Measuring the cost-effectiveness of electric vehicle subsidies
•We develop a vehicle choice model using a representative sample of U.S. new car buyers.•We simulate and compare alternative federal PEV subsidy policies.•Existing federal incentives are expensive, $36k per additional PEV.•Cost-effectiveness can be improved 2× by targeting incentives by consumer typ...
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Veröffentlicht in: | Energy economics 2019-10, Vol.84, p.104545, Article 104545 |
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creator | Sheldon, Tamara L. Dua, Rubal |
description | •We develop a vehicle choice model using a representative sample of U.S. new car buyers.•We simulate and compare alternative federal PEV subsidy policies.•Existing federal incentives are expensive, $36k per additional PEV.•Cost-effectiveness can be improved 2× by targeting incentives by consumer type.
Despite the prevalence of plug-in electric vehicle (PEV) subsidies, research on improving their cost-effectiveness and impact remains limited. To assess the scope for improving their cost-effectiveness, we develop a vehicle choice model-based counterfactual simulation using a large-scale nationally representative sample of U.S. new car buyers. Results suggest that existing federal incentives are expensive, $36k per additional PEV, as every buyer gets the subsidy. The cost-effectiveness can be improved by twofold by targeting incentives by income, vehicle disposal, geography, and/or vehicle miles traveled. Preserving the federal policy's assignment of larger subsidies for PEVs with larger battery capacities results in greater battery electric vehicle (BEV) adoption, while policies not discriminating by battery capacity result in greater plug-in hybrid electric vehicle adoption. The reduction in gasoline consumption is the same in both the cases, with a slightly lower marginal cost for the latter. |
doi_str_mv | 10.1016/j.eneco.2019.104545 |
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Despite the prevalence of plug-in electric vehicle (PEV) subsidies, research on improving their cost-effectiveness and impact remains limited. To assess the scope for improving their cost-effectiveness, we develop a vehicle choice model-based counterfactual simulation using a large-scale nationally representative sample of U.S. new car buyers. Results suggest that existing federal incentives are expensive, $36k per additional PEV, as every buyer gets the subsidy. The cost-effectiveness can be improved by twofold by targeting incentives by income, vehicle disposal, geography, and/or vehicle miles traveled. Preserving the federal policy's assignment of larger subsidies for PEVs with larger battery capacities results in greater battery electric vehicle (BEV) adoption, while policies not discriminating by battery capacity result in greater plug-in hybrid electric vehicle adoption. The reduction in gasoline consumption is the same in both the cases, with a slightly lower marginal cost for the latter.</description><identifier>ISSN: 0140-9883</identifier><identifier>EISSN: 1873-6181</identifier><identifier>DOI: 10.1016/j.eneco.2019.104545</identifier><language>eng</language><publisher>Kidlington: Elsevier B.V</publisher><subject>Air pollution ; Clean vehicles ; Computer simulation ; Consumption ; Cost analysis ; Costs ; Decision making models ; Effectiveness ; Electric vehicles ; Energy economics ; Federal policy ; Gasoline ; Geography ; Hybrid electric vehicles ; Impact strength ; Incentives ; Simulation ; Subsidies ; Transportation policy ; Travel demand</subject><ispartof>Energy economics, 2019-10, Vol.84, p.104545, Article 104545</ispartof><rights>2019 Elsevier B.V.</rights><rights>Copyright Elsevier Science Ltd. Oct 2019</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c441t-cfcaac07a25b8ad8153e03312aca0030eaeba3ee01a675cd6fe3eb5203bf68e3</citedby><cites>FETCH-LOGICAL-c441t-cfcaac07a25b8ad8153e03312aca0030eaeba3ee01a675cd6fe3eb5203bf68e3</cites><orcidid>0000-0002-1355-1202</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://dx.doi.org/10.1016/j.eneco.2019.104545$$EHTML$$P50$$Gelsevier$$Hfree_for_read</linktohtml><link.rule.ids>314,780,784,3550,27866,27924,27925,45995</link.rule.ids></links><search><creatorcontrib>Sheldon, Tamara L.</creatorcontrib><creatorcontrib>Dua, Rubal</creatorcontrib><title>Measuring the cost-effectiveness of electric vehicle subsidies</title><title>Energy economics</title><description>•We develop a vehicle choice model using a representative sample of U.S. new car buyers.•We simulate and compare alternative federal PEV subsidy policies.•Existing federal incentives are expensive, $36k per additional PEV.•Cost-effectiveness can be improved 2× by targeting incentives by consumer type.
Despite the prevalence of plug-in electric vehicle (PEV) subsidies, research on improving their cost-effectiveness and impact remains limited. To assess the scope for improving their cost-effectiveness, we develop a vehicle choice model-based counterfactual simulation using a large-scale nationally representative sample of U.S. new car buyers. Results suggest that existing federal incentives are expensive, $36k per additional PEV, as every buyer gets the subsidy. The cost-effectiveness can be improved by twofold by targeting incentives by income, vehicle disposal, geography, and/or vehicle miles traveled. Preserving the federal policy's assignment of larger subsidies for PEVs with larger battery capacities results in greater battery electric vehicle (BEV) adoption, while policies not discriminating by battery capacity result in greater plug-in hybrid electric vehicle adoption. The reduction in gasoline consumption is the same in both the cases, with a slightly lower marginal cost for the latter.</description><subject>Air pollution</subject><subject>Clean vehicles</subject><subject>Computer simulation</subject><subject>Consumption</subject><subject>Cost analysis</subject><subject>Costs</subject><subject>Decision making models</subject><subject>Effectiveness</subject><subject>Electric vehicles</subject><subject>Energy economics</subject><subject>Federal policy</subject><subject>Gasoline</subject><subject>Geography</subject><subject>Hybrid electric vehicles</subject><subject>Impact strength</subject><subject>Incentives</subject><subject>Simulation</subject><subject>Subsidies</subject><subject>Transportation policy</subject><subject>Travel demand</subject><issn>0140-9883</issn><issn>1873-6181</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2019</creationdate><recordtype>article</recordtype><sourceid>7TQ</sourceid><recordid>eNp9kE9PwzAMxSMEEmPwCbhU4tzhNEmXHUBCE_-kIS67R2nqsFSjHXFbiW9PRjlzsmy992z_GLvmsODAy9tmgS26blEAX6WJVFKdsBnXS5GXXPNTNgMuIV9pLc7ZBVEDAKpUesbu39DSEEP7kfU7zFxHfY7eo-vDmDKJss5nuE99DC4bcRfcHjMaKgp1QLpkZ97uCa_-6pxtnx6365d88_78un7Y5E5K3ufOO2sdLG2hKm1rzZVAEIIX1lkAAWixsgIRuC2XytWlR4GVKkBUvtQo5uxmij3E7mtA6k3TDbFNG00hlNSgNZdJJSaVix1RRG8OMXza-G04mCMn05hfTubIyUyckutucmG6fwwYDbmArcM6xPS2qbvwr_8Hu2dysA</recordid><startdate>20191001</startdate><enddate>20191001</enddate><creator>Sheldon, Tamara L.</creator><creator>Dua, Rubal</creator><general>Elsevier B.V</general><general>Elsevier Science Ltd</general><scope>6I.</scope><scope>AAFTH</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7ST</scope><scope>7TA</scope><scope>7TQ</scope><scope>8BJ</scope><scope>8FD</scope><scope>C1K</scope><scope>DHY</scope><scope>DON</scope><scope>FQK</scope><scope>JBE</scope><scope>JG9</scope><scope>SOI</scope><orcidid>https://orcid.org/0000-0002-1355-1202</orcidid></search><sort><creationdate>20191001</creationdate><title>Measuring the cost-effectiveness of electric vehicle subsidies</title><author>Sheldon, Tamara L. ; Dua, Rubal</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c441t-cfcaac07a25b8ad8153e03312aca0030eaeba3ee01a675cd6fe3eb5203bf68e3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2019</creationdate><topic>Air pollution</topic><topic>Clean vehicles</topic><topic>Computer simulation</topic><topic>Consumption</topic><topic>Cost analysis</topic><topic>Costs</topic><topic>Decision making models</topic><topic>Effectiveness</topic><topic>Electric vehicles</topic><topic>Energy economics</topic><topic>Federal policy</topic><topic>Gasoline</topic><topic>Geography</topic><topic>Hybrid electric vehicles</topic><topic>Impact strength</topic><topic>Incentives</topic><topic>Simulation</topic><topic>Subsidies</topic><topic>Transportation policy</topic><topic>Travel demand</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Sheldon, Tamara L.</creatorcontrib><creatorcontrib>Dua, Rubal</creatorcontrib><collection>ScienceDirect Open Access Titles</collection><collection>Elsevier:ScienceDirect:Open Access</collection><collection>CrossRef</collection><collection>Environment Abstracts</collection><collection>Materials Business File</collection><collection>PAIS Index</collection><collection>International Bibliography of the Social Sciences (IBSS)</collection><collection>Technology Research Database</collection><collection>Environmental Sciences and Pollution Management</collection><collection>PAIS International</collection><collection>PAIS International (Ovid)</collection><collection>International Bibliography of the Social Sciences</collection><collection>International Bibliography of the Social Sciences</collection><collection>Materials Research Database</collection><collection>Environment Abstracts</collection><jtitle>Energy economics</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Sheldon, Tamara L.</au><au>Dua, Rubal</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Measuring the cost-effectiveness of electric vehicle subsidies</atitle><jtitle>Energy economics</jtitle><date>2019-10-01</date><risdate>2019</risdate><volume>84</volume><spage>104545</spage><pages>104545-</pages><artnum>104545</artnum><issn>0140-9883</issn><eissn>1873-6181</eissn><abstract>•We develop a vehicle choice model using a representative sample of U.S. new car buyers.•We simulate and compare alternative federal PEV subsidy policies.•Existing federal incentives are expensive, $36k per additional PEV.•Cost-effectiveness can be improved 2× by targeting incentives by consumer type.
Despite the prevalence of plug-in electric vehicle (PEV) subsidies, research on improving their cost-effectiveness and impact remains limited. To assess the scope for improving their cost-effectiveness, we develop a vehicle choice model-based counterfactual simulation using a large-scale nationally representative sample of U.S. new car buyers. Results suggest that existing federal incentives are expensive, $36k per additional PEV, as every buyer gets the subsidy. The cost-effectiveness can be improved by twofold by targeting incentives by income, vehicle disposal, geography, and/or vehicle miles traveled. Preserving the federal policy's assignment of larger subsidies for PEVs with larger battery capacities results in greater battery electric vehicle (BEV) adoption, while policies not discriminating by battery capacity result in greater plug-in hybrid electric vehicle adoption. The reduction in gasoline consumption is the same in both the cases, with a slightly lower marginal cost for the latter.</abstract><cop>Kidlington</cop><pub>Elsevier B.V</pub><doi>10.1016/j.eneco.2019.104545</doi><orcidid>https://orcid.org/0000-0002-1355-1202</orcidid><oa>free_for_read</oa></addata></record> |
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subjects | Air pollution Clean vehicles Computer simulation Consumption Cost analysis Costs Decision making models Effectiveness Electric vehicles Energy economics Federal policy Gasoline Geography Hybrid electric vehicles Impact strength Incentives Simulation Subsidies Transportation policy Travel demand |
title | Measuring the cost-effectiveness of electric vehicle subsidies |
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