<?xml version="1.0" encoding="UTF-8"?><?xml-stylesheet type="text/xsl" href="static/style.xsl"?><OAI-PMH xmlns="http://www.openarchives.org/OAI/2.0/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/ http://www.openarchives.org/OAI/2.0/OAI-PMH.xsd"><responseDate>2026-09-19T01:23:38Z</responseDate><request verb="GetRecord" identifier="oai:dspace.mit.edu:1721.1/79205" metadataPrefix="dim">https://dspace.mit.edu/server/oai/request</request><GetRecord><record><header><identifier>oai:dspace.mit.edu:1721.1/79205</identifier><datestamp>2022-01-13T07:54:09Z</datestamp><setSpec>com_1721.1_7582</setSpec><setSpec>com_1721.1_7581</setSpec><setSpec>col_1721.1_131023</setSpec></header><metadata><dim:dim xmlns:dim="http://www.dspace.org/xmlns/dspace/dim" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xmlns:doc="http://www.lyncode.com/xoai" xsi:schemaLocation="http://www.dspace.org/xmlns/dspace/dim http://www.dspace.org/schema/dim.xsd">
   <dim:field mdschema="dc" element="contributor" qualifier="advisor" lang="en_US">Lawrence Susskind.</dim:field>
   <dim:field mdschema="dc" element="contributor" qualifier="author" lang="en_US">Look, Wesley Allen</dim:field>
   <dim:field mdschema="dc" element="contributor" qualifier="other" lang="en_US">Massachusetts Institute of Technology. Department of Urban Studies and Planning.</dim:field>
   <dim:field mdschema="dc" element="contributor" qualifier="department">Massachusetts Institute of Technology. Department of Urban Studies and Planning</dim:field>
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   <dim:field mdschema="dc" element="date" qualifier="accessioned">2013-06-17T19:47:23Z</dim:field>
   <dim:field mdschema="dc" element="date" qualifier="available">2013-06-17T19:47:23Z</dim:field>
   <dim:field mdschema="dc" element="date" qualifier="copyright" lang="en_US">2013</dim:field>
   <dim:field mdschema="dc" element="date" qualifier="issued" lang="en_US">2013</dim:field>
   <dim:field mdschema="dc" element="identifier" qualifier="uri">http://hdl.handle.net/1721.1/79205</dim:field>
   <dim:field mdschema="dc" element="identifier" qualifier="oclc" lang="en_US">844353189</dim:field>
   <dim:field mdschema="dc" element="description" lang="en_US">Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Urban Studies and Planning, 2013.</dim:field>
   <dim:field mdschema="dc" element="description" lang="en_US">Cataloged from PDF version of thesis.</dim:field>
   <dim:field mdschema="dc" element="description" lang="en_US">Includes bibliographical references (p. 60-62).</dim:field>
   <dim:field mdschema="dc" element="description" qualifier="abstract" lang="en_US">The political economy of US climate policy has revolved around state- and district- level distributional economics, and to a lesser extent household-level distribution questions. Many politicians and analysts have suggested that state- and district-level climate policy costs (and their distribution) are a function of local carbon intensity and commensurate electricity price sensitivity. However, other studies have suggested that what is most important in determining costs is the means by which revenues from a price on carbon are allocated. This is one of the first studies to analyze these questions simultaneously across all 50 United States, household income classes and a timeframe that reflects most recent policy proposals (2015 - 2050). I use a recursive dynamic computable general equilibrium (CGE) model to estimate the economic effects of a US "cap-and-dividend" policy, by simulating the implementation of the Carbon Limits and Energy for America's Renewal (CLEAR) Act, a bill proposed by Senators Cantwell (D-WA) and Collins (R-ME) in 2009. I find that while carbon intensity and electricity prices are indeed important in determining compliance costs in some states, they are only part of the story. My results suggest that revenue allocation mechanisms and new investment trends related to the switch to low-carbon infrastructure are more influential than incumbent carbon intensity or electricity price impacts in determining the distribution of state-level policy costs. These findings suggest that the current debate in the United States legislature over climate policy, and the constellation of both supporters and dissenters, is based upon an incomplete set of assumptions that must be revisited. Finally, please note that this study does not claim to comprehensively model the CLEAR Act,. nor does it incorporate a number of important data and assumptions, including: the latest data on natural gas resources and prices, the price effects on coal of EPA greenhouse gas and mercury regulations, the most recent trends in renewable energy pricing.</dim:field>
   <dim:field mdschema="dc" element="description" qualifier="statementofresponsibility" lang="en_US">by Wesley Allen Look.</dim:field>
   <dim:field mdschema="dc" element="description" qualifier="degree" lang="en_US">S.M.</dim:field>
   <dim:field mdschema="dc" element="format" qualifier="extent" lang="en_US">62 p.</dim:field>
   <dim:field mdschema="dc" element="language" qualifier="iso" lang="en_US">eng</dim:field>
   <dim:field mdschema="dc" element="publisher" lang="en_US">Massachusetts Institute of Technology</dim:field>
   <dim:field mdschema="dc" element="rights" lang="en_US">M.I.T. theses are protected by 
copyright. They may be viewed from this source for any purpose, but 
reproduction or distribution in any format is prohibited without written 
permission. See provided URL for inquiries about permission.</dim:field>
   <dim:field mdschema="dc" element="rights" qualifier="uri" lang="en_US">http://dspace.mit.edu/handle/1721.1/7582</dim:field>
   <dim:field mdschema="dc" element="subject" lang="en_US">Urban Studies and Planning.</dim:field>
   <dim:field mdschema="dc" element="title" lang="en_US">The economics of US greenhouse gas emissions reduction policy : assessing distributional effects across households and the 50 United States using a recursive dynamic computable general equilibrium (CGE) model</dim:field>
   <dim:field mdschema="dc" element="title" qualifier="alternative" lang="en_US">Economics of United States greenhouse gas emissions reduction policy</dim:field>
   <dim:field mdschema="dc" element="title" qualifier="alternative" lang="en_US">Assessing distributional effects across households and the 50 United States using a recursive dynamic computable general equilibrium (CGE) Model</dim:field>
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	&lt;Language>eng&lt;/Language>
   	&lt;Title>The economics of US greenhouse gas emissions reduction policy : assessing distributional effects across households and the 50 United States using a recursive dynamic computable general equilibrium (CGE) model&lt;/Title>
   	&lt;Subtitle>Economics of United States greenhouse gas emissions reduction policy&lt;/Subtitle>
   	&lt;Subtitle>Assessing distributional effects across households and the 50 United States using a recursive dynamic computable general equilibrium (CGE) Model&lt;/Subtitle>
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   	&lt;PublicationDate>2013&lt;/PublicationDate>
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        	&lt;DisplayName>Look, Wesley Allen&lt;/DisplayName>
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            &lt;DisplayName>Massachusetts Institute of Technology&lt;/DisplayName>
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    &lt;Keyword>Urban Studies and Planning.&lt;/Keyword>
   	&lt;Abstract>The political economy of US climate policy has revolved around state- and district- level distributional economics, and to a lesser extent household-level distribution questions. Many politicians and analysts have suggested that state- and district-level climate policy costs (and their distribution) are a function of local carbon intensity and commensurate electricity price sensitivity. However, other studies have suggested that what is most important in determining costs is the means by which revenues from a price on carbon are allocated. This is one of the first studies to analyze these questions simultaneously across all 50 United States, household income classes and a timeframe that reflects most recent policy proposals (2015 - 2050). I use a recursive dynamic computable general equilibrium (CGE) model to estimate the economic effects of a US &amp;quot;cap-and-dividend&amp;quot; policy, by simulating the implementation of the Carbon Limits and Energy for America&amp;apos;s Renewal (CLEAR) Act, a bill proposed by Senators Cantwell (D-WA) and Collins (R-ME) in 2009. I find that while carbon intensity and electricity prices are indeed important in determining compliance costs in some states, they are only part of the story. My results suggest that revenue allocation mechanisms and new investment trends related to the switch to low-carbon infrastructure are more influential than incumbent carbon intensity or electricity price impacts in determining the distribution of state-level policy costs. These findings suggest that the current debate in the United States legislature over climate policy, and the constellation of both supporters and dissenters, is based upon an incomplete set of assumptions that must be revisited. Finally, please note that this study does not claim to comprehensively model the CLEAR Act,. nor does it incorporate a number of important data and assumptions, including: the latest data on natural gas resources and prices, the price effects on coal of EPA greenhouse gas and mercury regulations, the most recent trends in renewable energy pricing.&lt;/Abstract>
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