改进工业数据：现状与未来方向

Marc Hafstead and Aaron Bergman About the Authors Marc Hafsteadis a Resources for the Future (RFF) fellow and director of the CarbonPricing Initiative and the Climate Finance and Financial Risk Initiative. His researchhas primarily focused on the evaluation and design of federal and state-level climateand energy policies using sophisticated multi-sector models of the US economy.With Stanford Professor and RFF University Fellow Lawrence H. Goulder, he wroteConfronting the Climate Challenge: US Policy Options(Columbia University Press) toevaluate the environmental and economic impacts of federal carbon taxes, cap-and-trade programs, clean energy standards, and gasoline. His research has also analyzedthe distributional and employment impacts of carbon pricing and the design of taxadjustment mechanisms to reduce the emissions uncertainty of carbon tax policies. Aaron Bergmanis a fellow at RFF. Prior to joining RFF, he was the Lead forMacroeconomics and Emissions at the Energy Information Administration (EIA),managing EIA’s modeling in those areas. Before working at EIA, Bergman spent almosta decade in the policy office at the Department of Energy, working on a broad arrayof climate and environmental policies. Bergman has worked in the White House at theOffice of Science and Technology Policy, managing the Quadrennial Energy Reviewand handling the methane measurement portfolio, and at the Council on EnvironmentalQuality, working on carbon regulation. Bergman entered the federal government in2009 as a Science and Technology Policy Fellow with the American Association for theAdvancement of Science, after working in high energy physics. Acknowledgements We would like to thank Daniel Steinberg and Laura Vimmerstedt from the NationalLaboratory of the Rockies for their significant contributions towards co-organizingour December 2024 workshop, Developing an Industrial Sector Data Commons. Wewould also like to thank them for their contributions towards this report in synthesizinginformation from the workshop and assisting us in developing a road map for prioritiesand next steps. We would also like to thank Annika Eberle of the National Laboratoryof the Rockies for assistance in preparing this report. We would like to thank ValerieKarplus, Dharik Mallapragada, Sarang Supekar, and Aranya Venkatesh for theircontributions to the steering committee responsible for setting the agenda of ourworkshop. Finally, we would like to thank David Paolella and Abigail Regitsky for theircomments and guidance in organizing the workshop. About RFF Resources for the Future (RFF) is an independent, nonprofit research institution inWashington, DC. Its mission is to improve environmental, energy, and natural resourcedecisions through impartial economic research and policy engagement. RFF iscommitted to being the most widely trusted source of research insights and policysolutions leading to a healthy environment and a thriving economy. The views expressed here are those of the individual authors and may differ from thoseof other RFF experts, its officers, or its directors. Sharing Our Work Our work is available for sharing and adaptation under an Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0) license. Youcan copy and redistribute our material in any medium or format; you must giveappropriate credit, provide a link to the license, and indicate if changes were made,and you may not apply additional restrictions. You may do so in any reasonablemanner, but not in any way that suggests the licensor endorses you or your use.You may not use the material for commercial purposes. If you remix, transform, orbuild upon the material, you may not distribute the modified material. For moreinformation, visithttps://creativecommons.org/licenses/by-nc-nd/4.0/. Executive Summary Investments to advance industrial manufacturing drive US productivity, innovation,global competitiveness, and supply chain robustness. Economic and energy data onindustrial manufacturing are fundamental to inform business investment and operationdecisions as well as public- and private-sector long-term strategies for economicgrowth, industrial competitiveness, and technology research and development.Improvements in data could improve these critical decisions about priorities forinvestment and unlock industrial manufacturing benefits. This can occur by improving three types of analysis: (1) analysis of capacity expansion— the construction and upgrading of industrial manufacturing, particularly theadoption of new, advanced technologies; (2) analysis of economic growth, includingtrade flows, labor needs, regional production, and investments; (3) analysis oftechnology innovation and optimization within facilities and manufacturing clusters. Improvements in industrial data and analysis could enhance business investmentand operational decisions, long-term strategies for economic growth, industrialcompetitiveness, and technology research and development