Data and Code for: Dynamic Incentives and Permit Market Equilibrium in Cap-and-Trade Regulation
Principal Investigator(s): View help for Principal Investigator(s) Yuta Toyama, Waseda University
Version: View help for Version V1
Name | File Type | Size | Last Modified |
---|---|---|---|
32_1_R_Construction_Production | 11/21/2023 12:25:AM | ||
33_1_R_Construction_Trading | 11/21/2023 12:31:AM | ||
34_1_R_Estimation_Step1 | 11/21/2023 01:04:AM | ||
34_2_Implication_Production | 11/21/2023 12:33:AM | ||
34_3_R_Descriptive | 11/21/2023 12:34:AM | ||
34_4_R_Estimation_Step2 | 01/11/2024 01:26:AM | ||
35_1_2_No_Banking_Between_P1P2 | 01/11/2024 01:27:AM | ||
35_1_Cost_effective_NoTC | 01/11/2024 01:30:AM | ||
35_4_R_Simu_Summary | 01/11/2024 01:34:AM | ||
Data | 05/14/2023 04:37:AM |
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Project Citation:
Toyama, Yuta. Data and Code for: Dynamic Incentives and Permit Market Equilibrium in Cap-and-Trade Regulation. Nashville, TN: American Economic Association [publisher], 2024. Ann Arbor, MI: Inter-university Consortium for Political and Social Research [distributor], 2024-07-03. https://doi.org/10.3886/E191522V1
Project Description
Summary:
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This paper develops and estimates a dynamic structural model of emissions abatement, investment, and permit trading with banking under cap-and-trade regulation. The model accounts for forward-looking behavior and transaction costs in the permit market, which determine the temporal and geographical distribution of emissions in equilibrium, and, thus, the welfare implications of the regulation. The model is applied to the US Acid Rain Program to evaluate the role of regulatory designs. Permit banking mitigates inefficiencies arising from transaction costs and modifies the timing of emissions. An emissions tax policy could achieve an outcome close to dynamic cap-and-trade without transaction costs.
Scope of Project
Subject Terms:
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Structural estimation;
environmental regulations;
power plants;
sulphur dioxide
JEL Classification:
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D22 Firm Behavior: Empirical Analysis
L94 Electric Utilities
Q52 Pollution Control Adoption and Costs; Distributional Effects; Employment Effects
Q58 Environmental Economics: Government Policy
D22 Firm Behavior: Empirical Analysis
L94 Electric Utilities
Q52 Pollution Control Adoption and Costs; Distributional Effects; Employment Effects
Q58 Environmental Economics: Government Policy
Geographic Coverage:
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United States
Time Period(s):
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1995 – 2003
Universe:
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Fossil-fuel-fired power plants in the United States
Data Type(s):
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aggregate data;
observational data;
program source code
Methodology
Data Source:
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- Energy Information Administration (1985-2005) EIA-767 Steam-Electric Plant Operation and Design Report
- Energy Information Administration (1990-2003) Historic Form EIA-423 & FERC-423 Detailed Data on Cost and Quality of Fuels for Electric Plants
- U.S. Bureau of Labor Statistics (1984-2015) Producer Price Index
- U.S. Census Bureau (2010) 2010 Census U.S. Gazetteer Files for Counties
- U.S. Census Bureau (2011) Census Bureau Region and Division Codes and Federal Information Processing System (FIPS) Codes for States
- BGC Environmental Brokerage Services (2011) SO2 Allowance Price Indications
- Energy Information Administration (1990-2003) The Form EIA-826 "Monthly Electric Utility Sales and Revenue Report with State Distributions"
- U.S. Environmental Protection Agency (1993-2013b) Emissions and Facility Data
- U.S. Environmental Protection Agency (1993-2013b) Acid Rain Program Compliance data
- U.S. Environmental Protection Agency (1993-2013a) Acid Rain Program Allowance Transactions Data
- Muller and Mendelsohn (2009) County-level health and environmental damages from Muller and Mendelsohn (2009)
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