AI智能总结
Zeyang Dong, Jing Liang, Joshua Linn, and Yueming Qiu About the Authors Zeyang Dongis a graduate student at the University of Maryland. His focus is onEnvironmental Economics and Energy Economics, with a particular interest in resource Jing Liangis a postdoctoral research associate at Princeton University’s Centerfor Policy Research on Energy and the Environment. Her research interests includeenergy efficiency, energy economics, energy policy, and energy sustainability. She Joshua Linnis a professor in the Department of Agricultural and Resource Economicsat the University of Maryland and a senior fellow at Resources for the Future (RFF).His research centers on the effects of environmental policies and economic incentivesfor new technologies in the transportation, electricity, and industrial sectors. Histransportation research assesses passenger vehicle taxation and fuel economy Yueming Qiuis a professor and associate dean for research and faculty affairs in theSchool of Public Policy at the University of Maryland. Her research group focuseson using big data with quasi-experimental and experimental methods to answer Acknowledgements The authors thank Jesse Buchsbaum, Stephanie Weber, and conference participantsat the 2025 Allied Social Science Associations Annual Meeting, 2025 InternationalIndustrial Organization Conference, and the 2025 Association of Environmental and 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 policy Working papers are research materials circulated by their authors for purposes ofinformation and discussion. They have not necessarily undergone formal peer review.The views expressed here are those of the individual authors and may differ from those 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, or Abstract Many jurisdictions encourage households to adopt technologies that reducegreenhouse gas emissions and energy consumption, but there is little evidence onhow these technologies affect the welfare of nonadopting households. We show that,in theory, adopting climate-friendly technologies that affect aggregate electricitydemand, such as rooftop solar photovoltaics or electric vehicles, can increase ordecrease average retail electricity prices in the short run; if the variable cost curvefor electricity generation is sufficiently flat, higher demand reduces prices (and viceversa). Analysis of US residential electricity price and consumption data, as well assimulations of a computational electricity generation model, suggests that this variable Contents 1. Introduction1 2. Data 2.1. Variables Used for Utility-level Analysis2.2. Generator Operation and Fuel Prices 3. Estimating the Effect of Electricity Consumption on Average Retail Prices 3.1. Theoretical Framework3.2. Estimation Strategy3.3. Results3.3.1. Baseline Results3.3.2. Lagged Responses3.3.3. Heterogeneity by Ownership Type and Interconnection 4. Simulating the Effect of Electricity Consumption on Average Prices4.1. Model Overview4.2. Results 5. Changes in Electricity Bills Caused by Rooftop Solar or EV Adoption 19 5.1. Methodology5.2. Rooftop Solar Results5.3. EV Results 6. Conclusions 26 References Tables and Figures29 Appendix: Calculation of distribution upgrade costs Appendix Tables and Figures48 1. Introduction Encouraging households to reduce greenhouse gas (GHG) emissions is politicallypopular and widespread globally. Governments at many levels subsidize electricvehicles (EVs), rooftop solar photovoltaics, and weatherizing residential homes.Other policies aiming to reduce residential GHG emissions are also common, such as A deepening literature evaluates the environmental benefits of the policies as wellas takeup and direct welfare effects on subsidy recipients (e.g., Bento et al. 2009,Borenstein 2017, Bruegge et al. 2019, Coyne and Globus-Harris 2024, Davis and Knittel2019, Feger et al. 2022, Glaeser et al. 2023, and Williams et al. 2015). For example,Springel (2021), Li et al. (2017), and Xing et al. (2021) evaluate subsidies for EVs andpublic charging stations in Norway and the United States; and Hughes and Podolefsky(2015), Pless and van Benthem (2019), and Dorsey (forthcoming) analyze rooftop solarsubsidies. T