GTAP Resources: Resource Display
| GTAP Resource #3518 |
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"Distributional Impacts of Carbon Pricing: A General Equilibrium Approach with Micro-Data for Households" by Rausch, Sebastian, Gilbert Metcalf and John Reilly Abstract Many policies to limit greenhouse gas emissions have at their core e orts to put a price on carbon emissions. Carbon pricing impacts households both by raising the cost of carbon intensive products and by reducing factor prices. A complete analysis requires taking both e ects into account. The impact of carbon pricing is determined by heterogeneity in household spending patterns across income groups as well as heterogeneity in factor income patterns across income groups. It is also a ected by precise formulation of the policy (how is the revenue from carbon pricing distributed) as well as the treatment of other government policies (e.g. the treatment of transfer payments). What is often neglected in analyses of policy is the heterogeneity of impacts across households even within income or regional groups. In this paper, we incorporate 15,588 households from the U.S. Consumer and Expenditure Survey data as individual agents in a comparative-static general equilibrium framework. These households are represented within the MIT USREP model, a detailed general equilibrium model of the U.S. economy. In particular, we categorize households by full household income (factor income as well as transfer income) and apply various measures of lifetime income to distinguish households that are temporarily low-income (e.g., retired households drawing down their financial assets) from permanently low-income households. We also provide more detailed within-group distributional measures of burden impacts from various policy scenarios. |
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- Climate change policy - Calibration and parameter estimation - North America |
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Public Access  2011 Conference Paper (1.2 MB) Replicated: 0 time(s)Restricted Access No documents have been attached. Special Instructions No instructions have been specified. |
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Last Modified: 9/15/2023 2:05:45 PM
