Data and Code for: Do Two Electricity Pricing Wrongs Make a Right? Cost Recovery, Externalities, and Efficiency
Principal Investigator(s): View help for Principal Investigator(s) Severin Borenstein, University of California-Berkeley; James B Bushnell, University of California-Davis
Version: View help for Version V1
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AEJEP2019-0758DataArchiveVER2.nosync | 11/07/2022 10:41:PM |
Project Citation:
Borenstein, Severin, and Bushnell, James B. Data and Code for: Do Two Electricity Pricing Wrongs Make a Right? Cost Recovery, Externalities, and Efficiency. Nashville, TN: American Economic Association [publisher], 2023. Ann Arbor, MI: Inter-university Consortium for Political and Social Research [distributor], 2023-09-26. https://doi.org/10.3886/E158242V1
Project Description
Summary:
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Economists favor pricing pollution in part so that consumers face the full social marginal cost (SMC) of goods and services. But even without valuing externalities, retail electricity prices typically exceed private marginal cost, due to a utility's need to cover average costs. Furthermore, due to costly storage, the marginal cost of electricity can fluctuate widely hour-to-hour, while retail prices do not. We show that residential electricity rates exceed average SMC in most of the US, but there is large variation, both geographically and temporally. This finding has important implications for pass-through of pollution costs, as well as for policies to promote dynamic pricing, alternative energy and reduced electricity consumption.
Funding Sources:
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Google;
Alfred P. Sloan Foundation
Scope of Project
Subject Terms:
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Electricity pricing and costs
JEL Classification:
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L51 Economics of Regulation
L94 Electric Utilities
L51 Economics of Regulation
L94 Electric Utilities
Geographic Coverage:
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United States
Time Period(s):
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2014 – 2016
Collection Date(s):
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2017 – 2021
Universe:
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Residential retail electricity prices, wholesale electricity prices, electricity quantities, electricity generation, electricity emissions, expenditures on selected utility public purpose programs
Data Type(s):
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administrative records data;
geographic information system (GIS) data;
program source code
Methodology
Collection Mode(s):
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other
Unit(s) of Observation:
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Distribution utility by state
Geographic Unit:
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Continental US
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