Efficient semiparametric estimation of quantile treatment effects

Detalhes bibliográficos
Autor(a) principal: Firpo, Sergio Pinheiro
Data de Publicação: 2003
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Institucional do FGV (FGV Repositório Digital)
Texto Completo: http://hdl.handle.net/10438/12995
Resumo: This paper presents calculations of semiparametric efficiency bounds for quantile treatment effects parameters when se1ection to treatment is based on observable characteristics. The paper also presents three estimation procedures forthese parameters, alI ofwhich have two steps: a nonparametric estimation and a computation ofthe difference between the solutions of two distinct minimization problems. Root-N consistency, asymptotic normality, and the achievement ofthe semiparametric efficiency bound is shown for one ofthe three estimators. In the final part ofthe paper, an empirical application to a job training program reveals the importance of heterogeneous treatment effects, showing that for this program the effects are concentrated in the upper quantiles ofthe earnings distribution.
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spelling Firpo, Sergio PinheiroEscolas::EPGEFGV2014-12-23T14:36:12Z2014-12-23T14:36:12Z2003-01http://hdl.handle.net/10438/12995This paper presents calculations of semiparametric efficiency bounds for quantile treatment effects parameters when se1ection to treatment is based on observable characteristics. The paper also presents three estimation procedures forthese parameters, alI ofwhich have two steps: a nonparametric estimation and a computation ofthe difference between the solutions of two distinct minimization problems. Root-N consistency, asymptotic normality, and the achievement ofthe semiparametric efficiency bound is shown for one ofthe three estimators. In the final part ofthe paper, an empirical application to a job training program reveals the importance of heterogeneous treatment effects, showing that for this program the effects are concentrated in the upper quantiles ofthe earnings distribution.engFundação Getulio Vargas. Escola de Pós-graduação em EconomiaSeminários de Almoço da EPGETodo cuidado foi dispensado para respeitar os direitos autorais deste trabalho. Entretanto, caso esta obra aqui depositada seja protegida por direitos autorais externos a esta instituição, contamos com a compreensão do autor e solicitamos que o mesmo faça contato através do Fale Conosco para que possamos tomar as providências cabíveisinfo:eu-repo/semantics/openAccessQuantile treatment effectsPropensity scoreSemiparametric efficiency boundsEfficient estimationSemiparametric estimationEconomiaEconometriaModelos econométricosEfficient semiparametric estimation of quantile treatment effectsinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articlereponame:Repositório Institucional do FGV (FGV Repositório Digital)instname:Fundação Getulio Vargas (FGV)instacron:FGVORIGINAL000314893_f527e.pdf000314893_f527e.pdfapplication/pdf1847020https://repositorio.fgv.br/bitstreams/37b5d472-0bd3-413b-a5e3-383e70820ce5/downloadb628cc10448b97ac96d5e58880aaf530MD51LICENSElicense.txtlicense.txttext/plain; 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dc.title.eng.fl_str_mv Efficient semiparametric estimation of quantile treatment effects
title Efficient semiparametric estimation of quantile treatment effects
spellingShingle Efficient semiparametric estimation of quantile treatment effects
Firpo, Sergio Pinheiro
Quantile treatment effects
Propensity score
Semiparametric efficiency bounds
Efficient estimation
Semiparametric estimation
Economia
Econometria
Modelos econométricos
title_short Efficient semiparametric estimation of quantile treatment effects
title_full Efficient semiparametric estimation of quantile treatment effects
title_fullStr Efficient semiparametric estimation of quantile treatment effects
title_full_unstemmed Efficient semiparametric estimation of quantile treatment effects
title_sort Efficient semiparametric estimation of quantile treatment effects
author Firpo, Sergio Pinheiro
author_facet Firpo, Sergio Pinheiro
author_role author
dc.contributor.unidadefgv.por.fl_str_mv Escolas::EPGE
dc.contributor.affiliation.none.fl_str_mv FGV
dc.contributor.author.fl_str_mv Firpo, Sergio Pinheiro
dc.subject.por.fl_str_mv Quantile treatment effects
Propensity score
Semiparametric efficiency bounds
Efficient estimation
Semiparametric estimation
topic Quantile treatment effects
Propensity score
Semiparametric efficiency bounds
Efficient estimation
Semiparametric estimation
Economia
Econometria
Modelos econométricos
dc.subject.area.por.fl_str_mv Economia
dc.subject.bibliodata.por.fl_str_mv Econometria
Modelos econométricos
description This paper presents calculations of semiparametric efficiency bounds for quantile treatment effects parameters when se1ection to treatment is based on observable characteristics. The paper also presents three estimation procedures forthese parameters, alI ofwhich have two steps: a nonparametric estimation and a computation ofthe difference between the solutions of two distinct minimization problems. Root-N consistency, asymptotic normality, and the achievement ofthe semiparametric efficiency bound is shown for one ofthe three estimators. In the final part ofthe paper, an empirical application to a job training program reveals the importance of heterogeneous treatment effects, showing that for this program the effects are concentrated in the upper quantiles ofthe earnings distribution.
publishDate 2003
dc.date.issued.fl_str_mv 2003-01
dc.date.accessioned.fl_str_mv 2014-12-23T14:36:12Z
dc.date.available.fl_str_mv 2014-12-23T14:36:12Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
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status_str publishedVersion
dc.identifier.uri.fl_str_mv http://hdl.handle.net/10438/12995
url http://hdl.handle.net/10438/12995
dc.language.iso.fl_str_mv eng
language eng
dc.relation.ispartofseries.por.fl_str_mv Seminários de Almoço da EPGE
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
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dc.publisher.none.fl_str_mv Fundação Getulio Vargas. Escola de Pós-graduação em Economia
publisher.none.fl_str_mv Fundação Getulio Vargas. Escola de Pós-graduação em Economia
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