# Climate Change: Costs and Benefits of S. 2191/S. 3036 > Briefs, arguments, decisions, and more. URL: https://www.frixlaw.com/law-library/documents/crs%3ARL34489 ## Record - **Collection:** Congressional research report - **Document type:** CRS Report - **Published:** May 15, 2008 - **Citation:** RL34489 ## Text ȱ •’–ŠŽȱ‘Š—ŽDZȱ˜œœȱŠ—ȱŽ—Ž’œȱ˜ȱ ǯȱŘŗşŗȦǯȱřŖřŜȱ Š››¢ȱŠ›”Ž›ȱ ™ŽŒ’Š•’œȱ’—ȱ—Ž›¢ȱŠ—ȱ—Ÿ’›˜—–Ž—Š•ȱ˜•’Œ¢ȱ ›Ž—ȱǯȱŠŒ˜‹žŒŒ’ȱ ™ŽŒ’Š•’œȱ’—ȱ—Ž›¢ȱŠ—ȱ—Ÿ’›˜—–Ž—Š•ȱ˜•’Œ¢ȱ Š¢ȱŗśǰȱŘŖŖŞȱ ˜—›Žœœ’˜—Š•ȱŽœŽŠ›Œ‘ȱŽ›Ÿ’ŒŽȱ ŝȬśŝŖŖȱ ǯŒ›œǯ˜Ÿȱ řŚŚŞşȱ ȱŽ™˜›ȱ˜›ȱ˜—›Žœœ Prepared for Members and Committees of Congress ȱ •’–ŠŽȱ‘Š—ŽDZȱ˜œœȱŠ—ȱŽ—Ž’œȱ˜ȱǯȱŘŗşŗȦǯȱřŖřŜȱ ž––Š›¢ȱ This report examines six studies that project the costs of S. 2191 (S. 3036) to 2030 or 2050. It is difficult to project costs up to the year 2030, much less beyond. The already tenuous assumption that regulatory standards will remain constant becomes more unrealistic, and other unforeseen events loom as critical issues which cannot be modeled. Long-term cost projections are at best speculative, and should be viewed with attentive skepticism. Despite models’ inability to predict the future, cases examined here do provide insights on the costs and benefits of S. 2191. First, the ultimate cost of S. 2191 would be determined by the response of the economy to the technological challenges presented by the bill. The potential for technology to reduce S. 2191‘s costs is not fully analyzed by any of the cases, nor can it be. Technology development is not sufficiently understood currently for models to replicate with confidence. Likewise, it is difficult to determine if available incentives are directed in an optimal manner. The cases suggest that S. 2191‘s Carbon Capture and Storage (CCS) bonus allowances would encourage deployment of CCS, accelerating development by 5-10 years. Second, a considerable amount of low-carbon generating capacity will have to be built under S. 2191 in order to meet the reduction requirement. How much capacity will be necessary depends on new and replacement capacity needs, along with consumer demand response to rising prices and incentives contained in S. 2191. Third, offsets could be a valuable tool not only to potentially reduce costs, but also to buy time to permit further development of new, more efficient technologies. Cost could be lowered further by greater availability of offsets and international credits and with a broader definition of eligible international credits. Fourth, the Carbon Market Efficiency Board could have an important effect on the cost of S. 2191 through its power to extend the availability of offsets and international credits. In this sense, the Board’s powers could mesh with the previous insight about the potential effect of offsets on the bill’s overall costs. Fifth, the Low Carbon Fuel Standard could significantly raise fuel prices and limit supply. The effects will depend on what fuels are included, the emissions reductions achieved by alternatives, and the ability to produce those alternatives. Finally, S. 2191’s climate-related benefit is best considered in a global context and the desire to engage the developing world in the reduction effort. The United States and other developed countries agreed both to reduce their own emissions to help stabilize atmospheric concentrations of greenhouse gases (GHGs) and to take the lead in reducing GHGs when they ratified the United Nations Framework Convention on Climate Change (UNFCCC). This context raises two issues for S. 2191: (1) whether S. 2191‘s GHG program would be considered sufficiently credible by developing countries so that schemes for including them in future international agreements become more likely, and (2) whether S. 2191‘s reductions meet U.S. commitments under the UNFCCC. ˜—›Žœœ’˜—Š•ȱŽœŽŠ›Œ‘ȱŽ›Ÿ’ŒŽȱ ȱ •’–ŠŽȱ‘Š—ŽDZȱ˜œœȱŠ—ȱŽ—Ž’œȱ˜ȱǯȱŘŗşŗȦǯȱřŖřŜȱ ˜—Ž—œȱ Overview of the Major Provisions of S. 2191 (S. 3036) ................................................................. 3 Earlier Versions of the Bill ........................................................................................................ 5 Bill as Introduced................................................................................................................ 5 Bill as Reported by Subcommittee...................................................................................... 6 As Ordered Reported by Committee................................................................................... 9 Deficit Reduction Amendment ........................................................................................... 9 Introduction: Models Cannot Predict the Future Costs of a Climate Change Program................... 9 Lessons from SO2 Cap and Trade Program............................................................................... 9 An Illustrative Example from Analyses of S. 2191..................................................................11 Likelihood for More Noise in Greenhouse Gas Reduction Cost Estimates .................................. 15 Complexity of the Problem ..................................................................................................... 15 Flexibility of Cap-and-Trade Program .................................................................................... 16 Importance of Technology to Future Results .......................................................................... 16 Increasing Problems with Ceteris Paribus Analysis ................................................................ 17 Changing Baselines By Changing Laws........................................................................... 17 Changing Baselines By Changing Regulation.................................................................. 18 Measuring the Noise: A Web of Cost Measures ............................................................................ 19 Three Perspectives: Getting Out of the Noise......................................................................... 22 Results for S. 2191 ........................................................................................................................ 25 Impact on Greenhouse Gas Emissions .................................................................................... 25 Impact on Non-Greenhouse Gas Emissions............................................................................ 28 Impact on GDP Per Capita ...................................................................................................... 28 Allowance Price Estimates...................................................................................................... 34 Auction Revenue Estimates .................................................................................................... 37 Issues Raised by the Models.......................................................................................................... 40 Technology Issues ................................................................................................................... 40 Electric Power Sector........................................................................................................ 40 Transportation Sector........................................................................................................ 48 Impact on Fuel Prices........................................................................................................ 50 Economic Issues...................................................................................................................... 52 Availability of Offsets....................................................................................................... 52 Impact of Banking............................................................................................................. 53 Impact of Carbon Market Efficiency Board...................................................................... 54 Impact of Revenue Recycling........................................................................................... 54 International Leakage........................................................................................................ 54 Ecological Issues..................................................................................................................... 55 Climate Change Benefits .................................................................................................. 55 Non-Climate Change Air Quality Benefits ....................................................................... 61 Impact on Behavior........................................................................................................... 62 Conclusion..................................................................................................................................... 65 ˜—›Žœœ’˜—Š•ȱŽœŽŠ›Œ‘ȱŽ›Ÿ’ŒŽȱ ȱ •’–ŠŽȱ‘Š—ŽDZȱ˜œœȱŠ—ȱŽ—Ž’œȱ˜ȱǯȱŘŗşŗȦǯȱřŖřŜȱ ’ž›Žœȱ Figure 1. Predicted Impacts of Carbon Abatement on the U.S. Economy (162 Estimates from 16 Models)......................................................................................................................... 21 Figure 2. Total Estimated Greenhouse Gas Emissions Under S. 2191.......................................... 26 Figure 3. Total Estimated Greenhouse Gas Emissions from Each Model Under S. 2191............. 27 Figure 4. GDP per Capita (2005$) Under S. 2191 ........................................................................ 29 Figure 5. GDP per Capita (2005$) from Each Model Under S. 2191 ........................................... 30 Figure 6. Percentage Change in GDP per Capita Under S. 2191 .................................................. 32 Figure 7. Percentage Change in GDP per Capita from Each Model Under S. 2191 ..................... 33 Figure 8. Projected Allowance Prices Under S. 2191.................................................................... 35 Figure 9. Projected Allowance Prices from Each Model Under S. 2191 ...................................... 36 Figure 10. Estimated Annual Revenues from Allowance Auctions Under S. 2191 ...................... 38 Figure 11. Global Mean Surface Air-Temperature Increase in Six Scenarios Using the MIT IGSM.................................................................................................................................. 61 Figure 12. Energy Price Change: Recent History Versus the S. 2191 Core Case......................... 65 Š‹•Žœȱ Table 1. Allocation of Allowances Under S. 2191 .......................................................................... 7 Table 2. Allocation of Auction Revenue (excluding Deficit Reduction Fund) Under S. 2191.............................................................................................................................................. 8 Table 3. Representative Sample of 1990 Estimates of Annual Compliance Cost for SO2 Cap-and-Trade Program ..............................................................................................................11 Table 4. Reference Case and S. 2191 Analyses for 2050 .............................................................. 12 Table 5. Reference Case Scenarios for 2020 and 2030 ................................................................. 14 Table 6. Influence of Climate Change Perspectives on Policy Parameters ................................... 23 Table 7. General Perspective of CATF and ACCF/NAM Cost Assumptions................................ 24 Table 8. Selected Results from CATF and ACCF/NAM Analyses................................................ 24 Table 9. EPA/IPM Reduction of Conventional Air Pollutants from Electric Utilities................... 28 Table 10. Allocation of Estimated Annual Auction Revenue from S. 2191 Using EPA/ADAGE-TECH Case ......................................................................................................... 39 Table 11. Assumptions about the Construction of Generating Capacity Under S. 191 to 2030............................................................................................................................................ 41 Table 12. Assumptions about the Availability of CCS .................................................................. 44 Table 13. Estimated Incremental Annual Combined Public and Private Funding Needs to Achieve EPRI’s Full Portfolio.................................................................................................... 46 Table 14. Total Public Funding Needs for 2007 CURC-EPRI Clean Coal Technology Roadmap over 18 Years (2008-2025)......................................................................................... 47 Table 15. Matrix of Climate Risks................................................................................................. 57 ˜—›Žœœ’˜—Š•ȱŽœŽŠ›Œ‘ȱŽ›Ÿ’ŒŽȱ ȱ •’–ŠŽȱ‘Š—ŽDZȱ˜œœȱŠ—ȱŽ—Ž’œȱ˜ȱǯȱŘŗşŗȦǯȱřŖřŜȱ Table 16. The Stern Review Estimates of Social Cost of Carbon for Three Emissions Paths ........................................................................................................................................... 58 ˜—ŠŒœȱ Author Contact Information .......................................................................................................... 67 ˜—›Žœœ’˜—Š•ȱŽœŽŠ›Œ‘ȱŽ›Ÿ’ŒŽȱ •’–ŠŽȱ‘Š—ŽDZȱ˜œœȱŠ—ȱŽ—Ž’œȱ˜ȱǯȱŘŗşŗȦǯȱřŖřŜȱ ȱ A s Congress continues the debate on an appropriate response to the climate change issue, multiple bills have been introduced to begin reducing greenhouse gas (GHG) emissions. Of these, S. 2191 (the Lieberman-Warner Climate Security Act of 20081) has received particular attention. Introduced by Senator Lieberman, S. 2191 was ordered reported by the Senate Committee on Environment and Public Works on December 5, 2007.2 Numerous analyses have been done on its impacts, and as of April 2008, six studies had been released. The most comprehensive analysis has been conducted by the U.S. Environmental Protection Agency (EPA). The report is entitled: EPA Analysis of the Lieberman-Warner Climate Security Act of 2008: S. 2191 in 110th Congress (March 14, 2008).3 The analysis employs a suite of models and basecases, along with some useful sensitivity analyses. This report will focus on three of the models, two basecases, and sensitivity analysis as appropriate. • The first model is ADAGE: a computable general equilibrium (CGE) model developed by RTI International.4 The case employing the reference basecase is designated EPA/ADAGE-REF in this report, while the case employing the high technology basecase is designated EPA/ADAGE-TECH. • The second model is IGEM: a CGE model developed by Dale Jorgenson Associates.5 The case employing the reference basecase is designated EPA/IGEM-REF in this report, while the case employing the high technology basecase is designated EPA/IGEM-TECH. • The third model is IPM: a dynamic, deterministic linear programming model of the U.S. electric power sector developed by ICF Resources. The case employing the IPM model is designated EPA/IPM in this report.6 A second analysis has been conducted by the Energy Information Administration (EIA). The report is entitled Energy Market and Economic Impacts of S. 2191, the Lieberman-Warner Climate Security Act of 2007 (April 2008). The analysis employs EIA’s NEMS model: a macroeconomic forecasting model with extensive energy technology detail.7 In addition to conducting a “core” analysis of S. 2191 using its preliminary 2008 Annual Energy Outlook (AEO) Baseline, EIA also conducts some useful sensitivity analyses that focus on the upside risk of increased energy prices under S. 2191 which are discussed as appropriate. The core S. 2191 analysis is designated EIA/NEMS in this report. A third analysis has been conducted by the Massachusetts Institute of Technology (MIT) Joint Program on the Science and Policy of Global Change. The report is an appendix to a more comprehensive analysis of cap-and-trade programs released in 2007.8 The appendix is titled: 1 Originally titled America’s Climate Security Act of 2007. As of May 14, 2008, the Ordered Reported version of the bill was available at Senator Lieberman’s website: http://lieberman.senate.gov/documents/lwcsa.pdf. 3 The report and supporting model runs are available at http://www.epa.gov/climatechange/economics/ economicanalyses.html 4 For more information on the ADAGE model, see http://www.rti.org/adage. 5 For more information on the IGEM model, see http://post.economics.harvard.edu/faculty/jorgenson/papers/ papers.html. 6 For more information on the IPM model, see http://www.epa.gov/airmarkets/progsreg/epa-ipm/index.html. 7 For more on the NEMS model, see http://www.eia.doe.gov/oiaf/aeo/overview/index.html. 8 Sergey Paltsev, et al., Assessment of U.S. Cap-and-Trade Proposals, MIT Joint Program on the Science and Policy of (continued...) 2 ˜—›Žœœ’˜—Š•ȱŽœŽŠ›Œ‘ȱŽ›Ÿ’ŒŽȱ ŗȱ ȱ •’–ŠŽȱ‘Š—ŽDZȱ˜œœȱŠ—ȱŽ—Ž’œȱ˜ȱǯȱŘŗşŗȦǯȱřŖřŜȱ Appendix D: Analysis of the Cap and Trade Features of the Lieberman-Warner Climate Security Act (S. 2191). The appendix employs MIT’s EPPA CGE model and presents some useful sensitivity analyses of S. 2191‘s offset and carbon capture and storage (CCS) bonus allowance provisions. The case that includes S. 2191‘s 15% international offset and CCS subsidies provisions is designated MIT/EPPA in this report.9 A fourth analysis has been conducted for the Clean Air Task Force (CATF) by OnLocation. The report is titled The Lieberman-Warner Climate Security Act—S. 2191: A Summary of Modeling Results from the National Energy Modeling System (February 2008). Employing EIA’s NEMS model, the CATF analysis is designated CATF/NEMS in this report. A fifth analysis has been conducted for the American Council for Capital Formation (ACCF) and National Association of Manufacturers (NAM) by Science Applications International Corporation. The report is entitled Analysis of The Lieberman-Warner Climate Security Act (S. 2191) Using The National Energy Modeling System (NEMS). Employing NEMS, ACCF/NAM employs two basic cases: (1) a high cost case using the most constrained and high cost assumptions of any of the analyses presented here (designated as ACCF/NAM/NEMS-HIGH) and (2) a low cost case using the second most constrained and high cost assumptions of any of the analyses presented here (designated as ACCF/NAM/NEMS-LOW). A sixth analysis has been conducted for the National Mining Association (NMA) by CRA International. The report is entitled Economic Analysis of the Lieberman-Warner Climate Security Act of 2007 Using CRA’s MRN-NEEM Model (April 8, 2008). The analysis employs CRA’s MRN-NEEM macroeconomic model with extensive electric power sector detail.10 The case employing the NMA analysis is designated NMA/CRA. It should be noted that several of the studies examined in this report are published as presentations with limited documentation, making comparative analysis difficult. Each presentation has selected features or impacts it is particularly interested in highlighting. The more comprehensive analyses are the work by EPA, EIA, and MIT. In order to increase the comparability of the various cases examined here, CRS has converted all publicly available data presented by the cases to 2005 dollars (where appropriate) and interpolated missing data where possible. Likewise, where studies have stated they used specific projections as a base case (such as EIA’s Annual Energy Outlook 2007 or preliminary 2008 projections), CRS has assumed those assumptions have not been altered except as specifically stated by the study. This analysis considers the bill as ordered reported by the Senate Committee on Environment and Public Works, incorporating the proposed deficit reduction amendment—S. 3036 is identical to that version, including the deficit amendment. Other proposed amendments are likely if the bill moves to the floor, and these amendments, if adopted, could affect the costs and benefits of the overall bill. (...continued) Global Change, Report No. 146 (April 2007). 9 The primary scenario used for this report—the S. 2191, 15% Offsets and CCS Subsidy case—is summarized on p. D21. For more information on the EPPA model, see http://web.mit.edu/globalchange/www/eppa.html. 10 For more information on the MRN-NEEM model, see http://www.crai.com/uploadedFiles/ RELATING_MATERIALS/Publications/BC/Energy_and_Environment/files/MRNNEEM%20Integrated%20Model%20for%20Analysis%20of%20US%20Greenhouse%20Gas%20Policies.pdf. ˜—›Žœœ’˜—Š•ȱŽœŽŠ›Œ‘ȱŽ›Ÿ’ŒŽȱ Řȱ ȱ •’–ŠŽȱ‘Š—ŽDZȱ˜œœȱŠ—ȱŽ—Ž’œȱ˜ȱǯȱŘŗşŗȦǯȱřŖřŜȱ ŸŽ›Ÿ’Ž ȱ˜ȱ‘ŽȱŠ“˜›ȱ›˜Ÿ’œ’˜—œȱ˜ȱǯȱŘŗşŗȱ ǻǯȱřŖřŜǼȱ S. 2191, The Lieberman-Warner Climate Security Act of 2008, was introduced October 18, 2007, by Senator Lieberman. On December 5, 2007, the Senate Committee on Environment and Public Works ordered reported an amended version of the bill that would establish a mandatory cap-andtrade system to reduce greenhouse gas emissions from most sectors of the economy.11 As ordered reported, S. 2191‘s emissions cap is estimated by its sponsors to require a 71% reduction from 2005 levels by 2050 from covered entities (estimated by the sponsors to account for 87% of total U.S. greenhouse gas emissions). Overall, the sponsors estimate that S. 2191 would reduce total U.S. greenhouse gas emissions by up to 66% from 2005 levels by 2050. S. 2191 would establish an absolute cap on the emissions from covered sectors and would allow trading of emissions permits (“allowances”) among covered and non-covered entities.12 The bill achieves its broad coverage through an upstream compliance mandate on petroleum, natural gas, and fluorinated gas producers and importers, and a downstream mandate on coal consumers, such as electric generators. Specifically, the bill would limit greenhouse gas emissions from all petroleum producers/importers, all natural gas processors, all facilities that use more than 5,000 tons of coal per year, and entities that produce or import more than 10,000 tons annually (carbon dioxide equivalent) of fluorinated gases and other greenhouse gases. S. 2191 does not have a “safety valve”—an alternative compliance option that permits covered entities to pay an excess emissions fee instead of reducing emissions. Instead, the bill creates a Carbon Market Efficiency Board with authority to temporarily adjust the availability of allowances through borrowing and other techniques; however, it is a zero-sum game. Allowances borrowed must be repaid, so the emissions cap is maintained. The bill limits the availability of domestic offsets to 15% of the allowance requirement, with allowances bought in an eligible international allowance market also limited to 15%. Both percentages may be increased by the Carbon Market Efficiency Board if market conditions suggest such action. The bill would permit banking of allowances. For each year 2012 through 2050, the bill specifies the total number of allowances available, then explicitly states the percentage of those allowances that will go to covered and non-covered sectors,13 as well as the share that will be auctioned. (See Table 1.) Over time, an increasing share of the allowances are auctioned, while the allowances to covered sectors decrease to zero. Auction proceeds are allocated for various purposes, including technology development and deployment, transition assistance, adaptation, and program administration.14 (See Table 2.) Under 11 For more a more detailed discussion of S. 2191 provisions, and a comparison with other proposals, see CRS Report RL33846, Greenhouse Gas Reduction: Cap-and-Trade Bills in the 110th Congress, by (name redacted), (name red acted), and (name redacted). 12 See “Common Terms” box for definitions. For more detailed definitions, see CRS Report RL33846. 13 In addition to allowances given at no cost to covered sectors, the bill also allocates allowances to states and tribes for various policy objectives, to local energy distribution companies to reduce costs to low- and middle-income energy consumers, to the U.S. Department of Agriculture to fund sequestration projects, and other purposes. Non-covered entities must sell their allowances (for “fair market value”) within one year of receipt and use the proceeds from those sales for specified purposes. 14 For a more detailed description of the allocation of allowances and auction revenues under S. 2191, see CRS General Distribution Memo Allocations of Carbon Allowances and Auctions under S. 2191 as Ordered Reported by the Senate (continued...) ˜—›Žœœ’˜—Š•ȱŽœŽŠ›Œ‘ȱŽ›Ÿ’ŒŽȱ řȱ •’–ŠŽȱ‘Š—ŽDZȱ˜œœȱŠ—ȱŽ—Ž’œȱ˜ȱǯȱŘŗşŗȦǯȱřŖřŜȱ ȱ a proposed amendment to make the bill revenue neutral, a percentage of allowances (starting at 6.1%, increasing to 15.99%) would be auctioned off-the-top for deficit reduction (“Deficit Reduction Fund”). After the Deficit Reduction allowances are allocated, the rest of the allowances (“remainder allowances”) are allocated according to the bill as reported. For example, in 2012, 6.1% of the total number of allowances are auctioned for deficit reduction, and an additional 21.5% of the “remainder allowances” are auctioned for program management, technology deployment, adaptation, and other purposes. Common Terms Allowance. A limited authorization by the government to emit 1 metric ton of carbon dioxide equivalent. Although used generically, an allowance is technically different from a credit. A credit represents a ton of pollutant that an entity has reduced in excess of its legal requirement. However, the terms tend to be used interchangeably, along with others, such as permits. Auctions. Auctions can be used in market-based pollution control schemes to allocate some, or all of the allowances. Auctions may be used to: (1) ensure the liquidity of the credit trading program; and/or (2) raise (potentially considerable) revenues for various related or unrelated purposes. Banking. The limited ability to save allowances for the future and shift the reduction requirement across time. Cap-and-trade program. An emissions reduction program with two key elements: (1) an absolute limit (“cap”) on the emissions allowed by covered entities; and (2) the ability to buy and sell (“trade”) those allowances among covered and non-covered entities. Coverage. Coverage is the breadth of economic sectors covered by a particular greenhouse gas reduction program, as well as the breadth of entities within sectors. Emissions cap. A mandated limit on how much pollutant (or greenhouse gases) an affected entity can release to the atmosphere. Caps can be either an absolute cap, where the amount is specified in terms of tons of emissions on an annual basis, or a rate-based cap, where the amount of emissions produced per unit of output (such as electricity) is specified but not the absolute amount released. Caps may be imposed on an entity, sector, or economy-wide basis. Greenhouse gases. The six gases recognized under the United Nations Framework Convention on Climate Change are carbon dioxide (CO2), methane (CH4), nitrous oxide (N2O), sulfur hexafluoride (SF6), hydrofluorocarbons (HFC), and perfluorocarbons (PFC). Leakage. The shift in greenhouse gas (GHG) emissions from an area subject to regulation (e.g., cap-and-trade program) to an unregulated area, so reduction benefits are not obtained. This would happen, for example, if a GHG emitting industry moved from a country with an emissions cap to a country without a cap. Offsets. Emission credits achieved by activities not directly related to the emissions of an affected source. Examples of offsets would include forestry and agricultural activities that absorb carbon dioxide, and reductions achieved by entities that are not regulated by a greenhouse gas control program. Revenue recycling. How a program disposes of revenues from auctions, penalties, and/or taxes. Revenue recycling can have a significant effect on the overall cost of the program to the economy. Sequestration. Sequestration is the process of capturing carbon dioxide from emission streams or from the atmosphere and then storing it in such a way as to prevent its release to the atmosphere. In addition to the cap-and-trade program, S. 2191 has other key provisions to reduce greenhouse gas emissions. • Title VI imposes an “international reserve allowance” requirement on certain “covered” imported goods as a prerequisite for entry into the country.15 Unlike (...continued) Committee on Environment and Public Works, dated May 13, 2008. 15 For a further discussion of Title VI, see Jeanne Grimmett and (name redacted), Whether Import Requirements Contained (continued...) ˜—›Žœœ’˜—Š•ȱŽœŽŠ›Œ‘ȱŽ›Ÿ’ŒŽȱ Śȱ •’–ŠŽȱ‘Š—ŽDZȱ˜œœȱŠ—ȱŽ—Ž’œȱ˜ȱǯȱŘŗşŗȦǯȱřŖřŜȱ ȱ importers of covered fuels that create greenhouse gases when used (which are directly controlled as covered facilities under S. 2191), Title VI would affect certain bulk goods manufactured in processes that generate greenhouse gases (e.g. iron, paper, etc.) that would not be allowed into the country if the allowance requirement were not met. The amount and allocation of international reserve allowances would be determined by EPA, and a separate allowance trading system could be established (international reserve allowances could not be used for domestic compliance). • Title VIII on carbon sequestration16 requires: (1) EPA to amend regulations under the Safe Drinking Water Act to allow commercial-scale underground injection of carbon dioxide for sequestration, and to monitor such activity to reduce adverse impacts from such injection; (2) the Department of the Interior to assess U.S. capacity for geological sequestration; (3) the Department of Energy to assess the feasibility of CO2 pipelines; and (4) EPA to establish a task force to study the issues related to federal assumption of liability for sequestration sites. • Title IX permits the President to temporarily adjust or waive any regulations promulgated under the bill if a “national security emergency exists,” and it is in the “paramount interest of the United States” to modify the requirements in response to that emergency. • In addition to the limits under the cap-and-trade program, Title X requires EPA to establish a program limiting U.S. consumption of hydrofluorocarbons under a separate HFC allowance program. • Title XI amends the Clean Air Act in three ways: (1) it requires EPA to establish a program to limit emissions of greenhouse gases not covered under the program; (2) it limits the sale and use of certain motor vehicle air conditioning fluids; and (3) it establishes a low carbon fuel standard (LCFS) requiring per-unit-energy reductions in greenhouse gas emissions from transportation fuels.17 Š›•’Ž›ȱŽ›œ’˜—œȱ˜ȱ‘Žȱ’••ȱ ’••ȱŠœȱ —›˜žŒŽȱ S. 2191 (originally titled America’s Climate Security Act of 2007), as introduced October 18, 2007, by Senator Lieberman, would cap greenhouse gas emissions from the electric generation, industrial, and transportation sectors (for facilities that emit more than 10,000 metric tons of carbon dioxide equivalent). As introduced, the cap was estimated by the sponsors to reduce emissions to 15% below 2005 levels in 2020, declining steadily to 63% below 2005 levels in 2050. The program would be implemented through an expansive allowance trading program to maximize opportunities for cost-effective reductions. Credits obtained from increases in carbon (...continued) in Title VI of S. 2191, the Lieberman-Warner Climate Security Act of 2008, as Ordered Reported, Are Consistent with U.S. WTO Obligations, Congressional Distribution Memorandum (March 27, 2008). Available from the authors. 16 For more information on carbon sequestration, see CRS Report RL33801, Carbon Capture and Sequestration (CCS), by (name redacted). 17 This LCFS provision is discussed in more detail in the section below under “Transportation Sector.” ˜—›Žœœ’˜—Š•ȱŽœŽŠ›Œ‘ȱŽ›Ÿ’ŒŽȱ śȱ ȱ •’–ŠŽȱ‘Š—ŽDZȱ˜œœȱŠ—ȱŽ—Ž’œȱ˜ȱǯȱŘŗşŗȦǯȱřŖřŜȱ sequestration and acquisition of allowances from foreign sources could be used to comply with 30% of reduction requirements. The bill also establishes a Carbon Market Efficiency Board to observe the allowance market and implement cost-relief measures if necessary. ’••ȱŠœȱŽ™˜›Žȱ‹¢ȱž‹Œ˜––’ŽŽȱ On November 1, 2007, the Senate Committee on Environment and Public Works’ Subcommittee on Private Sector and Consumer Solutions to Global Warming and Wildlife Protection reported out a revised version of S. 2191. As reported from subcommittee, S. 2191 was estimated to reduce greenhouse gas emissions 19% below 2005 levels by 2020 (up from 15% as introduced) and 63% below 2005 levels by 2050. The increase in the estimated reductions in 2020 is the result of amended text that includes greenhouse gases from all natural gas uses under the overall emissions cap. Other amendments approved included modifications to eligibility requirements for the advanced technology vehicles manufacturing incentive program and the advanced coal generation technology demonstration program. Modifications were also made to the proposed allocation of allowances to help tribal communities respond to climate change and to encourage international forest carbon activities, along with 1% of allowances reserved for rural cooperatives and a corresponding reduction in allowances allocated to the rest of the electric power industry. The revised bill also added two new recipients of auction revenues: a Bureau of Land Management Emergency Firefighting Fund ($300 million) and a Forest Service Emergency Firefighting Fund ($800 million). ˜—›Žœœ’˜—Š•ȱŽœŽŠ›Œ‘ȱŽ›Ÿ’ŒŽȱ Ŝȱ •’–ŠŽȱ‘Š—ŽDZȱ˜œœȱŠ—ȱŽ—Ž’œȱ˜ȱǯȱŘŗşŗȦǯȱřŖřŜȱ ȱ . Allocation of Allowances Under S. 2191 Table 1 2012 2020 2030 2040 2050 Total Allowances (millions) Sec. 1201 5775 4924 3860 2796 1732 Deficit Reduction Fund Sec. 3101 (as amended) 6.10% 8.40% 14.43% 15.99% 15.99% Remainder Allowances (millions) Sec. 3101 (as amended) 5423 4510 3303 2349 1455 Sec. 3101 Sec. 3102 Sec. 3201 Secs. 3301-3304 Sec. 3303(d) Sec. 3401 Sec. 3501 Sec. 3601 5% 21.5% 5% 10.5% 0.5% 9% 2% 4% 0% 36.5% 0% 10.5% 0.5% 9% 2% 4% 62.8% 69.5% 69.5% 10.5% 0.5% 9% 2% 4% 10.5% 0.5% 9% 2% 0% 10.5% 0.5% 9% 2% Sec. 3701 5% 5% 5% 5% 5% Sec. 3803 2.5% 2.5% 2.5% 2.5% 2.5% Sec. 3901 19% 16% 1% Sec. 3901 1% 1% 1% Sec. 3903(a)(2) 0.2% 0.2% 0% Sec. 3901 10% 8% 0% Sec. 3901 2% 2% 0.25% Sec. 3901 2% 2% 0.25% Sec. 3907 1% 1% 1% 1% 1% Share of Remainder Allowances Early Auction Auction Early Action States Tribal Communities Low/Middle-Class Electricity Consumers Low/Middle-Class Natural Gas Consumers CCS Bonus Allowances Domestic Agriculture and Forestry International Forest Protection Transition Assistance Fossil Fueled Electric Plants Rural Electric Cooperatives Pilot Program for VA and MT Energy-Intensive Manufacturing Facilities Petroleum Production/Import Facilities HFC Producers/Importers Landfill and Coal Mine Methane Reduction Ȭŝȱ •’–ŠŽȱ‘Š—ŽDZȱ˜œœȱŠ—ȱŽ—Ž’œȱ˜ȱǯȱŘŗşŗȦǯȱřŖřŜȱ ȱ . Allocation of Auction Revenue (excluding Deficit Reduction Fund) Under S. 2191 Table 2 2012 2020 2030 2040 2050 SSAN SSAN SSAN SSAN SSAN SSAN SSAN SSAN SSAN SSAN SSAN SSAN SSAN SSAN SSAN Off-the-Top Allocation of Auction Proceeds BLM Emergency Firefighting Fund Forest Service Emergency Firefighting Fund CSA Management Fund Sec. 4302(b)(1) Sec. 4302(b)(2) Sec. 4302(b)(3) Percentage of Remaining Proceeds Technology Deployment Sec. 4302(b)(4)(B) 52% 52% 52% 52% 52% Energy Independence Acceleration Fund Sec. 4302(b)(4)(C) 2% 2% 2% 2% 2% Energy Assistance Fund Sec. 4302(b)(4)(D) 18% 18% 18% 18% 18% Climate Change Worker Training Fund Sec. 4302(b)(4)(E) 5% 5% 5% 5% 5% Adaptation Fund Sec. 4302(b)(4)(F) 18% 18% 18% 18% 18% Climate Change and National Security Fund Sec. 4302(b)(4)(G) 5% 5% 5% 5% 5% Note: SSAN = “such sums as necessary.” For its analysis of S. 2191, EPA estimated total program costs (“CSA Management Fund”) at 1% of the total value of allowances in a given year. ȬŞȱ •’–ŠŽȱ‘Š—ŽDZȱ˜œœȱŠ—ȱŽ—Ž’œȱ˜ȱǯȱŘŗşŗȦǯȱřŖřŜȱ ȱ œȱ›Ž›ŽȱŽ™˜›Žȱ‹¢ȱ˜––’ŽŽȱ On December 5, 2007, the full committee ordered reported a revised version of S. 2191 by an 11 to 8 vote. The revised bill expands the greenhouse gas reduction program coverage by replacing the previous definition of covered facility based on the electric power, transportation, and industrial sectors with an upstream definition for oil refineries and natural gas processing plants, and a downstream definition for coal consumers. Among the amendments agreed to by the full committee were a new Low Carbon Fuel Standard (LCFS) that would require the carbon intensity of transportation fuel to be frozen in 2011 and then reduced by 5% in 2015 and 10% in 2020. Other amendments agreed to would increase incentives for states to modify their utility regulatory structures to encourage energy efficiency, and would broaden the ability of states to use their allowance allocations to mitigate adverse economic impacts resulting from the bill’s implementation. Ž’Œ’ȱŽžŒ’˜—ȱ–Ž—–Ž—ȱ Finally, in April 2008, a proposed amendment to S. 2191 was submitted by the committee to the Congressional Budget Office (CBO) to be included in the scoring of the bill. The amendment would provide for some of the auctioned revenues to be put aside for deficit reduction purposes. —›˜žŒ’˜—DZȱ˜Ž•œȱŠ——˜ȱ›Ž’Œȱ‘Žȱžž›Žȱ ˜œœȱ˜ȱŠȱ•’–ŠŽȱ‘Š—Žȱ›˜›Š–ȱ Žœœ˜—œȱ›˜–ȱŘȱŠ™ȱŠ—ȱ›ŠŽȱ›˜›Š–ȱ During the Clean Air Act debate in 1990 on the Title IV sulfur dioxide (SO2) cap-and trade program, CRS found it difficult to analyze the cost of the bill beyond the first 10 years (19902000), and considered any breakdown of even 2000 data on a state-by-state basis as “not useful for any more than illustrative purposes.”18 As stated in 1990: It is difficult (and some would consider it unwise) to project costs up to the year 2000, much less beyond. The already tenuous assumption that current regulatory standards will remain constant becomes more unrealistic, and other unforeseen events (such as electric utility deregulation) loom as critical issues which can not be modeled. Hence, cost projections beyond the year 2000 are at best speculative, and are more a function of each model’s assumptions and structure than they are of the details of proposed legislation. Projections this far into the future are based more on philosophy than analysis.19 [emphasis in original] The history of resulting SO2 cap-and-trade program costs has proven illuminating. As indicated in Table 3, the 2010 cost estimates for the SO2 cap-and-trade program made in 1990 proved to be substantially higher than what is now estimated to be the program’s actual costs. Indeed, the EPA18 See CRS Report 90-63, Acid Rain Control: An Analysis of Title IV of S. 1630, by (name redacted) (January 31, 1990), p. 13. (Available from the author.) 19 Ibid., p. 16. ˜—›Žœœ’˜—Š•ȱŽœŽŠ›Œ‘ȱŽ›Ÿ’ŒŽȱ şȱ •’–ŠŽȱ‘Š—ŽDZȱ˜œœȱŠ—ȱŽ—Ž’œȱ˜ȱǯȱŘŗşŗȦǯȱřŖřŜȱ ȱ ICF low estimate—the estimate closest to the projected actual number—is both 50% higher than the actual number, and the estimate least focused-on in the original ICF report.20 It is interesting that none of the analyses were willing to “speculate” with assumptions that would have created a 2010 cost estimate lower than EPA’s current projection.21 Equally interesting is that the “best” 2000 estimate was off by almost the same 50% that the 2010 estimate was.22 Like the 2010 estimates, the assumptions either underestimated the ingenuity and creativity of companies in responding to the SO2 requirements, or mis-read the economics of the cap-and-trade process. As explained below by Chestnut and Mills in 2005, the gross overestimates are essentially the product of the models’ failure both to fully incorporate the flexibility that the cap-and-trade program provided participants and to employ sufficient imagination to explore the potential for technological breakthroughs and enhancements: Costs are lower than originally predicted primarily because flexibility occurred in areas that were thought to be inflexible and technical improvements were made that were not anticipated. Factors contributing to the lower costs included lower transportation costs for low-sulfur coal (attributed to railroad deregulation), productivity increases in coal production leading to favorable prices for low-sulfur and mid-sulfur coal, cheaper than expected installation and operation costs for smokestack scrubbers, and new boiler adaptations to allow use of different types of coal. It appears that Title IV has worked as expected to provide the flexibility and incentives for producers to find low-cost compliance options. [footnote omitted] Banking opportunities also induced early reductions in emissions for some facilities. Harrington et al (2000) compared estimates of actual costs of many large regulatory programs to predictions of those costs made while the regulatory programs were being developed and found a tendency for predicted costs to overstate the actual implementation costs, especially for market-based programs such as the SO2 trading program. They cite technological innovation and unanticipated efficiency gains as key factors leading to lower than predicted costs. They noted that unit costs are often more accurately predicted than total costs because predicted emission reductions are sometimes overstated, but they report that predicted unit costs and total costs were both overstated for Title IV.23 20 The only 2010 national utility cost estimate mentioned in the summary of findings is for the High Case: “Longerterm costs reach about $5 billion [1988 dollars] per year by 2010 under both the High House and Senate cases, due to the provisions requiring new source emissions to be offset.” The Low House and Senate cases for 2010 are not mentioned. See EPA-ICF: ICF Resources Incorporated, Comparison of the Economic Impacts of the Acid Rain Provisions of the Senate Bill (S. 1630) and the House Bill (S. 1630), Prepared for the U.S. Environmental Protection Agency (July 1990), p. 21. 21 The implementation of the SO2 provisions of the Clean Air Interstate Rule (CAIR) will significantly increase the stringency of the SO2 cap for 23 states and the District of Columbia and will likely prevent EPA from estimating actual Title IV compliance costs in 2010 because of program interaction. 22 In its 1990 analysis, CRS agreed with the range of estimates provided by the EPA-ICF analysis for 2000. As suggested above, CRS did not estimate the costs for 2010. See CRS Report 90-63, Acid Rain Control: An Analysis of Title IV of S. 1630, by (name redacted) (January 31, 1990), p. 56. (Available from the author.) 23 Lauraine G. Chestnut and David M. Mills, “A fresh look at the benefits and costs of the US acid rain program,” Journal of Environmental Management 77 (2005) p. 255. ˜—›Žœœ’˜—Š•ȱŽœŽŠ›Œ‘ȱŽ›Ÿ’ŒŽȱ ŗŖȱ •’–ŠŽȱ‘Š—ŽDZȱ˜œœȱŠ—ȱŽ—Ž’œȱ˜ȱǯȱŘŗşŗȦǯȱřŖřŜȱ ȱ Table 3. Representative Sample of 1990 Estimates of Annual Compliance Cost for SO2 Cap-and-Trade Program (billions, 2005 dollars) EPA-ICF NCAC-Pechan EEI-TBSa Estimated Actual Costs 2000-2007: Ellerman, et al. 2010: EPA 2000 2010 $2.7-$3.6 $4.4-$4.6 (for 2000-2009) $7.1-$8.7 $1.9 (for 2000-2007) $3.4-$8.0 no estimate $7.9-$11.2 $2.2 EPA-ICF: ICF Resources Incorporated, Comparison of the Economic Impacts of the Acid Rain Provisions of the Senate Bill (S. 1630) and the House Bill (S. 1630), Prepared for the U.S. Environmental Protection Agency (July 1990); Pechan: E.H. Pechan & Associates, Clean Air Act Amendment Costs and Economic Effects: A Review of Published Studies, Prepared for the National Clean Air Coalition, National Clean Air Fund (October 1990); TBS: Temple, Barker & Sloane, Inc., Economic Evaluation of H.R. 3030/S. 1490 “Clean Air Act Amendments of 1989”: Title V, The Acid Rain Control Program, Prepared for the Edison Electric Institute (August 30, 1989). Estimated 2000-2007 actual cost from A. Denny Ellerman, Paul L. Joskow, and David Harrison, Jr., Emissions Trading in the U.S.: Experience, Lessons, and Considerations for Greenhouse Gases, prepared for the Pew Center on Global Climate Change (November 2007) p. 15. Estimated 2010 actual cost from: EPA, Acid Rain Program Benefits Exceed Expectations, Figure 4, p. 4. Available at http://www.epa.gov/airmarkets/cap-trade/docs/benefits.pdf. All estimates converted to 2005 dollars using the GDP implicit price deflator. a. Analysis of original Administration bill. EPA estimated that the final bill was $400 million (1988 dollars) annually more expensive than the original proposal. See EPA, Office of Air and Radiation, Clean Air Amendments: Cost Comparison (January 23, 1990). Source: —ȱ ••žœ›Š’ŸŽȱ¡Š–™•Žȱ›˜–ȱ—Š•¢œŽœȱ˜ȱǯȱŘŗşŗȱ There is no reason to believe that cost estimates for greenhouse gas reductions will be any more accurate than the 1990 SO2 estimates; indeed, they are likely to be more unreliable. This is not to say that they will be too high; they may be too low. To illustrate, CRS examines some results of the modeling efforts with respect to the costs of S. 2191. To frame this illustration, we focus on the three primary drivers of greenhouse gas emissions: (1) population growth, (2) incomes (measured as per capita gross domestic product [GDP]), and (3) intensity of greenhouse gas emissions relative to economic activities (measured as metric tons of greenhouse gas emissions per million dollars of GDP). As shown in the following formula, a country’s annual greenhouse gas emissions are the product of these three drivers: (Population) x (Per Capita GDP) x (Intensityghg) = Emissionsghg This is the relationship for a given point in time; over time, any effort to change emissions alters the exponential rates of change of these variables. This means that the rates of change of the three left-hand variables, measured in percentage of annual change, sum to the rate of change of the right-hand variable, emissions. Using the three drivers, Table 4 provides the essential assumptions from three analyses of S. 2191 for the year 2050. Examining the “business-as-usual” reference cases, a range of assumptions are employed by the models. As suggested by the formula above, the differing assumptions result in very different 2050 baseline GHG emissions: 10.3 billion metric tons for EPA/ADAGE-REF, 11.1 ˜—›Žœœ’˜—Š•ȱŽœŽŠ›Œ‘ȱŽ›Ÿ’ŒŽȱ ŗŗȱ •’–ŠŽȱ‘Š—ŽDZȱ˜œœȱŠ—ȱŽ—Ž’œȱ˜ȱǯȱŘŗşŗȦǯȱřŖřŜȱ ȱ billion metric tons for EPA/IGEM-REF, and 13.3 billion metric tons for MIT/EPPA—a 29% difference from the lowest to the highest. Interestingly, major sources of disagreement in the reference cases include per capita GDP and population projections—two variables that are generally not the focus of greenhouse gas reduction strategies. . Reference Case and S. 2191 Analyses for 2050 Table 4 Model EPA/ ADAGEREF EPA/ IGEMREF MIT/ EPPA Population (millions) Difference Difference from lowest GDP per from lowest to highest capita to highest model (2005$) model Reference Case Scenario GHG Intensity (GHG/ GDP)a Difference from lowest to highest model $106,800 242 24% 400 9% 17% 434 $95,400 269 397 $111,300 300 S. 2191 Scenario EPA/ ADAGEREF EPA/ IGEMREF MIT/ EPPA 400 9% $104,300 24% 127 434 $88,800 107 397 $110,500 86 48% ADAGE and IGEM model assumptions from the “Data Annex” available on the EPA website at http://www.epa.gov/climatechange/economics/economicanalyses.html. The EPPA model assumptions from Sergey Paltsev, et al., “Appendix D” of Paltsev et al., Assessment of U.S. Cap-and-Trade Proposals, MIT Joint Program on the Science and Policy of Global Change (2007). All estimates converted to 2005 dollars using the GDP implicit price deflator. a. Measured in metric tons of greenhouse gas emissions per million dollars of GDP. Source: Moving to the S. 2191 scenario as modeled, the variability in the results widens for two of the three drivers (the 2050 reference case population remains constant in the three models). Not surprisingly, the range widens for the projected 2050 greenhouse gas emissions estimates: 5.3 billion metric tons for EPA/ADAGE-REF, 4.1 billion metric tons EPA/IGEM-REF, and 3.8 billion metric tons for MIT/EPPA—a 40% difference. In particular, the models’ assumptions about the flexibility and responsiveness of the U.S. economy resulted in some interesting reversals: (1) The MIT/EPPA model, which has the closest relationship between GHGs and GDP in the reference case, has the most responsive assumptions resulting in the greatest reduction in GHG and GHG intensity under S. 2191; (2) In contrast, the EPA/ADAGE-REF model, which has the lowest GHG intensity assumption in its reference cases, has the highest GHG intensity result under S. 2191. The MIT/EPPA model assumes more economic growth per capita and more responsiveness by the economy to GHG constraints; the EPA/ADAGE model assumes the most GHG-efficient ˜—›Žœœ’˜—Š•ȱŽœŽŠ›Œ‘ȱŽ›Ÿ’ŒŽȱ ŗŘȱ ȱ •’–ŠŽȱ‘Š—ŽDZȱ˜œœȱŠ—ȱŽ—Ž’œȱ˜ȱǯȱŘŗşŗȦǯȱřŖřŜȱ economy, but the least amount of flexibility to respond to GHG constraints; and the EPA/IGEM model assumes the fastest growth in population. The result of these different views of the economy is that the economic impact is less than the differences in the models’ reference case assumptions. As indicated in Table 4, the MIT/EPPA model projection of the country’s 2050 GDP per capita under S. 2191 is greater than the basecase projections of either of the other models. According to the MIT/EPPA model, the 2050 GDP per capita of the country is reduced by only 0.75% under S. 2191. The reduction under the other two models is 6.9% for EPA/IGEM-REF and 2.4% for EPA/ADAGE-REF—well within the variability of the reference cases. The result is not significantly more consistent for projections for 2030, particularly with the addition of the EIA baselines.24 The CATF/NEMS analysis uses the EIA baseline published in its Annual Energy Outlook 2007 for its analysis.25 The EIA/NEMS analysis uses a preliminary version of EIA’s upcoming 2008 AEO baseline.26 As indicated in Table 5, the basecase assumptions for per capita GDP vary by a greater percentage for 2030 than they do for 2050. The introduction of the EIA 2008 baseline is responsible for much of the increase in GDP per capita variability (it would be 7% without it). Similarly, the inclusion of the 2007 and 2008 EIA baseline increases the variability of the greenhouse gas intensity driver (it would be 9% without it). Likewise, the GDP per capita impact of S. 2191 is within the noise of the reference cases as the estimated GDP per capita reduction under S. 2191 is only 0.3% for EIA/NEMS, 0.37% for EPPA, 0.90% for ADAGE, and 3.8% for IGEM. The situation is more constant in the 2020 reference cases, although the impact of S. 2191 is still within the noise of the per capita GDP assumptions, with S. 2191 GDP per capita impact estimated at 0.3% for EIA/NEMS, 0.69% for EPA/ADAGE-REF, 0.78% for MIT/EPPA, and 2.6% for EPA/IGEM-REF. The uncertainty about the future direction of the basic drivers of greenhouse gas emissions and the economy’s responsiveness (economically, technologically, and behaviorally) illustrate the inability of models to predict the ultimate macroeconomic costs of reducing greenhouse gases. Policy relevant analysis is analysis that provides insight into the features and design of proposals that increase or reduce compliance cost and under what economic, technological, and behavior conditions, and that identify potential intended and unintended consequences on the economy. Models cannot predict the future, but they can indicate the sensitivity of a program’s provisions to varying economic, technological, and behavioral assumptions that may assist policymakers in designing a greenhouse gas reduction strategy. 24 Currently, EIA makes projections only to the year 2030. EIA, Annual Energy Outlook 2007 With Projections to 2030, DOE/EIA-0383 (2007), (February 2007). 26 Available at http://www.eia.doe.gov/oiaf/aeo/index.html EIA/NEMS and the two ACCF/NAM/NEMs cases also use the preliminary 2008 baseline. The NMA/CRA case is also based on the preliminary 2008 basecase, but CRA does not explain how it extends EIA’s baseline beyond 2030 to 2050. 25 ˜—›Žœœ’˜—Š•ȱŽœŽŠ›Œ‘ȱŽ›Ÿ’ŒŽȱ ŗřȱ •’–ŠŽȱ‘Š—ŽDZȱ˜œœȱŠ—ȱŽ—Ž’œȱ˜ȱǯȱŘŗşŗȦǯȱřŖřŜȱ ȱ Table 5. Reference Case Scenarios for 2020 and 2030 Model EPA/ ADAGEREF EPA/ IGEM-REF MIT/EPPA CATF/ NEMSb EIA/ NEMS Population (millions) Difference Difference from lowest GDP per from lowest to highest capita to highest model (2005$) model Reference Case Scenario (2030) 364 4% $72,700 19% GHG Intensity (GHG/ GDP)a Difference from lowest to highest model 344 12% 372 $70,400 363 359 365 $73,700 $69,000 374 384 366 $62,000 372 Reference Case Scenario (2020) EPA/ ADAGEREF EPA/ IGEM-REF MIT/EPPA CATF/ NEMSb EIA/ NEMS 336 2% $59,000 12% 417 342 $58,000 428 334 337 $59,200 $56,700 435 438 338 $53,000 431 5% ADAGE and IGEM model assumptions from the “Data Annex” available on the EPA website at http://www.epa.gov/climatechange/economics/economicanalyses.html. The EPPA model assumptions from Sergey Paltsev, et al., “Appendix D” of Paltsev et al., Assessment of U.S. Cap-and-Trade Proposals, MIT Joint Program on the Science and Policy of Global Change (2007). The AEO 2007 assumptions from Energy Information Administration, Energy Market and Economic Impacts of S. 1766, the Low Carbon Economy Act of 2007 (January 2007). The AEO 2008 economic and population assumptions from EIA’s website at http://www.eia.doe.gov/oiaf/ aeo/index.html. The EIA/NEMS assumptions from EIA, Energy Market and Economic Impacts of S. 2191, the Lieberman-Warner Climate Security Act of 2007 (April 2008). All estimates converted to 2005 dollars using the GDP implicit price deflator where necessary. a. Measured in metric tons of greenhouse gas emissions per million dollars of GDP. b. Based on the report’s statement that it uses the 2007 AEO baseline projection for its analysis. All estimates converted to 2005 dollars using the GDP implicit price deflator. Source: ˜—›Žœœ’˜—Š•ȱŽœŽŠ›Œ‘ȱŽ›Ÿ’ŒŽȱ ŗŚȱ ȱ •’–ŠŽȱ‘Š—ŽDZȱ˜œœȱŠ—ȱŽ—Ž’œȱ˜ȱǯȱŘŗşŗȦǯȱřŖřŜȱ ’”Ž•’‘˜˜ȱ˜›ȱ˜›Žȱ˜’œŽȱ’—ȱ ›ŽŽ—‘˜žœŽȱ Šœȱ ŽžŒ’˜—ȱ˜œȱœ’–ŠŽœȱ The potential for noise is greater in estimating the costs of a GHG program than the simple three driver illustration presented above. In its analysis of S. 2191, EPA presents eight pages of bullets identifying various limitations on its modeling exercise and four pages of additional “qualitative” considerations.27 This is a good indicator of the modeling complexity in attempting to estimate the impact of a greenhouse gas reduction bill. These modeling limitations reflect the inherent complexity of such strategies that cannot be quantified or predicted. ˜–™•Ž¡’¢ȱ˜ȱ‘Žȱ›˜‹•Ž–ȱ Compared with the complexity of implementing a greenhouse gas cap-and trade scheme, the SO2 program was trivial. Conceptually, a CO2 tradeable permit program could work similarly to the SO2 program. However, significant differences exist between acid rain and possible global warming that affect current abilities to model responses. For example, the acid rain program involves up to 3,000 new and existing electric generating units that contribute two-thirds of the country’s SO2. This concentration of sources makes the logistics of allowance trading administratively manageable and enforceable. The imposition of the allowance requirement is straightforward. The acid rain program is a “downstream” program focused on the electric utility industry. The allowance requirement is imposed at the point of SO2 emissions so the participant has a clear price signal to respond to. The basic dynamic of the program is simple, although not necessarily predictable. A comprehensive greenhouse gas cap-and-trade program would not be as straightforward to implement. Greenhouse gas emissions sources are not concentrated. Although over 80% of the greenhouse gases generated comes from fossil fuel combustion, only about 33% comes from electricity generation. Transportation accounts for about 26%, direct residential and commercial use about 8%, agriculture about 6%, and direct industrial use about 16%.28 Thus, small dispersed sources in transportation, residential/commercial, agriculture, and the industrial sectors are far more important in controlling greenhouse gas emissions than they are in controlling SO2 emissions. This greatly increases the economic sectors and individual entities that may be required to reduce emissions. It also affects the operation of a cap-and-trade program, as the diversity of sources creates significant administrative and enforcement problems for a tradeable permit program if it is meant to be comprehensive. A downstream approach is impractical for a comprehensive greenhouse gas program where the transportation sector and dispersed residential, commercial, and agricultural sources emit almost half the total emissions. One alternative is to move the imposition point more “upstream” in those sectors, as is done by S. 2191. This complicates the economics of the program as the price signal has to work its way through multiple paths to the particular entities— utilities, consumers, industry—that are the ultimate sources of the greenhouse gases. Arguably, 27 U.S. Environmental Protection Agency, EPA Analysis of the Lieberman-Warner Climate Security Act of 2008 (March 14, 2008), pp. 96-102, 108-115. 28 U.S. Environmental Protection Agency, U.S. Inventory of Greenhouse Gas Emissions and Sinks: 1990-2006 (April 2008), p. ES-8. ˜—›Žœœ’˜—Š•ȱŽœŽŠ›Œ‘ȱŽ›Ÿ’ŒŽȱ ŗśȱ •’–ŠŽȱ‘Š—ŽDZȱ˜œœȱŠ—ȱŽ—Ž’œȱ˜ȱǯȱŘŗşŗȦǯȱřŖřŜȱ ȱ the primary purpose of an economic mechanism, such as a cap-and-trade program, is to put a price on greenhouse gas emissions. In the case of a comprehensive cap-and-trade program, the impact of that price signal will not be simple or straightforward, with unintended consequences likely.29 In addition, attempts by analysts to capture the general equilibrium effects of the program’s interaction with the overall economy add a layer of assumptions and opaqueness to the analysis that can hide insights the analysis may have on program design and implementation. •Ž¡’‹’•’¢ȱ˜ȱŠ™ȬŠ—Ȭ›ŠŽȱ›˜›Š–ȱ The flexibility envisioned by most cap-and-trade programs exceeds that of the SO2 program. Acid rain is a regional problem that resulted in independent responses by the United States and Canada. The United States chose a cap-and-trade program that included important flexibility mechanisms like banking; Canada chose a variety of approaches and the entire process was later codified by treaty. Offsets (emission reductions made by entities not directly covered by the program) are not a major component of the SO2 program. Uncovered industrial entities that want to participate in the program must become covered entities with their own baselines and monitoring equipment. The bill also sets up a small reserve of allowances to reward reductions through conservation and renewable energy efforts. With the sulfur dioxide cap-and-trade system being limited to the United States, there is no international trading in the acid rain program. In contrast, most GHG cap-and-trade proposals expand the supply of available allowances by permitting offsets from a wide variety of sources, including agricultural practices, forestry projects, sequestration activities, and alternative energy projects. These diverse sources multiply as the trading extends globally and as other non-CO2 greenhouse gases are included in the supply mix. Finally, the interaction of these various supply sources and the demand of other countries also reducing emissions (or who may decide to reduce in the future) provide for an almost infinite number of possible scenarios. Crucially, the availability of offsets may have a significant impact on compliance costs, particularly in the short-term. –™˜›Š—ŒŽȱ˜ȱŽŒ‘—˜•˜¢ȱ˜ȱžž›ŽȱŽœž•œȱ The three driver analysis illustrated the importance of reducing the greenhouse intensity of the economy to reducing overall greenhouse gas emissions. The other two drivers, population and economic growth, are generally not elements targeted for reduction under greenhouse gas reduction programs (indeed, by any federal program). The key factor in reducing the intensity driver over the long run is technology development. This is recognized in most greenhouse gas reduction bills, including S. 2191, with substantial funding, incentives, and price signals to encourage both accelerated deployment and the initiation of efforts to develop new generations of technology. The effectiveness of these initiatives and price signals would be pivotal to the ultimate cost of any reduction strategy, particularly in the long term. As stated by Houghton: 29 This is particularly true if allowances are allocated to upstream entities at no cost. See Sergey Paltsev, et al., Assessment of U.S. Cap-and-Trade Proposals, MIT Joint Program on the Science and Policy of Global Change (April 2007), p. 5. ˜—›Žœœ’˜—Š•ȱŽœŽŠ›Œ‘ȱŽ›Ÿ’ŒŽȱ ŗŜȱ •’–ŠŽȱ‘Š—ŽDZȱ˜œœȱŠ—ȱŽ—Ž’œȱ˜ȱǯȱŘŗşŗȦǯȱřŖřŜȱ ȱ Technology change is a particularly critical component of the climate change debate. For example, the cost of meeting stabilization levels is very sensitive to assumptions about future technologies. If assumed technology improvements lead to relatively low emissions, then it is relatively inexpensive to meet stabilization levels, and vice versa. Furthermore, technology research and development is a very significant policy instrument in the portfolio of options.30 —Œ›ŽŠœ’—ȱ›˜‹•Ž–œȱ ’‘ȱŽŽ›’œȱŠ›’‹žœȱ—Š•¢œ’œřŗȱ As was the case with analyses of the SO2 cap-and-trade program, current studies of greenhouse gas reduction proposals assume that in the absence of new legislation EPA would take no action in this area between now and the year 2050, and no future initiatives would be enacted in related areas, such as energy policy. This seems unlikely. Indeed, the potential for a future requirement to reduce greenhouse gas emission may already be having an effect on decisions by industry and consumers. As noted by EIA: While forecasting policy change is beyond EIA’s mandate, an argument can be made that, all else being equal, public and industry awareness of climate change as a major policy issue can potentially impact energy investment decisions even if no specific policy change actually occurs. Any adjustment to reflect the influence of climate change as an unresolved policy issue, while raising costs in the Reference Case, would generally reduce the estimated incremental impact resulting from the full implementation of a given policy response.32 ‘Š—’—ȱŠœŽ•’—Žœȱ¢ȱ‘Š—’—ȱŠ œȱ That the policy baseline for greenhouse gas emissions can be shifted significantly through new initiatives has already been illustrated by enactment of the 2007 Energy Independence and Security Act (EISA). On December 19, 2007, President Bush signed EISA (P.L. 110-140). EISA contains many energy provisions that could lead to reductions in greenhouse gas emissions, including33 • more stringent fuel economy (CAFE) standards for passenger cars and light trucks; • higher efficiency standards for appliances and lighting; • higher efficiency requirements for government buildings; and • research and development on renewable energy. The American Council for an Energy-Efficient Economy estimates that the efficiency provisions in EISA will save roughly 700 million metric tons of carbon dioxide annually by 2030.34 Most of this savings would come from tighter CAFE standards. 30 John Houghton, “Introduction,” Energy Economics 28 (2006), p. 535. From Latin, roughly meaning all else being held the same. In analysis, this refers to the practice of holding certain variables constant to isolate the effect of the variable being analyzed. 32 Energy Information Administration, Energy Market and Economic Impact of S. 2191, the Lieberman-Warner Climate Security Act of 2007 (April 2008) p. viv. 33 For more information on EISA, see CRS Report RL34294, Energy Independence and Security Act of 2007: A Summary of Major Provisions, by (name redacted). 31 ˜—›Žœœ’˜—Š•ȱŽœŽŠ›Œ‘ȱŽ›Ÿ’ŒŽȱ ŗŝȱ ȱ •’–ŠŽȱ‘Š—ŽDZȱ˜œœȱŠ—ȱŽ—Ž’œȱ˜ȱǯȱŘŗşŗȦǯȱřŖřŜȱ In addition to these indirect reductions, EISA also directly addresses climate change issues in several ways. First, EISA expands the renewable fuel standard (RFS) established in P.L. 109-58. The EISA amendments to the RFS significantly expand the mandated level. Further, the new law requires that an increasing share of the RFS be met with “advanced biofuels,” defined as having 50% lower lifecycle greenhouse gas emissions than petroleum fuels. Further, conventional biofuels from new refineries must have at least 20% lower lifecycle emissions. This is the first time that Congress has enacted national policy addressing the carbon content of motor fuels. Second, Title VII of the new law focuses on research, development, and demonstration of technologies to capture and store carbon dioxide. DOE carbon storage R&D is expanded and is to include large-scale demonstration projects. The Department of the Interior must develop a methodology to assess the national potential for geologic and ecosystem storage of carbon dioxide, and must recommend a regulatory framework for managing geologic carbon sequestration on public lands. In addition to the above programs, EISA also requires the establishment of an Office of Climate Change and Environment in the Department of Transportation (DOT). This office is to plan, coordinate, and implement research at DOT on reducing transportation-related energy use, mitigating the causes of climate change, and addressing the impacts of climate change on transportation. The practical result of this is the necessary re-working of EIA’s AEO 2008 baseline to reflect the energy and environmental impact of the new laws. More changes are likely over the 40-year time frame of S. 2191. ‘Š—’—ȱŠœŽ•’—Žœȱ¢ȱ‘Š—’—ȱŽž•Š’˜—řśȱ The stringency of the SO2 cap-and-trade is being changed by EPA’s Clean Air Interstate Rule (CAIR). The baseline may also be influenced by future EPA initiatives not requiring new authority. The Clean Air Act is a powerful tool that could be used to regulate emissions of greenhouse gases from mobile sources of all kinds, their fuels (with the exception of jet fuel), and both large and small stationary sources. The possibility for regulation through existing Clean Air Act authority was recently outlined by EPA in congressional testimony.36 The key to such regulation is that the EPA Administrator issue appropriate findings on whether greenhouse gases “contribute to air pollution that is reasonably anticipated to endanger public health or welfare.” It is difficult, bordering on impossible, to determine where such a finding would lead. The Administrator has substantial discretion in defining what emission limits should be set once he or she makes such a finding, and what sections of the act he or she might (...continued) 34 American Council for an Energy-Efficient Economy, Energy Bill Savings Estimates as passed by the Senate (December 14, 2007). 35 This section prepared by James McCarthy, Specialist in Environmental Policy. 36 Robert J. Meyers, Principal Deputy Assistant Administrator, Office of Air and Radiation, U.S. Environmental Protection Agency, Testimony before the Subcommittee on Energy and Air Quality, Committee on Energy and Commerce, U.S. House of Representatives (April 10, 2008). ˜—›Žœœ’˜—Š•ȱŽœŽŠ›Œ‘ȱŽ›Ÿ’ŒŽȱ ŗŞȱ ȱ •’–ŠŽȱ‘Š—ŽDZȱ˜œœȱŠ—ȱŽ—Ž’œȱ˜ȱǯȱŘŗşŗȦǯȱřŖřŜȱ use. Greenhouse gases could be defined as criteria air pollutants, or not. They could be controlled in mobile sources of all kinds. They could be subject to New Source Performance Standards (NSPS), Prevention of Significant Deterioration (PSD), or Maximum Available Control Technology (MACT) requirements. Each of these has its own standard-setting process and criteria. To some extent, the important question may be how an Administrator would define the source categories. If all power plants were considered in the same category, then the act’s authority could be used to require the use of natural gas or cleaner fuels (or at least to set emission standards based on the emissions from plants using such fuels). If coal-fired plants were their own category or a technological approach were taken, the best technology could be carbon capture and storage (CCS). How the sources would be categorized would be at the discretion of the Administrator. The Administrator would also get to make technical judgments concerning whether technologies were “available” or “achievable.” These judgments could be crucial in determining how much technology-forcing the regulations would do. ŽŠœž›’—ȱ‘Žȱ˜’œŽDZȱȱŽ‹ȱ˜ȱ˜œȱŽŠœž›Žœȱ Because of the economic complexities and interactions noted above, analysts have generally chosen to focus on estimating the macro-economic effects of proposals, such as GDP impacts. There are two components of macro-economic cost measures: (1) the direct abatement (or compliance) cost of a greenhouse gas reduction program, and (2) the general equilibrium effects of a greenhouse gas reduction program (i.e., the interactions of the direct abatement costs with the rest of the economy). The most common measure presented is Gross Domestic Product (GDP). GDP measures the total value of goods and services produced within a nation’s borders.37 Although it is commonly used as a measure of quality of life, this application is problematic. Generally, it includes only those items for which there is a value defined in a market, and does not take into account some activities that have economic value, but no market valuation (e.g., leisure time, environmental quality, etc.). GDP is intended to be a measure of economic activity, not quality of life. A second measure sometimes presented is consumption effects (sometimes called welfare effects). Unfortunately, the models do not measure consumption or welfare effects in a consistent fashion (the primary advantage of measuring GDP). For example, the MIT/EPPA analysis presents “welfare effects” in terms of changes in aggregate market consumption plus leisure. Measured as “equivalent variation,” the change in welfare represents the amount of income needed to compensate for the change. In contrast, the EIA/NEMS model presents “real consumption impacts” in terms of consumer expenditures. This makes comparisons difficult and lessens the utility of the measure. For example, when analyzing proposed legislation, the “welfare effects” of legislation under the MIT/EPPA are usually less than the GDP effects, while the “real consumption impacts” under EIA/NEMS are usually greater than the GDP effects on a percentage 37 It has four basic components: private consumption (including most personal expenditures of households); investments by business and households in capital (including new house purchases); government expenditures on goods and services (but not transfer payments, such as Social Security); and net imports. ˜—›Žœœ’˜—Š•ȱŽœŽŠ›Œ‘ȱŽ›Ÿ’ŒŽȱ ŗşȱ ȱ •’–ŠŽȱ‘Š—ŽDZȱ˜œœȱŠ—ȱŽ—Ž’œȱ˜ȱǯȱŘŗşŗȦǯȱřŖřŜȱ basis. In addition, like GDP, none of the definitions of consumption or welfare currently employed quantify any environmental effects. A third measure generally presented is allowance prices. These generally reflect to some degree the aggregate marginal cost of the program as estimated by the models. Marginal cost is the cost of reducing the last ton (and, therefore, the most expensive) of greenhouse gases required by the program at a specific point in time. Marginal costs are very useful to affected entities in choosing what reduction strategy would be the most cost-effective in achieving their assigned reduction requirement. They are not an average cost and therefore cannot be simply multiplied by the greenhouse gases reduced to estimate total compliance cost. They also need to be put into the context of the overall reduction achieved at the given point and time being examined. However, allowance prices in most analyses are actually different from marginal costs because of program provisions, such as banking. Banking activity reflects the assumed foresight of affected entities to the likelihood of increasing allowance prices (in real terms) as the cap tightens. As indicated by the experience with the SO2 program, entities will bank substantial allowances early and use them later as the program’s requirements tighten. This results in allowance prices being higher than marginal costs in the early years of the program, and lower in later years. For example, the NMA/CRA International analysis of S. 2191 has a 2050 allowance price of about $352 under “no banking” assumptions, but an allowance price of about $195 with banking. In contrast, 2015 allowance prices are estimated at $51 for the “banking” scenario, but only $38 under the no banking scenario.38 This ability to time-shift reduction requirements and compliance costs means that allowance price projections reflect the assumed foresight of affected entities as much as they do actual marginal costs. In presenting cost measures, most analyses over-emphasize aggregate welfare indicators, such as GDP. As illustrated above, aggregate, macroeconomic cost results for S. 2191 fall into the noise of uncertainty about future conditions. In addition, aggregate macroeconomic measures reduce the transparency of the analyses’ compliance strategies, and as a result, make them easier to dismiss. For example, Figure 1 below shows a 1997 scatter-plot by World Resources Institute (WRI) of 162 predicted impacts estimates from 16 different economic models of the U.S. economy as a result of a CO2 abatement program. As indicated, the vast majority of estimates fall with a range of 0%-4% of GDP, regardless of the reduction requirement. Over-emphasis on GDP or other aggregate cost measures can obscure fundamental technological, economic, or behavioral insights the analyses may have in helping policymakers craft legislation. Instead, the analysis becomes a “black box” exercise with little enlightenment function. 38 W. David Montgomery and Anne E. Smith, Economic Analysis of the Lieberman-Warner Climate Security Act of 2007 Using CRA’s MRN-NEEM Model, CRA International (April 8, 2008) p. 18. Prices are in 2007$. ˜—›Žœœ’˜—Š•ȱŽœŽŠ›Œ‘ȱŽ›Ÿ’ŒŽȱ ŘŖȱ •’–ŠŽȱ‘Š—ŽDZȱ˜œœȱŠ—ȱŽ—Ž’œȱ˜ȱǯȱŘŗşŗȦǯȱřŖřŜȱ ȱ Figure 1. Predicted Impacts of Carbon Abatement on the U.S. Economy (162 Estimates from 16 Models) Source: Robert Repetto and Duncan Austin, The Costs of Climate Protection: A Guide for the Perplexed, World Resources Institute, 1997. This “fog” is inherent when analysts choose to include the general equilibrium effects of a program in their cost measure—a fog that can limit the explanatory value of the analysis. While supporting use of aggregate welfare cost measures, MIT notes: GE [general equilibrium] effects can stem from interactions with pre-existing distortions (e.g., taxes), from externally induced terms-of-trade effects, from the fact that the domestic policy itself creates terms-of-trade effects, and from other rigidities in the economy. Many aspects of model structure produce GE effects that are not easy to separately measure because of the inherent interactions in the economy.39 39 Sergey Paltsev, et al., Assessment of U.S. Cap-and-Trade Proposals, MIT Joint Program on the Science and Policy of Global Change (April 2007), p. 27. ˜—›Žœœ’˜—Š•ȱŽœŽŠ›Œ‘ȱŽ›Ÿ’ŒŽȱ Řŗȱ ȱ •’–ŠŽȱ‘Š—ŽDZȱ˜œœȱŠ—ȱŽ—Ž’œȱ˜ȱǯȱŘŗşŗȦǯȱřŖřŜȱ Generally, the cases examined here have not chosen to separate the two components of macroeconomic cost measures: (1) the direct abatement (or compliance) cost of a greenhouse gas reduction program, and (2) the general equilibrium effects of a greenhouse gas reduction program (i.e., the interactions of the direct abatement costs with the rest of the economy).40 The availability of compliance cost estimates would allow policymakers to put current greenhouse gas reduction proposals in the context of other environmental initiatives—be they acid rain or toxic air pollutants—and, indeed, to the overall environmental agenda, and greatly increase the transparency of the analyses’ insights. It would also help relieve confusion between compliance costs, average costs (per ton reduced), and the other commonly presented costs, such as allowance prices.41 It is argued that an aggregate macroeconomic cost measure provides a more complete view of the economic impact of proposed legislation, and helps identity potential unintended economic effects of compliance strategies. This may be true, particularly if, for example, auction revenues are being recycled via a reformed tax code. However, as indicated here, aggregated macroeconomic cost measures, such as GDP, can also be interpreted to merely show that the United States has a massive economy that can absorb substantial shocks with limited long-term effect. ‘›ŽŽȱŽ›œ™ŽŒ’ŸŽœDZȱ Ž’—ȱžȱ˜ȱ‘Žȱ˜’œŽȱ Breaking through the fog of analyses and cost indicators, cost estimates to reduce CO2 emissions vary greatly and focus attention on an estimator’s basic beliefs about the problem and the future, in addition to simple, technical differences in economic assumptions. In a previous report, CRS identified three “lenses” through which people can view the global climate change issues, and their influence on cost analysis.42 These are summarized in Table 6. None of these perspectives is inherently more “right” or “correct” than another; rather, they overlap and to varying degrees complement and conflict with one another. People generally hold to each of the lenses to some degree. 40 The compliance cost estimates provided by EPA in its analyses are flawed. As noted by EPA, they are overestimates of actual costs. Worse, the overestimation increases as the tonnage reduction requirement and marginal costs increase. NMA/CRA provides an estimate of the net present value of S. 2191’s total costs. 41 For a good discussion of the confusion that can arise from mixing cost measures, see Anne E. Smith, Jeremy Platt, and A. Denny Ellerman, “The Cost of Reducing SO2 (It’s Higher Than You Think),” Public Utilities Fortnightly (May 15, 1998), pp. 22-29. 42 CRS Report 98-738, Global Climate Change: Three Policy Perspectives, by (name redacted) and (name redacted). ˜—›Žœœ’˜—Š•ȱŽœŽŠ›Œ‘ȱŽ›Ÿ’ŒŽȱ ŘŘȱ •’–ŠŽȱ‘Š—ŽDZȱ˜œœȱŠ—ȱŽ—Ž’œȱ˜ȱǯȱŘŗşŗȦǯȱřŖřŜȱ ȱ Table 6. Influence of Climate Change Perspectives on Policy Parameters Approach Seriousness of problem Technology Is agnostic on the merits of the problem. The focus is on developing new technology that can be justified from multiple criteria, including economic, environmental, and social perspectives. Economic Understands issue in terms of quantifiable cost-benefit analysis. Generally assumes the status quo is the baseline from which costs and benefits are measured. Unquantifiable uncertainty tends to be ignored. Ecological Understands issues in terms of their potential threat to basic values, including ecological viability and the well-being of future generations. Such values reflect ecological and ethical considerations; adherents see attempts to convert them into commodities to be bought and sold as trivializing the issue. Risk in developing mitigation program Believes any reduction program should be designed to maximize opportunities for new technology. Risk lies in not developing technology by the appropriate time. Focus on research, development, and demonstration; and on removing barriers to commercialization of new technology. Believes that economic costs should be examined against economic benefits in determining any specific reduction program. Risk lies in imposing costs in excess of benefits. Any chosen reduction goal should be implemented through economic measures such as tradeable permits or emission taxes. Rather than economic costs and benefits or technological opportunity, effective protection of the planet’s ecosystems should be the primary criterion in determining the specifics of any reduction program. Focus of program should be on altering values and broadening consumer choices. Costs Viewed from the bottom-up. Tends to see significant energy inefficiencies in the current economic system that currently available (or projected) technologies can eliminate at little or no overall cost to the economy. Viewed from the top-down. Tends to see a gradual improvement in energy efficiency in the economy, but significant costs (usually quantified in terms of GDP loss) resulting from global climate change control programs. Typical loss estimates range from 0-4% of GDP. Views costs from an ethical perspective in terms of the ecological values that global climate change threatens. Believes that values such as intergenerational equity should not be considered commodities to be bought, sold, or discounted. Costs are defined broadly to include aesthetic and environmental values that economic analysis cannot readily quantify and monetize. However, different combinations of these perspectives lead to very different cost estimates. A classic example of this is the contrast between the S. 2191 results obtained by the Clean Air Task Force (CATF) and the American Council for Capital Formation/National Association of Manufacturers (ACCF/NAM) using the same model: EIA’s NEMS model. Table 7 summarizes the general approach of the two analyses according to the three perspectives identified above. In its analysis, CATF expresses confidence in S. 2191‘s various technology and efficiency provisions and models the bill assuming EIA’s Best Available Technology (BAT) case, banking, and offsets. In contrast, ACCF/NAM states that it is “unlikely” that technology, new energy sources, and market mechanisms (e.g., carbon offsets, banking) will be sufficiently available to achieve S. 2191‘s emission targets. Accordingly, ACCF/NAM’s assumptions differ substantially from CATF’s and other studies by excluding banking, significantly capping the availability of various technologies, and assuming higher construction costs. ˜—›Žœœ’˜—Š•ȱŽœŽŠ›Œ‘ȱŽ›Ÿ’ŒŽȱ Řřȱ •’–ŠŽȱ‘Š—ŽDZȱ˜œœȱŠ—ȱŽ—Ž’œȱ˜ȱǯȱŘŗşŗȦǯȱřŖřŜȱ ȱ . General Perspective of CATF and ACCF/NAM Cost Assumptions Table 7 CATF ACCF/NAM-Low ACCF/NAM- Technology Assumes no constraints on technology availability beyond those embedded in NEMS Economic Assumes efficient decisionmaking via banking and offsets (30%) as allowed in S. 2191 Ecological Assumes decisions made in favor of efficiency over price because of S. 2191 incentives and regulations Assumes significant constraints on technology availability and higher costs than those embedded in NEMS Assumes short-term decision-making with no banking; amount of offsets allowed “greater than 20%” None—total GHG emissions reduction estimates not presented Assumes substantial constraints on technology availability and higher costs than those embedded in NEMS Assumes short-term decision-making with no banking; offsets constrained to 15%-20% None—total GHG emissions reduction estimated not presented High CRS analysis of: Jonathan Banks, Clean Air Task Force, The Lieberman-Warner Climate Security Act— S. 2191: A Summary of Modeling Results from the National Energy Modeling System (February 2008); Science Applications International Corporation, Analysis of The Lieberman-Warner Climate Security Act (S. 2191) Using the National Energy Modeling System (NEMS), a report by the American Council for Capital Formation and the Source: National Association of Manufacturers (2008). As indicated by Table 8, the widely different cost assumptions provided the expected results, although all three analyses remained in the 0-4% GDP range common for greenhouse gas reduction analysis. Allowance price estimates are widely different, but this cost measure tends to exaggerate differences between results and should not be confused with average costs or program costs. This is particularly true in this case, as ACCF/NAM did not publish its environmental results in terms of greenhouse gases reduced; thus, one can not compare the allowance price with what is being reduced over time. Unfortunately, the analyses do not present sufficient sensitivity analysis and other information to determine whether it is the economic assumptions (e.g., banking and offset availability), the behavioral assumptions (e.g., BAT), the technology assumptions (e.g., availability), or just the higher cost assumptions of the ACCF/NAM analysis that explains the difference in allowance prices. . Selected Results from CATF and ACCF/NAM Analyses Table 8 GDP per capita Reduction 2020a GDP per capita Reduction 2030a Allowance Price 2020 (2005$) Allowance Price 2030 (2005$) Greenhouse Gas Emissions 2020 (MMTCO2e) Greenhouse Gas Emissions 2030 (MMTCO2e) CATF ACCF/NAM-Low ACCF/NAM-High not discernable from graph 0.9% about $21 about $45 about 5.5 (not including set-asides) about 5.4 (not including set-asides) 0.8% 1.1% 2.6% $52 $216 not published 2.7% $61 $258 not published not published not published Source: Jonathan Banks, Clean Air Task Force, The Lieberman-Warner Climate Security Act—S. 2191: A Summary of Modeling Results from the National Energy Modeling System (February 2008); Science Applications International ˜—›Žœœ’˜—Š•ȱŽœŽŠ›Œ‘ȱŽ›Ÿ’ŒŽȱ ŘŚȱ •’–ŠŽȱ‘Š—ŽDZȱ˜œœȱŠ—ȱŽ—Ž’œȱ˜ȱǯȱŘŗşŗȦǯȱřŖřŜȱ ȱ Analysis of the Lieberman-Warner Climate Security Act (S. 2191) Using the National Energy Modeling System (NEMS), a report by the American Council for Capital Formation and the National Association of Manufacturers (2008). All estimates converted to 2005 dollars using the GDP implicit price deflator. a. Reduction is relative to the model’s reference case baseline for 2020 and 2030. Corporation, Some attempts have been made to sort out the importance of various assumptions in analyzing the costs of greenhouse gas reduction proposals, beginning with Repetto and Austin’s effort for the World Resources Institute (WRI) in 1997, with more recent efforts by Barker, Qureshi and Kohler in 2006 and Barker and Jenkins in 2007.43 Indeed, Dr. Repetto has set up a website where people may answer seven key questions about the cost and benefit assumptions they feel are most reasonable and find out how their choices would affect GDP.44 Through meta-analysis of the results from multiple independent studies, the role of various assumptions and methodologies are quantified.45 In general, these studies found seven underlying assumptions affecting results: (1) the efficiency of the economic response;46 (2) availability of non-carbon technology;47 (3) availability of the Kyoto mechanisms;48 (4) method of revenue recycling; (5) method of incorporating technological advancements; (6) inclusion of non-climate-related environmental benefits; and (7) inclusion of climate-related benefits. As none of the models reviewed in this report quantify any environmental benefits in their analyses, all models’ results can be considered “worst-case” scenarios. Žœž•œȱ˜›ȱǯȱŘŗşŗȱ –™ŠŒȱ˜—ȱ ›ŽŽ—‘˜žœŽȱ Šœȱ–’œœ’˜—œȱ Figure 2 and Figure 3 present greenhouse gas emissions under S. 2191 as estimated by the ten cases, relative to their baseline assumptions. The range might seem surprising, given the emission cap defined in the bill. The cause of the range is largely two-fold: (1) estimated emissions growth in the 10%-15% of the economy not covered under the bill, (2) estimated use of international credits to meet emission reduction requirements that do not reduce domestic emissions. 43 Robert Repetto and Duncan Austin, The Costs of Climate Protection: A Guide for the Perplexed, World Resources Institute (1997); Terry Barker, Mahvash Saeed Qureshi, and Jonathan Kohler, The Costs of Greenhouse Gas Mitigation with Induced Technological Change: A Meta-Analysis of Estimates in the Literature, Tyndall Centre for Climate Change Research (July 2006); and Terry Barker and Katie Jenkins, The Costs of Avoiding Dangerous Climate Change: Estimates Derived from a Meta-Analysis of the Literature, A Briefing Paper for the Human Development Report 2007 (May 2007). 44 http://www.climate.yale.edu/seeforyourself/. 45 As defined by Repetto on the “See For Yourself” website: “The meta-analysis was based on more than 1,400 policy simulations performed with the various models. It used statistical regression analysis to ascribe differences among models in the predicted economic cost of a given percentage reduction of greenhouse gas emissions to differences among models in specific assumptions. Though some of the models related only to the U.S. economy, others to the world economy, the meta-analysis found that both sets of models produced the same results.” 46 In this regard, Computable General Equilibrium Models (CGE) generally assume efficient economic responses to programs while macroeconomic models allow time for the economy to adjust, resulting in higher short-term costs. 47 Some models include a “backstop” technology in unlimited amounts at a specified high price. 48 Credits from the Clean Development Mechanism (CDM) and Joint Implementation (JI). ˜—›Žœœ’˜—Š•ȱŽœŽŠ›Œ‘ȱŽ›Ÿ’ŒŽȱ Řśȱ •’–ŠŽȱ‘Š—ŽDZȱ˜œœȱŠ—ȱŽ—Ž’œȱ˜ȱǯȱŘŗşŗȦǯȱřŖřŜȱ ȱ Figure 2.Total Estimated Greenhouse Gas Emissions Under S. 2191 13000 GHG Emissions (MMT CO2 eq.) 11000 9000 7000 5000 3000 2010 2020 2030 2040 Reference Cases EPA/ADAGE-REF EPA/ADAGE-TECH EPA/IGEM-REF EPA/IGEM-TECH CATF/NEMS EIA/NEMS MIT/EPPA NMA/CRA S. 2191 Cases EPA/ADAGE-REF EPA/ADAGE-TECH EPA/IGEM-REF EPA/IGEM-TECH CATF/NEMS EIA/NEMS MIT/EPPA NMA/CRA 2050 EPA/ADAGE and EPA/IGEM: “Data Annex” available on the EPA website at http://www.epa.gov/ climatechange/economics/economicanalyses.html MIT/EPPA: Sergey Paltsev, et al., “Appendix D” of Paltsev et al., Assessment of U.S. Cap-and-Trade Proposals, MIT Joint Program on the Science and Policy of Global Change (2007). EIA/NEMS: EIA, Energy Market and Economic Impacts of S. 2191, the Lieberman-Warner Climate Security Act of 2007 (April 2008). CATF/NEMS: Jonathan Banks, Clean Air Task Force, The Lieberman-Warner Climate Security Act—S. 2191: A Summary of Modeling Results from the National Energy Modeling System (February 2008). ACCF/NAM/NEMS: SAIC, Analysis of the Lieberman-Warner Climate Security Act (S. 2191) Using the National Energy Modeling System (NEMS), report by the ACC. and NAM (2008). NMA/CRA: CRA International, Economic Analysis of the Lieberman-Warner Climate Security Act of 2007 Using CRA’s MRN-NEEM Model (April 8, 2008). Estimates extrapolated by CRS from available data where necessary. Sources: ˜—›Žœœ’˜—Š•ȱŽœŽŠ›Œ‘ȱŽ›Ÿ’ŒŽȱ ŘŜȱ •’–ŠŽȱ‘Š—ŽDZȱ˜œœȱŠ—ȱŽ—Ž’œȱ˜ȱǯȱŘŗşŗȦǯȱřŖřŜȱ ȱ .Total Estimated Greenhouse Gas Emissions from Each Model Under S. 2191 13000 13000 11000 11000 GHG Emissions (MMT CO2 eq.) GHG Emissions (MMT CO2 eq.) Figure 3 9000 7000 5000 3000 2030 2040 2050 5000 2010 2030 2040 EPA/ADAGE-REF EPA/ADAGE-TECH Reference Cases EPA/IGEM-REF EPA/IGEM-TECH S. 2191 Cases EPA/ADAGE-REF EPA/ADAGE-TECH S. 2191 Cases EPA/IGEM-REF EPA/IGEM-TECH 13000 13000 11000 11000 9000 7000 5000 2010 2020 Reference Cases 3000 ȬŘŝȱ 7000 3000 2020 GHG Emissions (MMT CO2 eq.) GHG Emissions (MMT CO2 eq.) 2010 9000 2050 9000 7000 5000 3000 2020 2030 Reference Cases CATF/NEMS S. 2191 Cases CATF/NEMS 2040 2050 2010 2020 2030 2040 EIA/NEMS Reference Cases MIT/EPPA NMA/CRA EIA/NEMS S. 2191 Cases MIT/EPPA NMA/CRA 2050 •’–ŠŽȱ‘Š—ŽDZȱ˜œœȱŠ—ȱŽ—Ž’œȱ˜ȱǯȱŘŗşŗȦǯȱřŖřŜȱ ȱ The most stringent interpretation of S. 2191’s emissions cap is by NMA/CRA. The resulting emissions estimates could be attributed to three factors: (1) NMA/CRA does not allow any international credits to be used to achieve reductions, (2) NMA/CRA uses the preliminary AEO 2008 baseline, which may project lower emissions growth by non-covered sectors because of EISA or other factors; and (3) NMA/CRA also analyzes the effect of the bill’s proposed Low Carbon Fuel Standard, which reduces emissions further, as discussed later. The highest emissions permitted under the bill are estimated by the two EPA/ADAGE cases. This higher emissions level is probably the result of the substantial use of international credits and percentage of uncovered entities assumed by ADAGE. Interestingly, the two ACCF/NAM/NEMS cases do not present any estimates of their total greenhouse gas emissions baseline, or the reduction calculated by their analysis. The closest they come to presenting emissions reductions is a chart with assumed increases in energy-related CO2 emissions and their interpretation of the reductions S. 2191 would require on the energy sector. –™ŠŒȱ˜—ȱ˜—Ȭ ›ŽŽ—‘˜žœŽȱ Šœȱ–’œœ’˜—œȱ The only estimates of non-greenhouse gas emission reductions under S. 2191 are provided by EPA/IPM. Those projections are for the electric power sector only, assume implementation of the Clean Air Interstate Rule (CAIR) rule (currently in litigation), and only go to 2025. The projections also reflect the interaction of CO2 reductions with the banking provisions of the Acid Rain and CAIR rules. This interaction results in the short-term changes (to 2015) in emissions being overstated. As indicated in Table 9 below, one-third of the SO2 reductions and one-sixth of the NOx reductions are achieved in the last year of the projection. EPA/IPM also projected mercury emissions reductions; however, they were done in the context of the now-vacated mercury rule.49 This eliminated their utility for this analysis. Table 9. EPA/IPM Reduction of Conventional Air Pollutants from Electric Utilities Reduction from Reference Case: 2025 (short tons) Cumulative Reduction from Reference Case 2010-2025 (short tons) Sulfur Dioxide 1,064,000 3,000,000 Nitrogen Oxides 848,000 4,900,000 S. 2191 –™ŠŒȱ˜—ȱ ȱŽ›ȱŠ™’Šȱ Figure 4 and Figure 5 present the estimated GDP per capita in the baseline and S. 2191 scenarios for the various cases. As suggested by the discussion of “noise” earlier, uncertainty about the basecase assumptions absorbs the impact of S. 2191. Indeed, they are so intertwined as to make the results nearly meaningless in one sense. In another sense, the figures indicate the models’ expectations that the economy continues to growth under S. 2191, albeit at a slower rate than under their respective reference cases. 49 For more information on the court decision, see CRS Report RS22817, The D.C. Circuit Rejects EPA’s Mercury Rules: New Jersey v. EPA, by (name redacted) and (name redacted). ˜—›Žœœ’˜—Š•ȱŽœŽŠ›Œ‘ȱŽ›Ÿ’ŒŽȱ ŘŞȱ •’–ŠŽȱ‘Š—ŽDZȱ˜œœȱŠ—ȱŽ—Ž’œȱ˜ȱǯȱŘŗşŗȦǯȱřŖřŜȱ ȱ Figure 4. GDP per Capita (2005$) Under S. 2191 $110,000 GDP per Capita (2005$) $100,000 $90,000 $80,000 $70,000 $60,000 $50,000 $40,000 2010 2020 2030 2040 Reference Cases EPA/ADAGE-REF EPA/ADAGE-TECH EPA/IGEM-REF EPA/IGEM-TECH CATF/NEMS ACCF/NAM/NEMS-HIGH ACCF/NAM/NEMS-LOW EIA/NEMS MIT/EPPA NMA/CRA S. 2191 Cases EPA/ADAGE-REF EPA/ADAGE-TECH EPA/IGEM-REF EPA/IGEM-TECH CATF/NEMS ACCF/NAM/NEMS-HIGH ACCF/NAM/NEMS-LOW EIA/NEMS MIT/EPPA NMA/CRA 2050 EPA/ADAGE and EPA/IGEM: “Data Annex” available on the EPA website at http://www.epa.gov/ climatechange/economics/economicanalyses.html MIT/EPPA: Sergey Paltsev, et al., “Appendix D” of Paltsev et al., Assessment of U.S. Cap-and-Trade Proposals, MIT Joint Program on the Science and Policy of Global Change (2007). EIA/NEMS: EIA, Energy Market and Economic Impacts of S. 2191, the Lieberman-Warner Climate Security Act of 2007 (April 2008). CATF/NEMS: Jonathan Banks, Clean Air Task Force, The Lieberman-Warner Climate Security Act— S. 2191: A Summary of Modeling Results from the National Energy Modeling System (February 2008). ACCF/NAM/NEMS: SAIC, Analysis of the Lieberman-Warner Climate Security Act (S. 2191) Using The National Energy Modeling System (NEMS), report by the ACC. and NAM (2008). NMA/CRA: CRA International, Economic Analysis of the Lieberman-Warner Climate Security Act of 2007 Using CRA’s MRN-NEEM Model (April 8, 2008). Estimates extrapolated by CRS from available data where necessary. Estimates converted to 2005$ using GDP implicit price deflator. Sources: ˜—›Žœœ’˜—Š•ȱŽœŽŠ›Œ‘ȱŽ›Ÿ’ŒŽȱ Řşȱ •’–ŠŽȱ‘Š—ŽDZȱ˜œœȱŠ—ȱŽ—Ž’œȱ˜ȱǯȱŘŗşŗȦǯȱřŖřŜȱ ȱ . GDP per Capita (2005$) from Each Model Under S. 2191 $110,000 $110,000 $100,000 $100,000 GDP per Capita (2005$) GDP per Capita (2005$) Figure 5 $90,000 $80,000 $70,000 $60,000 $50,000 $70,000 $60,000 $40,000 2010 2020 2030 2040 2050 2010 2020 2030 2040 Reference Cases EPA/ADAGE-REF EPA/ADAGE-TECH Reference Cases EPA/IGEM-REF EPA/IGEM-TECH S. 2191 Cases EPA/ADAGE-REF EPA/ADAGE-TECH S. 2191 Cases EPA/IGEM-REF EPA/IGEM-TECH $110,000 $110,000 $100,000 $100,000 GDP per Capita (2005$) GDP per Capita (2005$) $80,000 $50,000 $40,000 $90,000 $80,000 $70,000 $60,000 $50,000 2050 $90,000 $80,000 $70,000 $60,000 $50,000 $40,000 $40,000 2010 2020 2030 2040 Reference Cases CATF/NEMS ACCF/NAM/NEMS-HIGH ACCF/NAM/NEMS-LOW EIA/NEMS S. 2191 Cases CATF/NEMS ACCF/NAM/NEMS-HIGH ACCF/NAM/NEMS-LOW EIA/NEMS ȬřŖȱ $90,000 2050 2010 2020 2030 2040 Reference Cases MIT/EPPA NMA/CRA S. 2191 Cases MIT/EPPA NMA/CRA 2050 ȱ •’–ŠŽȱ‘Š—ŽDZȱ˜œœȱŠ—ȱŽ—Ž’œȱ˜ȱǯȱŘŗşŗȦǯȱřŖřŜȱ To sort the situation out a little further, Figure 6 and Figure 7 show percentage reductions in GDP per capita from S. 2191 (relative to the models’ respective reference cases) according to the ten cases presented here. With the exception of the IGEM model, all projections for all years between 2020 and 2050 fell into a range between 0.3% (EIA/NEMS for 2020 and 2030) and 2.7% (ACCF/NAM-HIGH for 2030). As indicated in Figure 6 and Figure 7, the EPA/IGEM cases produced 2050 estimates that were more than twice those of the other models. The high estimates for GDP per capita reduction by the EPA-IGEM cases result from its structure and assumptions contained in the model. For example, the assumption about the relationship between leisure and consumption in IGEM is quite different from the other models. Essentially, as prices for goods and services increase, IGEM assumes a highly responsive relationship, with people deciding to work less and buy less. As a result, a small increase in prices will produce a relatively large loss of consumption, resulting in a larger impact on GDP and other cost measures. In contrast, other models are less responsive, assuming people will absorb higher prices without changing their work or consumption habits very much.50 Other factors influencing IGEM’s results include (1) a somewhat higher emissions baseline, (2) the lack of some less carbon-emitting technological alternatives, such as carbon capture and storage, (3) a U.S.-only context that affects the model’s estimates of exports, and (4) elasticities that are calibrated based on historical data. The only year for which GDP per capita estimates were presented for all cases is 2030.51 Once again, the estimates from the IGEM model are substantially higher (3.6% and 3.8%) than the seven other cases for reasons noted above. The other cases fall into two categories. The largest category is six cases that estimate 2030 GDP effect at about 1% or less. These cases are: EPA/ADAGE-REF, EPA/ADAGE-TECH, CATF/NEMS, EIA/NEMS, MIT/EPPA, and NMA/CRA. The other category is the two ACCF/NAM/NEMS cases where the GDP effect is 2.6% and 2.7% in 2030. Thus, despite their restrictive assumptions, the ACCF/NAM/NEMS cases do not exceed the 0-4% range of GDP effects common to reduction programs. 50 See Janet Peace and John Weyant, Insights Not Numbers: The Appropriate Use of Economic Models, Pew Center on Global Climate Change (April, 2008), pp. 18-19. This is an additional warning to readers about understanding the assumptions and limitations of models. As stated later by Peace and Weyant: “The sensitivity of modeling results to a single assumption—in this case, the elasticity of substitution between consumption and leisure—also serves to illustrate that important differences between models are not always obvious. Most casual users would never dive deep enough into model documentation to ascertain that IGEM and ADAGE utilize a different assumption about the tradeoff between consumption and leisure. For this reason, it is very important that model developers (a) make transparent their assumptions and inputs (as Jorgenson, Goettle, and Poss do) and (b) to the extent possible, characterize principal sources of uncertainty in the model design and identify limitations that influence model results.” p. 20. 51 For the 2010 and 2020 estimates presented in Figures 4 and 5, CRS extrapolated the data for some of the presentations. ˜—›Žœœ’˜—Š•ȱŽœŽŠ›Œ‘ȱŽ›Ÿ’ŒŽȱ řŗȱ •’–ŠŽȱ‘Š—ŽDZȱ˜œœȱŠ—ȱŽ—Ž’œȱ˜ȱǯȱŘŗşŗȦǯȱřŖřŜȱ ȱ Figure 6. Percentage Change in GDP per Capita Under S. 2191 0% Change in GDP per Capita (%) -1% -2% -3% -4% -5% -6% -7% 2010 2020 2030 2040 EPA/ADAGE-REF EPA/ADAGE-TECH EPA/IGEM-REF EPA/IGEM-TECH CATF/NEMS ACCF/NAM/NEMS-HIGH ACCF/NAM/NEMS-LOW EIA/NEMS MIT/EPPA 2050 NMA/CRA Note: Reductions are relative to each model’s reference case baseline. EPA/ADAGE and EPA/IGEM: “Data Annex” available on the EPA website at http://www.epa.gov/ climatechange/economics/economicanalyses.html MIT/EPPA: Sergey Paltsev, et al., “Appendix D” of Paltsev et al., Assessment of U.S. Cap-and-Trade Proposals, MIT Joint Program on the Science and Policy of Global Change (2007). EIA/NEMS: EIA, Energy Market and Economic Impacts of S. 2191, the Lieberman-Warner Climate Security Act of 2007 (April 2008). CATF/NEMS: Jonathan Banks, Clean Air Task Force, The Lieberman-Warner Climate Security Act— S. 2191: A Summary of Modeling Results from the National Energy Modeling System (February 2008). ACCF/NAM/NEMS: SAIC, Analysis of the Lieberman-Warner Climate Security Act (S. 2191) Using The National Energy Modeling System (NEMS), report by the ACC. and NAM (2008). NMA/CRA: CRA International, Economic Analysis of the Lieberman-Warner Climate Security Act of 2007 Using CRA’s MRN-NEEM Model (April 8, 2008). Estimates extrapolated by CRS from available data where necessary. Estimates converted to 2005$ using GDP implicit price deflator. Sources: ˜—›Žœœ’˜—Š•ȱŽœŽŠ›Œ‘ȱŽ›Ÿ’ŒŽȱ řŘȱ •’–ŠŽȱ‘Š—ŽDZȱ˜œœȱŠ—ȱŽ—Ž’œȱ˜ȱǯȱŘŗşŗȦǯȱřŖřŜȱ ȱ . Percentage Change in GDP per Capita from Each Model Under S. 2191 0% 0% -1% -1% Change in GDP per Capita (%) Change in GDP per Capita (% Figure 7 -2% -3% -4% -5% -6% -7% 2020 2030 EPA/ADAGE-REF 2040 -4% -5% -6% 2050 2010 2020 EPA/ADAGE-TECH 2030 EPA/IGEM-REF 0% 0% -1% -1% Change in GDP per Capita (%) Change in GDP per Capita (%) -3% -7% 2010 -2% -3% -4% -5% -6% -7% 2040 2050 EPA/IGEM-TECH -2% -3% -4% -5% -6% -7% 2010 CATF/NEMS Ȭřřȱ -2% 2020 ACCF/NAM/NEMS-HIGH 2030 2040 ACCF/NAM/NEMS-LOW 2050 EIA/NEMS 2010 2020 2030 MIT/EPPA 2040 NMA/CRA 2050 ȱ •’–ŠŽȱ‘Š—ŽDZȱ˜œœȱŠ—ȱŽ—Ž’œȱ˜ȱǯȱŘŗşŗȦǯȱřŖřŜȱ ••˜ Š—ŒŽȱ›’ŒŽȱœ’–ŠŽœȱ Figure 8 and Figure 9 present the estimated allowance prices for each of the ten cases examined here. In addition, we have included the Congressional Budget Office’s estimates used in scoring S. 2191.52 It is clear from the figures that the banking assumption of the different cases has a fundamental influence on projected prices. For example, as noted earlier, the ACCF/NAM/NEMS cases do not include banking—an expressed decision by ACCF/NAM and not an inherent part of the NEMS model as evident by the CATF/NEMS and EIA/NEMS cases. This assumption has a clear effect on the trajectory of their allowance prices. In contrast, the ADAGE, IGEM, MRNNEEM, and EPPA models assume discount rates that tend to encourage banking.53 As noted earlier, banking tends to increase allowance prices in the early years of the program and lower them in the out-years. This flattening effect results in the gentler slope of the allowance price curves evident in Figure 8 and Figure 9 below for these cases. Of the 2030 estimates for the eight cases that include S. 2191‘s banking provision, four cases project allowance prices in the range of $45-$61 (CATF/NEMS, EIA/NEMS, and the two EPA/ADAGE cases) while the other four cases project allowance prices in the $73-$86 range (MIT/EPPA, NMA/CRA, and the two EPA/IGEM cases). The spread of allowance price estimates expands after 2030, as evident in the figures. 52 Congressional Budget Office. Cost Estimate: S. 2191: America’s Climate Security Act of 2007 (April 10, 2008). For a discussion of the models’ banking assumptions, see Congressional Budget Office, Cost Estimate: S. 2191: America’s Climate Security Act of 2007 (April 10, 2008), pp. 21-23. 53 ˜—›Žœœ’˜—Š•ȱŽœŽŠ›Œ‘ȱŽ›Ÿ’ŒŽȱ řŚȱ •’–ŠŽȱ‘Š—ŽDZȱ˜œœȱŠ—ȱŽ—Ž’œȱ˜ȱǯȱŘŗşŗȦǯȱřŖřŜȱ ȱ Figure 8. Projected Allowance Prices Under S. 2191 Allowance Price (2005$/MMT CO2 eq.) 300 250 200 150 100 50 0 2010 2020 2030 2040 EPA/ADAGE-REF EPA/ADAGE-TECH EPA/IGEM-REF EPA/IGEM-TECH CATF/NEMS ACCF/NAM/NEMS-HIGH ACCF/NAM/NEMS-LOW EIA/NEMS MIT/EPPA NMA/CRA CBO 2050 EPA/ADAGE and EPA/IGEM: “Data Annex” available on the EPA website at http://www.epa.gov/ climatechange/economics/economicanalyses.html MIT/EPPA: Sergey Paltsev, et al., “Appendix D” of Paltsev et al., Assessment of U.S. Cap-and-Trade Proposals, MIT Joint Program on the Science and Policy of Global Change (2007). EIA/NEMS: EIA, Energy Market and Economic Impacts of S. 2191, the Lieberman-Warner Climate Security Act of 2007 (April 2008). CATF/NEMS: Jonathan Banks, Clean Air Task Force, The Lieberman-Warner Climate Security Act— S. 2191: A Summary of Modeling Results from the National Energy Modeling System (February 2008). ACCF/NAMS/NEMS: SAIC, Analysis of The Lieberman-Warner Climate Security Act (S. 2191) Using the National Energy Modeling System (NEMS), report by the ACCF and NAM (2008). NMA/CRA: CRA International, Economic Analysis of the Lieberman-Warner Climate Security Act of 2007 Using CRA’s MRN-NEEM Model (April 8, 2008). CBO: Congressional Budget Office, Cost Estimate: S. 2191: America’s Climate Security Act of 2007 (April 10, 2008). Estimates extrapolated by CRS from available data where necessary. Estimates converted to 2005$ using GDP implicit price deflator. Sources: ˜—›Žœœ’˜—Š•ȱŽœŽŠ›Œ‘ȱŽ›Ÿ’ŒŽȱ řśȱ •’–ŠŽȱ‘Š—ŽDZȱ˜œœȱŠ—ȱŽ—Ž’œȱ˜ȱǯȱŘŗşŗȦǯȱřŖřŜȱ ȱ . Projected Allowance Prices from Each Model Under S. 2191 Figure 9 300 Allowance Price (2005$/MMT CO2 eq.) Allowance Price (2005$/MMT CO2 eq.) 300 250 200 150 100 50 0 2010 2020 2030 EPA/ADAGE-REF 2040 150 100 50 2020 EPA/ADAGE-TECH 2030 EPA/IGEM-REF 2040 2050 EPA/IGEM-TECH 300 Allowance Price (2005$/MMT CO2 eq.) Allowance Price (2005$/MMT CO2 eq.) 200 0 2010 2050 300 250 200 150 100 50 0 2010 CATF/NEMS ȬřŜȱ 250 2020 ACCF/NAM/NEMS-HIGH 2030 2040 ACCF/NAM/NEMS-LOW 2050 EIA/NEMS 250 200 150 100 50 0 2010 2020 2030 MIT/EPPA NMA/CRA 2040 CBO 2050 ȱ •’–ŠŽȱ‘Š—ŽDZȱ˜œœȱŠ—ȱŽ—Ž’œȱ˜ȱǯȱŘŗşŗȦǯȱřŖřŜȱ žŒ’˜—ȱŽŸŽ—žŽȱœ’–ŠŽœȱ None of the analyses examined were conducted after the proposed deficit reduction amendment was announced April 10, 2008.54 Therefore, CRS has provided the following estimates based on two cases: a “high” revenue case based on the MIT/EPPA study, and a “low” revenue case based on the EPA/ADAGE-TECH case (Figure 10). In each case, the auction revenue estimates are calculated by multiplying the estimated allowance price in a given year by the number of allowances auctioned by the program for deficit reduction (“Deficit Reduction Fund”) and the number of “remainder allowances” allocated for auction (“General Auction”). As the number of allowances for auction in a given year is set by the bill, the total auction revenue for that year becomes a function of the allowance price. A higher allowance price will lead to higher auction revenue. As shown in Figure 10, using the lower allowance prices in the EPA/ADAGE-TECH case, total auction revenues start in the tens of billions of dollars (2005$) and increase to over $100 billion before 2030. Using higher allowances prices, such as the MIT/EPPA case, total auction revenues exceed $100 billion before 2020. In comparison, currently the federal government spends roughly $5 billion annually for the Climate Change Science Program, the Climate Change Technology Program, and International Climate Change Assistance, combined.55 As indicated in Table 10, after the firefighting, deficit reduction, administration expenses, and other funds have been allocated, a substantial amount of auction revenue would remain available annually for technology deployment even in the low revenue EPA/ADAGE-TECH case. For example, the Advanced Technology Vehicles Manufacturing Incentive Program (Sec. 4405) would provide grants to automakers and parts manufacturers to develop the capacity to build plug-in hybrid and other advanced vehicles (and parts). Funds could be used for engineering integration of vehicles and retooling old plants to produce advanced vehicles. Using the lower allowance prices in the EPA/ADAGE-TECH case, this program would provide over $1 billion (2005$) annually in 2012, increasing to more than $7 billion by 2040. In comparison, DOE currently spends between $200 million and $400 million for advanced vehicle and hydrogen fuel R&D.56 As noted in the next section, the effectiveness of these funds in accelerating technology development and commercialization—as well as agencies’ and firms’ capacity to absorb (in some cases) very large funding increases—could have a significant effect on the overall costs of S. 2191 and the ultimate success of the program. 54 Submitted to CBO April 9, 2008. CBO, S. 2191, America’s Climate Security Act, with an Amendment (April 10, 2008). 55 For more information on federal expenditures on climate change, see CRS Report RL33817, Climate Change: Federal Program Funding and Tax Incentives, by (name redacted). 56 For more information on advanced vehicle R&D, see CRS Report RS21442, Hydrogen and Fuel Cell Vehicle R&D: FreedomCAR and the President’s Hydrogen Fuel Initiative, by (name redacted). ˜—›Žœœ’˜—Š•ȱŽœŽŠ›Œ‘ȱŽ›Ÿ’ŒŽȱ řŝȱ •’–ŠŽȱ‘Š—ŽDZȱ˜œœȱŠ—ȱŽ—Ž’œȱ˜ȱǯȱŘŗşŗȦǯȱřŖřŜȱ ȱ . Estimated Annual Revenues from Allowance Auctions Under S. 2191 Figure 10 EPA/ADAGE-TECH MIT/EPPA $300 $250 $200 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 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00 00 00 00 00 00 00 00 00 00 00 [Text truncated at 120,000 characters. The full text is on the page linked above.] --- Source: Frix Law Library, https://www.frixlaw.com/law-library/documents/crs%3ARL34489. Public record. Not legal advice.