some post-AEO2007 modeling changes to support recent congressional analysis requests, as well as to reflect the baseline GHG coverage assumptions under S. 1766.6 The AEO2007 was published in February 2007; consequently, none of the cases examined in this analysis reflect the passage of the Energy Independence and Security Act of 2007, which was enacted on December 19, 2007. This law, which is expected to reduce oil consumption, increase production of alternative fuels, and increase energy efficiency, would affect the results contained in this report. The EIA Reference case is deliberately designed to reflect only current laws and policies. Because analysis of alternative policies at the request of the Congress and/or the Administration is a core part of the EIA mission and because EIA does not take a position or speculate on potential policy changes, such changes are not included in the Reference case. If assumptions about “expected” policy changes such as future fuel economy standards, taxes, caps on GHG emissions, or new regulatory requirements for conventional pollutants, were included in the Reference case, it could not be used as a baseline in assessing the impacts of alternative policy proposals in these areas. For this reason, EIA Reference case projections are not directly comparable with private energy forecasts that include estimates of policy change in their scenarios. Although forecasting policy change is beyond EIA’s mandate, a reasonable argument can be made that, all else being equal, public and industry awareness of a major policy issue alone can potentially impact energy investment decisions. For example, the possibility of future action to control GHG emissions during the expected operating lifetime of new power generation facilities could favor investment in no- and low-GHG-emission technologies relative to high-GHG-emission alternatives, even if no specific policy change actually occurred. Such an effect might be incorporated in models by penalizing technologies that are perceived to be risky due to policy concerns. However, applying such adjustments on an ad hoc basis is difficult, since the extent of any future disadvantage borne by new high-GHG emission generators that begin construction prior to the enactment of a new policy will depend heavily on the details of the policy design and implementation. It is also important to recognize that any adjustment that is made in the Reference case to reflect the influence of an unresolved policy issue, while raising costs in the Reference case, would generally reduce the estimated impact resulting from the implementation of a given policy response. For example, to the extent that concern over the climate change issue serves to significantly depress investment in new coal-fired power plants, the primary effect would be most evident in the Reference case, where significant coal builds are projected after 2015, and not in policy cases reflecting a significant cap-and-trade program for GHG emissions, where few if any conventional coal-fired power plants are projected to be built. Since policy impacts are measured in terms of the difference between cases that incorporate policy changes and the Reference case baseline, the impact of modeling adjustments to reflect the impact of unresolved policy issues would generally be to reduce, rather than increase, the estimated impact of a given policy response on delivered energy costs. NEMS endogenously calculates changes in energy-related CO2 emissions in the analysis cases. The cost of using each fossil fuel includes the costs associated with the GHG allowances needed to cover the emissions produced when they are used. These adjustments influence energy demand and energy-related CO2 emissions. The GHG allowance price also determines the reductions in projected baseline emissions of other GHGs based on assumed abatement cost relationships. With emission allowance banking, NEMS solves for the time path of permit prices such that cumulative emissions match the cumulative emissions target without requiring allowance borrowing and with price escalation consistent with the average cost of capital to the electric power sector. Under S. 1766, the TAP price provides a ceiling on the allowance price. Because the 5-percent real growth in the TAP price is not expected to be high enough to induce allowance banking, allowance banking is assumed to end when the TAP price is attained.The NEMS Macroeconomic Activity Module (MAM), which is based on the Global Insight U.S. Model, interacts with the energy supply, demand, and conversion modules of NEMS to solve for an energy-economy equilibrium. In an iterative process within NEMS, MAM reacts to changes in energy prices, energy consumption, and allowance revenues, solving for the effect on macroeconomic and industry level variables such as real gross domestic product (GDP), the unemployment rate, inflation, and real industrial output. To represent nonenergy-related GHG emissions abatement and increases in biogenic carbon sequestration, EIA applied the same methodologies and data sources described in its evaluation of S. 280, the Climate Stewardship and Innovation Act of 2007.7 For the analysis of the S. 1766, however, no international emission offsets were used, and several nonenergy emissions sources, notably, methane from natural gas systems and agricultural-related nitrous oxide, were assumed to be ineligible as offsets. For more information on the NEMS MAM and nonenergy emissions abatement assumptions, see the EIA’s S. 280 analysis. EIA is unable to directly model or estimate the effects of the energy technology incentives funded from the S. 1766 allowance auction revenue and the TAP programs. EIA also does not address the impacts of climate change adaptation programs, nor the potential benefits of S. 1766 in mitigating climate change. Analysis Cases The letter requesting this analysis specified that the impacts of S. 1766 should be estimated under two sets of assumptions, the EIA’s AEO2007 Reference case assumptions and the AEO2007 High Technology case assumptions. The latter includes more optimistic assumptions regarding the availability, cost, and performance of new energy consumption and electricity production technologies.8 The letter also requested an additional case be prepared, with the high technology assumptions, that includes several energy policies under consideration in recent energy bills, including a Corporate Average Fuel Economy (CAFE) standard for light-duty vehicles of 35 miles per gallon, as passed by the Senate in June 2007; a renewable fuels standard (RFS); and a 15-percent renewable portfolio standard (RPS) for electricity producers. A subsequent letter clarifying the analysis request (Appendix B) dropped the request for inclusion of the RFS as it would have delayed the analysis. The letter also requested a case where the bonus allowance incentive for CCS was halved. In addition to the requested cases, two alternative cases were prepared. For comparison purposes, a case simulating the impacts of S. 1766 together with the CAFE and RPS policies using reference technology assumptions was prepared. The results from this case are not discussed in the report, but they are useful when trying to separate the impacts of the technology assumptions and other policies from the impacts of S. 1766. EIA also prepared a “what-if” case with limits on several key carbon reduction technologies for electric power generation, as well as limits on the expansion of liquefied natural gas (LNG) imports. Earlier EIA analyses have shown that these technologies are likely to be important in reducing U.S. greenhouse gas emissions but there is considerable uncertainty about their future cost and performance; how fast they might reach commercialization; and whether other hurdles such as licensing, financing, and public acceptance might slow or block their market penetration. The assumptions for this case are based on a recent letter to EIA from Senators Barrasso, Inhofe, and Voinovich9 who requested EIA to include scenarios assuming nuclear and biomass could not be expanded beyond the AEO2007 Reference case levels, CCS technologies were unavailable through 2030, and the supply of imported natural gas was restricted, citing the uncertainty regarding technology availability and the adequacy of future natural gas supplies. This case examines what would happen if some of the key technologies found to be important in the S. 1766 policy cases were not widely available between now and 2030. The results of this case illustrate the effects of technology development and deployment uncertainties, and the full set of tables for this case, along with the others prepared for this analysis, are included on EIA’s web site.EIA has previously pointed out that the level of barriers to key technologies may be directly influenced by policy design choices.10 For example, inclusion of a mechanism to relax compliance pressure that is tied to the level of compliance costs or other measures of economic impact is likely to discourage efforts by some stakeholders to raise barriers to particular technologies, such as nuclear power, that are attractive from a GHG emissions reduction perspective but are controversial for other reasons. With such a mechanism in place, these stakeholders will recognize that success in impeding particular GHG emission reduction options would increase the chances of triggering the mechanism and compromising the GHG target. In the absence of such a mechanism, these stakeholders might be more inclined to press their opposition to particular technologies once a GHG target is set, because they know the allowance price will increase to whatever higher level may be required to encourage deployment of the emission reduction options they prefer without compromising the GHG target. To examine the impacts of S. 1766, simulations of NEMS were made with and without the provisions of the bill. The list of cases examined is shown in Table 1. Note that four of the policy cases (S. 1766 Core, the Half CCS Bonus, S. 1766 Limited Alternatives and S. 1766 Plus Policies) are based on Reference case assumptions, while the other two S. 1766 cases are based on the high technology assumptions. Because the technology development assumed in the High Technology case is not ascribed to the effects of the S. 1766 policies, the results of the two S. 1766 cases under high technology assumptions should be compared to the High Technology case under current policies, not the standard Reference case. While faster technology advancement could be induced under a GHG cap and trade bill, particularly with additional technology research and development programs funded with allowance proceeds, EIA is unable to link the proposed spending provisions under S. 1766 to the technology improvements suggested by the High Technology case.Finally, all of EIA’s analysis cases assume efficient policy implementation subject to whatever specific technology constraints and policies are modeled. To the extent that actual policies are implemented in a manner that degrades efficiency, allowance prices and energy and economic impacts can increase beyond the modeled levels. Economic impact results are also sensitive to the representation of the role of energy in the aggregate production function that is incorporated in the NEMS MAM. |