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POLICY INSIGHTS FROM THE EMF 32 STUDY ON U.S. CARBON TAX SCENARIOS

Alexander R. Barron, Allen A. Fawcett, Marc Hafstead, James R. McFarland and Adele C. Morris
Additional contact information
Alexander R. Barron: #x2020;Environmental Science and Policy Program, Smith College, 44 College Lane, Northampton, MA 01063, USA
Allen A. Fawcett: #x2021;U.S. Environmental Protection Agency, 1200 Pennsylvania Avenue NW, Washington, DC 20460, USA
James R. McFarland: #x2021;U.S. Environmental Protection Agency, 1200 Pennsylvania Avenue NW, Washington, DC 20460, USA
Adele C. Morris: #xB6;Brookings Institution, 1775 Massachusetts Ave, NW Washington, DC 20036, USA

Climate Change Economics (CCE), 2018, vol. 09, issue 01, 1-47

Abstract: The Stanford Energy Modeling Forum exercise 32 (EMF 32) used 11 different models to assess emissions, energy, and economic outcomes from a plausible range of economy-wide carbon price policies to reduce carbon dioxide (CO2) emissions in the United States. Here we discuss the most policy-relevant results of the study, mindful of the strengths and weaknesses of current models. Across all models, carbon prices lead to significant reductions in CO2 emissions and conventional pollutants, with the vast majority of the reductions occurring in the electricity sector. Importantly, emissions reductions do not significantly depend on the rebate or tax cut used to return revenues to the economy. Expected economic costs, as modeled by either GDP or welfare, are modest, but vary across models. These costs are offset by benefits from avoided climate damages and health benefits from reductions in conventional air pollution. Using revenues to reduce preexisting capital or labor taxes reduces costs in most models relative to lump-sum rebates, but the size of the cost reductions varies significantly. Devoting at least some revenue to household rebates can significantly reduce adverse impacts on low income households. Carbon prices at $25/ton or even lower levels cause significant shifts away from coal as an energy source with responses of other energy sources highly dependent upon technology cost assumptions. Beyond 2030, we conclude that model uncertainties are too large to make quantitative results useful for near-term policy design. We close by describing recommendations for policymakers on interacting with model results in the future.

Keywords: Climate change; model comparison; decarbonization; CGE models (search for similar items in EconPapers)
Date: 2018
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DOI: 10.1142/S2010007818400031

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