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EMF 32: US GHG and Revenue Recycling Scenarios



The purpose of this modeling exercise is to use energy-economic models to assess emissions, energy and economic outcomes from a plausible range of US policies to reduce greenhouse gases (GHGs). In addition to standard emphasis on the effects of such policies on emissions, energy prices and macroeconomic performance, an economic issue of particular interest will be how fiscal decisions on revenue distribution might also affect these outcomes.
The steering committee for EMF 32 is:
Francisco de la Chesnaye: Electric Power Research Institute
John Bistline: Electric Power Research Institute
Jared Creason: US Environmental Protection Agency
Allen A. Fawcett: US Environmental Protection Agency
Jim McFarland: US Environmental Protection Agency
Adele Morris: Brookings Institution
Brian Murray: Duke University
John Weyant: Stanford University
The original motivations for the EMF 32 US climate policy MIP were:
• The political saliency of GHG tax revenue recycling. How feasible/effective are such policies?
• Search for U.S. power sector GHG control policies - What is feasible in the current environment?
• Proposed EPA Clean Air Act Section 111 approach to utility GHG regulation. How effective will this be and how would it interact with other GHG and accompanying fiscal policies?
• Implications of the November 2014 U.S./China Presidential agreement for the U.S energy system/policy
Schedule for the EMF 32 US Climate Policy Scenario MIP:
Meeting #1: Scoping: EPRI Washington DC Office, October 22-23, 2014
Meeting #2: Brookings Institution Washington, DC, June 8-9, 2015
Meeting #3: Brookings Institution Washington, DC, March 29-30, 2016
Meeting #4: Brookings Institution Washington, DC, February 2-3, 2017
From the beginning, the EMF 32 study sought to explore results of a MIP with U.S. climate policy scenarios focusing on different carbon tax trajectories and different options for using the revenues from the tax; as well as scenarios that explored the implications of technology and policy strategies for reducing GHG emissions in the U.S. power sector. While EMF 32 meetings covered both halves of the study, the steering committee decided report the results of the two halves of EMF 32 in two separate publications. 

EMF 32 Study on U.S. Carbon Tax Scenarios – Climate Change Economics Special Issue

Allen Fawcett, Jim McFarland, Adele Morris, and John Weyant served as guest editors of, “The EMF 32 Study on U.S. Carbon Tax Scenarios,” special issue of the journal Climate Change Economics. The special issue was published in February 2018, and contains 15 papers: 10 written by modeling teams and 5 overview/synthesis papers. 
The results of this part of the EMF 32 study are consistent with much of the existing modeling literature on carbon pricing in the United States. Across all models, we find that the core carbon price scenarios lead to significant reductions in CO2 emissions, with the vast majority of the reductions occurring in the electricity sector and disproportionately through reductions in coal. Emissions reductions are largely independent of the uses of the revenues modeled here. Expected economic costs (not accounting for any of the benefits of greenhouse gas and conventional pollutant mitigation), in terms of either GDP or welfare, are modest, but they vary across models and policies. Using revenues to reduce preexisting capital or, to a lesser extent labor taxes, reduces welfare losses in most models relative to providing household rebates, but the magnitudes of the cost savings vary. The use of revenue can also have important distributional implications, revenue recycling in the form of capital tax reductions is the most efficient but the most regressive, while lump sum rebates to households is the most progressive but the least efficient. Notably, we find that it is possible to protect low-income households with a modest share of revenues, while using the remainder of revenues on capital tax reductions allows the policy-maker to attain efficiency close to that of a pure capital tax reduction. In the present study, the models do not agree on the regional implications of the various revenue recycling schemes. Beyond 2030, we conclude that model uncertainties are too large to make quantitative results useful for near term policy design. 

EMF 32 Study on Technology and Climate Policy Strategies for Greenhouse Gas Reductions in the U.S. Electric Power Sector – Energy Economics Special Issue

Brian Murray, John Bistline (EPRI), and Jared Creason (EPA) served as guest editors of, “The EMF 32 Study on Technology and Climate Policy Strategies for Greenhouse Gas Reductions in the U.S. Electric Power Sector,” special issue of the journal Energy Economics. This forthcoming special issue is expected to be published in the Spring of 2018, and will contain 11 papers: 8 written by modeling teams, and 3 overview/synthesis papers.  
In this part of the EMF 32 study, harmonized policy scenarios (including mass-based emissions limits and various power-sector-only carbon tax trajectories), spanning a range of technological and natural gas price assumptions, across 16 models provide comparative assessments of potential impacts on electric sector investment and generation outcomes, emissions reductions, and economic implications. Under a wide range of policy, technology, and market assumptions, model results suggest that future coal generation will decline relative to current levels while generation from natural gas, wind, and solar will increase, though the pace and extent of these changes vary by policy scenario, technological assumptions, region, and model. The power sector transformation comes primarily in the form of substitution of natural gas and renewables for coal generation, a trend that has already started without a national policy in place, but would be amplified considerably if the types and levels of technological change and/or carbon pricing policies studied here were enacted.
(Link coming soon-  EMF 32 Energy Economics Special Issue)
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Last Modified: 
August 2015
Last Modified: 
August 2015
Last Modified: 
February 2015