Assessment of EIA Analysis of the Climate Stewardship Act

See Summary for a quick overview of the EIA analysis.

Introduction

On July 3, 2003 the Energy Information Administration (EIA) of the U.S. Department of Energy released its economic analysis of Senate Bill 139: the Climate Stewardship Act of 2003. This bill was introduced by Senators John McCain and Joseph Lieberman on January 9, 2003. S.139 represents the first economy-wide “cap-and-trade” bill that reduces greenhouse gas (GHG) emissions primarily through limiting the amount of emissions from key economic sectors and providing flexibility in obtaining GHG reductions through emissions trading and sequestration (or storage) of carbon. The program would apply to greenhouse gas emissions from major sectors – electric utilities, transportation, and industry-- covering roughly 80% of U.S. emissions.

This analysis discusses key features of EIA’s National Energy Modeling System (NEMS) model and relevant assumptions used by EIA in analyzing the costs of S.139. Modeling an economy-wide greenhouse gas trading program presents real challenges. Model results can provide important insights regarding policy design features and their implications for costs but should not be viewed as definitive predictions of future costs. Historically, advance projections of costs of many environmental programs – particularly market-based programs such as the SO2 acid rain trading program – have been much higher than the actual costs of implemented programs. Consumers of any modeling results should understand how model structure, inputs, and assumptions drive the results – which in this case focus only on the costs, but not the benefits, of climate change policy. (For more information on key drivers of cost estimates in modeling, see An Introduction to the Economics of Climate Change Policy.

EIA’s analysis of S.139 using its (NEMS) model is just one of a number of efforts by a range of organizations to model S.139. In addition to the EIA analysis, both MIT and NRDC have released their own review of the potential costs of S.139, and these results are compared with EIA’s below. In addition, the Center is working with Dr. Dale Jorgenson of Harvard University and his colleagues to evaluate possible costs of the bill.

The Center's Director of Policy Analysis, Vicki Arroyo, served as a peer reviewer on the EIA effort. She and other reviewers provided input to EIA, and while some of those comments have been reflected in their analysis (e.g., deleting a side case with zero offsets and including one with a higher limit on offsets), many were not addressed. The discussion below reflects comments submitted during the review process and notes how the cumulative effect of many factors – both structural features of NEMS and assumed inputs – serves to drive the projected costs higher than what they are likely to be.

Characterization of the EIA NEMS Model

As a macro-energy model, NEMS is a useful tool to analyze an economy-wide greenhouse gas trading program. Macro-energy models solve for the most promising solutions to achieving reductions in greenhouse gas emissions, and program costs are calculated from the economy-wide impacts of higher fossil fuel prices, altered productivity, and changing competitive advantages of firms and sectors. However, the trade-off is that macro-energy models lose detail on new technologies, characteristics of individual sectors and opportunities for energy efficiency. As a result, they often miss available opportunities to minimize program costs.

EIA’s NEMS model is considered a conservative macro-energy model and has often produced cost projections in the top quarter of modeling comparisons (for example, in the Energy Modeling Forum’s modeling comparison of the U.S. and the Kyoto Protocol). 1 Some NEMS features yielding higher projected costs are listed below.

Substitution by Firms and Consumers

  • NEMS aggregates all non-energy sectors and thus ignores opportunities for process improvements and substituting energy and material inputs.
  • NEMS assumes a “putty-clay” formation of capital investments; that is, there is complete flexibility before investment in energy capital and no flexibility once that facility has been built. This is important in shorter-term reductions where capital is assumed to be retired rather than retrofitted.
  • NEMS assumes a starting point of full and efficient employment of capital and labor; thus there are no existing low-cost opportunities for energy efficiency.
  • NEMS allows increased use of existing or new energy technologies into the energy mix, however, these opportunities are limited by specific resource and infrastructure constraints. If a technology requires a regulatory change to realize its potential, NEMS will not include it.

Technological Change

  • NEMS only chooses from a predetermined menu of technologies; thus while these technologies may improve with greater market penetration, no new technologies beyond the existing set can be used.

Inclusion of Benefits of Climate Change Policies

  • NEMS does not consider the benefits of policy in terms of avoided climate change impacts.
  • NEMS does not consider ancillary benefits of reducing local air pollution, addressing energy security etc.

Baseline Estimates of Population, GDP, Energy Use and Hence Emissions

  • NEMS projects strong economic growth for the U.S.
  • NEMS projects continued rapid expansion of carbon-intensive sources, especially electricity from coal and petroleum-based transportation.
  • NEMS includes military and bunker (aircraft and shipping) emissions, thus raising the baseline of projected “business-as-usual” (BAU) emissions.
  • NEMS has a pessimistic projection on the available supply (low) and price (high) of North American natural gas; this heavily influences cost projections as natural gas is a major transition fuel to a lower carbon economy.

Policy Regime Considered

  • The discussion of EIA’s assumptions below details the treatment of important variables including the extent of international emissions trading, inclusion of non-CO2 GHGs, use of sequestration, and methods of revenue recycling to lessen impacts on specific user groups or sectors. All of these mechanisms can reduce the cost impacts of reducing greenhouse gas emissions

Key Parameters of McCain-Lieberman S.139

The key characteristics of the S.139 GHG cap-and-trade program are:

  • All six greenhouse gases (GHGs) are covered, including emissions from the electricity, industrial and transportation sectors.
  • Covered entities for the transportation sector are upstream fuel producers/importers, while covered entities in the electricity and industrial sectors are all downstream firms responsible for more than 10,000 tons of carbon equivalent (TCE) per year.
  • Prescribed targets are Phase 1 -- year 2000 emission levels by 2010, and Phase 2 -- year 1990 emission levels by 2016.
  • The assumed “business as usual” or “base case” (without policy) specified in the bill is based on EPA’s U.S. Climate Action Report.
  • Flexibility mechanisms (international emission trading, carbon sequestration and reduction opportunities in non-covered sectors) are permitted for 15% of an entity’s required emissions allowances through 2010, declining to 10% through 2016.

    For international emission trading, the bill specifies that only pre-certified programs (e.g., the EU emissions trading scheme) can sell permits to the U.S.
  • Early action credits – firms that pursue early emissions reductions can use flexibility mechanisms to meet 20% of required reductions through 2016.
  • Banking of credits is permitted, allowing for early over-compliance to generate credits for use later in the program
  • Method of permit allocation is unspecified in the bill.
  • While the bill allows for revenue recycling via a Climate Change Credit Corporation, the methodology and amount is unspecified.

Reference Case

The first driver of the costs of reductions is the assumed “business as usual” or “base” case – that is, what emissions would have been in the absence of S.139.

The base case in NEMS assumes strong economic growth (3% per year, despite continuing economic uncertainty), and a continued reliance on fossil fuels with high carbon emissions. In particular, a significant increase of coal for electricity production is forecast, with generation from coal predicted to rise by 32% by 2025 relative to year 2000. In addition, continued expansion of transportation is expected, with petroleum consumption rising by 46% by 2025 relative to year 2000. Additional emissions increases are expected in the industrial, commercial and residential sectors. Despite these high baselines, electricity and fuel prices remain low in the base case, further exaggerating the relative impact of S.139 when costs are imposed.

The future supply -- and hence price -- of natural gas is a crucial component of the costs of controlling GHGs since natural gas is expected to be the primary transition fuel to a lower carbon economy. EIA assumes a tight supply under increased demand for natural gas in their 2003 Annual Energy Outlook, yet in its analysis of S.139, these estimates have been revised to be even higher based on the short-term indications from EIA’s recent Monthly Energy Reviews. This assumption represents a very pessimistic long-term assessment of North American natural gas resources, especially regarding the price level at which new “back-stop” natural gas resources would become available – e.g., from Northern Canada and Alaska, deep water in the Gulf of Mexico, and unconventional gas resources.

In addition, no new policy measures -- including those aimed at reducing local air pollution, improving energy security, developing new technology, promoting hydrogen, or liberalizing the electricity market -- are included in EIA’s analysis. Enactment of these complementary policies is likely to reduce the costs of controlling greenhouse gas emissions over the time period studied (to 2025).

EIA’s Primary Analysis of S.139

In EIA’s primary analysis run of S.139, a number of additional input assumptions drive up the costs of controlling GHGs under this bill. These can be divided into two main categories:

Input data and use of flexibility mechanisms for lower cost reductions:

  • A conservative assessment of available international emissions trading, due to the bill’s requirement only to trade with certified programs, hence excluding bilateral CDM opportunities.
  • High discounting of international and sequestration offsets.
  • Pessimistic assumptions of early action by firms, and hence very limited use of the increased 20% allowance for flexibility mechanisms (the equivalent assumption being employed is that only 1/5th of firms take early action).
  • Lack of inclusion of certain non-CO2 GHGs, especially methane from natural gas systems and smaller landfills.
  • Lack of inclusion of CO2 emissions from non-energy sources.
  • Use of EIA’s CO2 emissions from fossil fuel combustion rather than EPA’s estimates (as specified in S.139), resulting in a greater required reduction to meet target levels.

Technology penetration and energy efficiency opportunities:

  • Lack of foresight in the residential and commercial sectors despite publicity surrounding GHG reduction policies that would accompany debate over and passage of S.139.
  • Limited and constrained use of key technologies that require institutional and regulatory changes, especially combined heat and power (CHP), distributed generation (DG), buildings integrated photo-voltaics (BIPV), and wind.
  • Lack of consideration of efficiency step changes (e.g., widespread penetration of hybrid vehicles) in the transportation sector, and resulting small improvements in efficiency despite a large price signal (for example, an average efficiency increase of only 1.3 mpg is projected by 2025, to only 21.8 mpg).
  • Projected low level of energy efficiency improvements of products in the commercial and residential sectors resulting from the program. This lack of significant efficiency improvement is despite a significant price signal and is not well-supported by this analysis.
  • These factors combine to give extremely low levels of end-use energy efficiency in all sectors despite a significant and sustained price signal.

As a result of the above assumptions, the majority of emission reductions in this analysis come from anticipated fuel switching in the electricity sector. This leads to higher prices, premature reduction of existing energy equipment, and hence higher costs of the bill.

EIA Sensitivity Analyses of S.139

The report details a number of sensitivity cases in addition to the primary case. Many of these cases were specified by the Senators directing EIA to undertake the analysis. In some cases undertaken by EIA, the specified cases diverged from the recommendations of the reviewers.

  • A further tightening of natural gas supply resulting in even higher costs, despite the reference case already having higher natural gas prices than EIA’s AEO 2003. Given the huge uncertainties over longer term natural gas supply, a lower natural gas price case should have been included.
  • Prohibiting inclusion of both geological sequestration and advanced nuclear technologies. While both technologies are permitted under the bill itself, EIA was directed to exclude both options. Combined with tight natural gas supply and other technology restrictions, this assumption serves to dramatically drive up projected costs.
  • Zero banking of credits despite its availability under the bill and experience of cost reductions from banking under the SO2 acid rain program.
  • While EIA did include a high technology case, it only considers improvements in consumer products and electricity technologies, but does not cover advances in the natural gas production and distribution industries nor does it include a range of potentially significant new technologies (e.g., IGCC with sequestration). In addition, the improved technologies are also assumed to be available in a high tech reference case rather than be induced by the climate policy. One would expect additional technological change to be induced given the sustained price signals that EIA calculates for this bill.
  • Finally, the sensitivity case on increased use of offsets or flexibility mechanisms (e.g., participation of non-covered sectors, international trading, and sequestration) is very illustrative. Increasing the allowable offsets to 50% of required reductions shows the significant cost reductions from allowing greater flexibility in meeting the target. ($64/tC [$17/tCO2] and $174/tC [$47/tCO2] if 50% flexibility is allowed in years 2010 and 2025 vs. $79/tC [$22/tCO2] and $221/tC [$60/tCO2] under the bill’s current caps).
  • However, in the additional sensitivity case with international trading prices assumed to be halved, the bill’s cap on offsets results in most offset reductions coming from domestic non-CO2 and sequestration sources.

Discussion of Results

The cost projections generated by the EIA analysis reflect the input assumptions and model structure of NEMS, and hence are higher than costs are likely to be under the bill as proposed.

Impacts on GDP are reported at a loss of 0.4% by 2025. EIA also reports a higher loss in “real GDP” (down to 0.7% in 2015 before converging with “potential GDP” at 0.4% loss by 2025). This reflects EIA’s assumptions regarding imperfect responses in interest rates and other macro-economic variables. However, this compounded loss in GDP represents only a very small change in annual economic growth rates. The S.139 program would only reduce annual GDP growth in 2001-2025 from 3.04% to 3.02%. That is, rather than growing at 3.04% through 2025, curtailing greenhouse gases under this legislation will result in the economy growing slightly less – at 3.02%. As EIA notes in the Executive Summary, “…other factors that drive the U.S. economy, such as labor force and productivity growth are likely to play a larger role than decisions regarding the enactment of S. 139 in determining the size of the U.S. economy in 2025.”

Specific sectoral impacts are projected to be more pronounced, reflecting the presumed high baseline. The restrictions on natural gas supply, the low level of energy efficiency improvements in the face of sustained price signals (especially in transportation), and low penetration of key technologies that require institutional and regulatory changes for full market penetration, mean that the overwhelming reductions come from fuel and technology switching in the electricity supply industry. As a result, the energy price increases are expected to be significant: e.g., by 2025 prices are projected to increase 27% for petroleum, 46% for natural gas (above an already high base gas price), 475% for coal (because coal is currently very cheap and has more carbon content), and 46% for electricity. In contrast, the MIT analysis of S.139 has far more efficiency improvements, significantly more coal use coupled with carbon sequestration and accelerated penetration of alternative energy supply technologies, including distributed generation and combined heat and power plants. MIT results anticipate a falling price for natural gas under GHG reductions, as higher efficiency and use of alternative fuels weakens demand for natural gas.

Comparison to Other Analyses

Although additional analyses of S.139 are forthcoming, results of EIA’s NEMS runs can be compared with the previously released MIT study (using their EPPA model). As discussed above, a number of different input assumptions in the MIT analysis lead to different principal paths for greenhouse gas reductions, resulting in very different carbon prices and economic impacts. This is illustrated in the table below. Also shown are the results from an analysis for NRDC by the Tellus Institute, which adapts the NEMS model using a more optimistic assessment of opportunities for energy efficiency and the diffusion of lower carbon technologies. In addition, the NRDC analysis includes complementary policies, such as mandatory improvements in vehicle fuel efficiency, controls on local air pollutants and easing of regulatory restrictions that limit combined heat and power technologies.

 EIAMIT

MIT
(phase 1 only)

NRDC
Carbon Price in $/tC [$/tCO2]201079 [22]62 [17]31 [9]29 [8]
2015119 [32]81 [22]40 [11]66 [18]
2020178 [49]103 [28]52 [14]81 [22]
Welfare % cost2010-0.30%-0.07%-0.02%-
2015-0.70%-0.09%-0.02%-
2020-0.40%-0.11%-0.02%-
Total Welfare cost (billion $)2010-26.9-6.1-1.7-
2015-72.8-9.1-2.0-
2020-48.6-13.1-2.4-
Cost per Household ($)2010228521553
20155927517-124
202038310319-379

Notes:
The table shows carbon prices, welfare costs and costs per household.
All prices are in $2001.
MIT refers to scenario #9 in that analysis.
Welfare in this case measures lost consumption (or income) by consumers (as leisure effects are ignored). The NRDC analysis does not derive costs per household from overall welfare impacts, instead simply reporting net resource cost changes. Consumption is the major component of GDP (the other components being investment, government expenditures and imports/exports balance). Welfare is a good measure of actual impact on the population.
In year 2000, US GDP was around $10 trillion with consumption at $6.3 trillion.
In year 2000, there were 108 million households in the US with a median income of $41,000, by 2020, there is projected to be 127 million households with a median income of $61,000.

MIT’s analysis of S.139 finds carbon prices to be significantly less for both phases of the bill, including offsets. This reduced impact is even smaller when the model calculates the effects of higher energy prices on overall economic performance and on an individual household basis. Note that if only Phase 1 of S.139 is enacted, the anticipated economic impacts are very small. NRDC’s emphasis on greatly improved energy efficient technologies leads to net benefits from S.139.

Conclusion

The EIA analysis represents an ambitious attempt to provide insights into possible costs related to S.139; however, it should be thought of as an upper bound of likely costs. A more technologically rich and flexible model accompanied by more realistic assumptions regarding modeling inputs would yield lower cost projections.

 


1 See Weyant J. (ed) 1999, The Costs of the Kyoto Protocol: A Multi-Model Evaluation, Special Issue of the Energy Journal