This paper analyzes changes in U.S. energy-intensive, trade-exposed (EITE) manufacturing over the past decade, through the lens of previously proposed climate policy measures. The American Clean Energy and Security Act of 2009 defined measures and thresholds for EITE eligibility and proposed compensatory allowances designed to reduce negative competitive impacts to domestic industry and to prevent emissions leakage. We undertook a retrospective analysis of the 2009 eligibility criteria, using the same methods with more recent data to examine trends over the 2004-2017 period. We find that energy intensity, emissions intensity, output, and emissions have fluctuated with economic conditions, and defining measures and thresholds that remain informative is challenging. Had ACES been enacted as written and not revised, the number of sectors qualifying for rebates would have decreased from 39 to 26, after adjustment for the changes in North American Industry Classification System definitions. Emissions from the eligible sectors fell 26% across the three periods of analysis, while emissions from manufacturing as a whole fell 5%. We decompose the changes in emissions into scale and intensity measures based on a hybrid measure derived from Grossman and Krueger [(1993). Environmental impacts of a North American free trade agreement. In The US-Mexico Free Trade Agreement, PM Garber (ed.). Cambridge, MA: MIT Press] and Kaya and Yokoburi [(1997). Environment, Energy, and Economy: Strategies for Sustainability. Tokyo: United Nations University Press]. As an alternative, we perform the same analyses using the EPA's Greenhouse Gas Reporting Program data. These data, not available when ACES was written, offer annual greenhouse gas estimates for facilities that emit more than 25,000 tons COe annually. Finally, we draw some recommendations for future policy including (1) using measures that make price level adjustments straightforward or unnecessary, (2) keeping EITE policy focused on a small group of industries to minimize sectoral reclassification problems, (3) identifying industries prone to emissions leakage rather than just changes in output and (4) consider spatial heterogeneity of emissions and trade patterns.

Observational evidence shows marine species are shifting their geographic distribution in response to warming ocean temperatures. These shifts have implications for the US fisheries and seafood consumers. The analysis presented here employs a two-stage inverse demand model to estimate the consumer welfare impacts of projected increases or decreases in commercial landings for 16 US fisheries from 2021 to 2100, based on the predicted changes in thermally available habitat. The fisheries analyzed together account for 56% of the current US commercial fishing revenues. The analysis compares welfare impacts under two climate scenarios: a high emissions case that assumes limited efforts to reduce atmospheric greenhouse gas and a low emissions case that assumes more stringent mitigation. The present value of consumer surplus impacts when discounted at 3% is a net loss of $2.1 billion (2018 US$) in the low emissions case and $4.2 billion in the high emissions scenario. Projected annual losses reach $278-901 million by 2100.

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 (CO) 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 CO 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.

This paper presents a multi-model assessment of the distributional impacts of carbon pricing. A set of harmonized representative CO taxes and tax revenue recycling schemes is implemented in five large-scale economy-wide general equilibrium models. Recycling schemes include various combinations of uniform transfers to households and labor and capital income tax reductions. Particular focus is put on equity - the distribution of impacts across household incomes - and efficiency, evaluated in terms of household welfare. Despite important differences in the assumptions underlying the models, we find general agreement regarding the ranking of recycling schemes in terms of both efficiency and equity. All models identify a clear trade-off between efficient but regressive capital tax reductions and progressive but costly uniform transfers to households; all agree upon the inferiority of labor tax reductions in terms of welfare efficiency; and all agree that different combinations of capital tax reductions and household transfers can be used to balance efficiency and distributional concerns. A subset of the models go further and find that equity concerns, particularly regarding the impact of the tax on low income households, can be alleviated without sacrificing much of the double-dividend benefits offered by capital tax rebates. There is, however, less agreement regarding the progressivity of CO taxation net of revenue recycling. Regionally, the models agree that abatement and welfare impacts will vary considerably across regions of the U.S. and generally agree on their broad geographical distribution. There is, however, little agreement regarding the regions which would profit more from the various recycling schemes.

The Energy Modeling Forum (EMF) 32 study on carbon tax scenarios analyzed a set of illustrative policies in the United States that place an economy-wide tax on fossil-fuel-related carbon dioxide (CO) emissions, a carbon tax for short. Eleven modeling teams ran these stylized scenarios, which vary by the initial carbon tax rate, the rate at which the tax escalates over time, and the use of the revenues. Modelers reported their results for the effects of the policies, relative to a reference scenario that does not include a carbon tax, on emissions, economic activity, and outcomes within the U.S. energy system. This paper explains the scenario design, presents an overview of the results, and compares results from the participating models. In particular, we compare various outcomes across the models, such as emissions, revenue, gross domestic product, sectoral impacts, and welfare.

This paper is an introduction to, "The EMF 32 Study on U.S. Carbon Tax Scenarios," part of the Stanford Energy Modeling Forum (EMF) Model Inter-comparison Project (MIP) number 32. Eleven modeling teams participated in this study examining the economic and environmental impacts of various carbon tax trajectories and differing uses of carbon tax revenues. This special issue of documents the results of this study with four crosscutting papers that summarize results across models, and ten papers from individual modeling teams.

This paper provides a detailed, cross-model analysis and discussion of the implications of carbon tax scenarios on changes in sectoral output, energy production and consumption and the competitiveness of the United States' economy. Our analysis focuses on the broad patterns apparent across models in both qualitative and quantitative terms at the sector level, with a focus on energy-intensive, trade-exposed sectors. We identify how variations in carbon tax trajectories and different options for using the revenue from the tax drive these results.