A distributional synthetic control method for policy evaluation
Summary We extend the synthetic control method to evaluate the distributional effects of policy intervention in the possible presence of poor matching. The counterfactuals (or intervention effects) are identified by matching a vector of pre‐intervention quantile residuals of the treated unit and a c...
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Veröffentlicht in: | Journal of applied econometrics (Chichester, England) England), 2020-08, Vol.35 (5), p.505-525 |
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container_title | Journal of applied econometrics (Chichester, England) |
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creator | Chen, Yi‐Ting |
description | Summary
We extend the synthetic control method to evaluate the distributional effects of policy intervention in the possible presence of poor matching. The counterfactuals (or intervention effects) are identified by matching a vector of pre‐intervention quantile residuals of the treated unit and a convex combination of its potential‐control counterparts. The residuals are orthogonal to a set of observable common factors that control for the potentially poor matching. We also apply our method to a set of case studies that explore the distributional effects of state‐level minimum‐wage hikes in the USA. |
doi_str_mv | 10.1002/jae.2778 |
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We extend the synthetic control method to evaluate the distributional effects of policy intervention in the possible presence of poor matching. The counterfactuals (or intervention effects) are identified by matching a vector of pre‐intervention quantile residuals of the treated unit and a convex combination of its potential‐control counterparts. The residuals are orthogonal to a set of observable common factors that control for the potentially poor matching. We also apply our method to a set of case studies that explore the distributional effects of state‐level minimum‐wage hikes in the USA.</description><identifier>ISSN: 0883-7252</identifier><identifier>EISSN: 1099-1255</identifier><identifier>DOI: 10.1002/jae.2778</identifier><language>eng</language><publisher>Chichester: Wiley Periodicals Inc</publisher><subject>Econometrics ; Intervention ; Matching ; Minimum wage</subject><ispartof>Journal of applied econometrics (Chichester, England), 2020-08, Vol.35 (5), p.505-525</ispartof><rights>2020 John Wiley & Sons, Ltd.</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c3268-6e63b1c0f68ca27acb6c70b5bc149c7e450df7a4deafb4dbde6807dccf8fbd2e3</citedby><cites>FETCH-LOGICAL-c3268-6e63b1c0f68ca27acb6c70b5bc149c7e450df7a4deafb4dbde6807dccf8fbd2e3</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://onlinelibrary.wiley.com/doi/pdf/10.1002%2Fjae.2778$$EPDF$$P50$$Gwiley$$H</linktopdf><linktohtml>$$Uhttps://onlinelibrary.wiley.com/doi/full/10.1002%2Fjae.2778$$EHTML$$P50$$Gwiley$$H</linktohtml><link.rule.ids>314,780,784,1416,27923,27924,45573,45574</link.rule.ids></links><search><creatorcontrib>Chen, Yi‐Ting</creatorcontrib><title>A distributional synthetic control method for policy evaluation</title><title>Journal of applied econometrics (Chichester, England)</title><description>Summary
We extend the synthetic control method to evaluate the distributional effects of policy intervention in the possible presence of poor matching. The counterfactuals (or intervention effects) are identified by matching a vector of pre‐intervention quantile residuals of the treated unit and a convex combination of its potential‐control counterparts. The residuals are orthogonal to a set of observable common factors that control for the potentially poor matching. We also apply our method to a set of case studies that explore the distributional effects of state‐level minimum‐wage hikes in the USA.</description><subject>Econometrics</subject><subject>Intervention</subject><subject>Matching</subject><subject>Minimum wage</subject><issn>0883-7252</issn><issn>1099-1255</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2020</creationdate><recordtype>article</recordtype><recordid>eNp10EtLAzEQwPEgCtYH-BECXrxsnWSzyfYkpdQXBS96DnnSlG1Tk6yy396t9eppLr8Zhj9CNwSmBIDeb5SbUiHaEzQhMJtVhDbNKZpA29aVoA09Rxc5bwCAA4gJephjG3JJQfclxJ3qcB52Ze1KMNjEXUmxw1tX1tFiHxPexy6YAbsv1fXqsHCFzrzqsrv-m5fo43H5vniuVm9PL4v5qjI15W3FHa81MeB5axQVymhuBOhGG8JmRjjWgPVCMeuU18xq63gLwhrjW68tdfUluj3e3af42btc5Cb2afw3S8pqximpGR3V3VGZFHNOzst9CluVBklAHvLIMY885BlpdaTfoXPDv06-zpe__gda1mfN</recordid><startdate>202008</startdate><enddate>202008</enddate><creator>Chen, Yi‐Ting</creator><general>Wiley Periodicals Inc</general><scope>AAYXX</scope><scope>CITATION</scope><scope>8BJ</scope><scope>FQK</scope><scope>JBE</scope><scope>JQ2</scope></search><sort><creationdate>202008</creationdate><title>A distributional synthetic control method for policy evaluation</title><author>Chen, Yi‐Ting</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c3268-6e63b1c0f68ca27acb6c70b5bc149c7e450df7a4deafb4dbde6807dccf8fbd2e3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2020</creationdate><topic>Econometrics</topic><topic>Intervention</topic><topic>Matching</topic><topic>Minimum wage</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Chen, Yi‐Ting</creatorcontrib><collection>CrossRef</collection><collection>International Bibliography of the Social Sciences (IBSS)</collection><collection>International Bibliography of the Social Sciences</collection><collection>International Bibliography of the Social Sciences</collection><collection>ProQuest Computer Science Collection</collection><jtitle>Journal of applied econometrics (Chichester, England)</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Chen, Yi‐Ting</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>A distributional synthetic control method for policy evaluation</atitle><jtitle>Journal of applied econometrics (Chichester, England)</jtitle><date>2020-08</date><risdate>2020</risdate><volume>35</volume><issue>5</issue><spage>505</spage><epage>525</epage><pages>505-525</pages><issn>0883-7252</issn><eissn>1099-1255</eissn><abstract>Summary
We extend the synthetic control method to evaluate the distributional effects of policy intervention in the possible presence of poor matching. The counterfactuals (or intervention effects) are identified by matching a vector of pre‐intervention quantile residuals of the treated unit and a convex combination of its potential‐control counterparts. The residuals are orthogonal to a set of observable common factors that control for the potentially poor matching. We also apply our method to a set of case studies that explore the distributional effects of state‐level minimum‐wage hikes in the USA.</abstract><cop>Chichester</cop><pub>Wiley Periodicals Inc</pub><doi>10.1002/jae.2778</doi><tpages>21</tpages></addata></record> |
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subjects | Econometrics Intervention Matching Minimum wage |
title | A distributional synthetic control method for policy evaluation |
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