A practical generalized propensity score estimator for quantile continuous treatment effects

Autores
Alejo, Javier; Galvao, Antonio; Montes Rojas, Gabriel
Año de publicación
2018
Idioma
inglés
Tipo de recurso
documento de conferencia
Estado
versión publicada
Descripción
A new Stata command, qcte, is proposed to implement several methods for estimation and inference for quantile treatment effects models with a continuous treatment. An easy semiparametric two-step estimator, where the first step is based on a flexible Box-Cox model is proposed as the default model of the command. Practical statistical inference procedures are developed using bootstrap. We implement some simulations exercises to show that the proposed methods have good performance. Finally, the command is applied to a survey of Massachusetts lottery winners to estimate the unconditional quantile effects of the prize amount, as a proxy of non-labor income changes, on subsequent labor earnings from U.S. Social Security records. The empirical results reveal strong heterogeneity across unconditional quantiles.
Facultad de Ciencias Económicas
Materia
Ciencias Económicas
st000l
qcte
quantile treatment effects
continuous treatment
quantile regression
Nivel de accesibilidad
acceso abierto
Condiciones de uso
http://creativecommons.org/licenses/by-nc-sa/4.0/
Repositorio
SEDICI (UNLP)
Institución
Universidad Nacional de La Plata
OAI Identificador
oai:sedici.unlp.edu.ar:10915/169110

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spelling A practical generalized propensity score estimator for quantile continuous treatment effectsAlejo, JavierGalvao, AntonioMontes Rojas, GabrielCiencias Económicasst000lqctequantile treatment effectscontinuous treatmentquantile regressionA new Stata command, qcte, is proposed to implement several methods for estimation and inference for quantile treatment effects models with a continuous treatment. An easy semiparametric two-step estimator, where the first step is based on a flexible Box-Cox model is proposed as the default model of the command. Practical statistical inference procedures are developed using bootstrap. We implement some simulations exercises to show that the proposed methods have good performance. Finally, the command is applied to a survey of Massachusetts lottery winners to estimate the unconditional quantile effects of the prize amount, as a proxy of non-labor income changes, on subsequent labor earnings from U.S. Social Security records. The empirical results reveal strong heterogeneity across unconditional quantiles.Facultad de Ciencias Económicas2018-11info:eu-repo/semantics/conferenceObjectinfo:eu-repo/semantics/publishedVersionObjeto de conferenciahttp://purl.org/coar/resource_type/c_5794info:ar-repo/semantics/documentoDeConferenciaapplication/pdfhttp://sedici.unlp.edu.ar/handle/10915/169110enginfo:eu-repo/semantics/altIdentifier/isbn/978-987-28590-6-0info:eu-repo/semantics/altIdentifier/url/https://bd.aaep.org.ar/anales/works/works2018/alejo.pdfinfo:eu-repo/semantics/altIdentifier/issn/1852-0022info:eu-repo/semantics/openAccesshttp://creativecommons.org/licenses/by-nc-sa/4.0/Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)reponame:SEDICI (UNLP)instname:Universidad Nacional de La Platainstacron:UNLP2025-09-29T11:43:26Zoai:sedici.unlp.edu.ar:10915/169110Institucionalhttp://sedici.unlp.edu.ar/Universidad públicaNo correspondehttp://sedici.unlp.edu.ar/oai/snrdalira@sedici.unlp.edu.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:13292025-09-29 11:43:27.152SEDICI (UNLP) - Universidad Nacional de La Platafalse
dc.title.none.fl_str_mv A practical generalized propensity score estimator for quantile continuous treatment effects
title A practical generalized propensity score estimator for quantile continuous treatment effects
spellingShingle A practical generalized propensity score estimator for quantile continuous treatment effects
Alejo, Javier
Ciencias Económicas
st000l
qcte
quantile treatment effects
continuous treatment
quantile regression
title_short A practical generalized propensity score estimator for quantile continuous treatment effects
title_full A practical generalized propensity score estimator for quantile continuous treatment effects
title_fullStr A practical generalized propensity score estimator for quantile continuous treatment effects
title_full_unstemmed A practical generalized propensity score estimator for quantile continuous treatment effects
title_sort A practical generalized propensity score estimator for quantile continuous treatment effects
dc.creator.none.fl_str_mv Alejo, Javier
Galvao, Antonio
Montes Rojas, Gabriel
author Alejo, Javier
author_facet Alejo, Javier
Galvao, Antonio
Montes Rojas, Gabriel
author_role author
author2 Galvao, Antonio
Montes Rojas, Gabriel
author2_role author
author
dc.subject.none.fl_str_mv Ciencias Económicas
st000l
qcte
quantile treatment effects
continuous treatment
quantile regression
topic Ciencias Económicas
st000l
qcte
quantile treatment effects
continuous treatment
quantile regression
dc.description.none.fl_txt_mv A new Stata command, qcte, is proposed to implement several methods for estimation and inference for quantile treatment effects models with a continuous treatment. An easy semiparametric two-step estimator, where the first step is based on a flexible Box-Cox model is proposed as the default model of the command. Practical statistical inference procedures are developed using bootstrap. We implement some simulations exercises to show that the proposed methods have good performance. Finally, the command is applied to a survey of Massachusetts lottery winners to estimate the unconditional quantile effects of the prize amount, as a proxy of non-labor income changes, on subsequent labor earnings from U.S. Social Security records. The empirical results reveal strong heterogeneity across unconditional quantiles.
Facultad de Ciencias Económicas
description A new Stata command, qcte, is proposed to implement several methods for estimation and inference for quantile treatment effects models with a continuous treatment. An easy semiparametric two-step estimator, where the first step is based on a flexible Box-Cox model is proposed as the default model of the command. Practical statistical inference procedures are developed using bootstrap. We implement some simulations exercises to show that the proposed methods have good performance. Finally, the command is applied to a survey of Massachusetts lottery winners to estimate the unconditional quantile effects of the prize amount, as a proxy of non-labor income changes, on subsequent labor earnings from U.S. Social Security records. The empirical results reveal strong heterogeneity across unconditional quantiles.
publishDate 2018
dc.date.none.fl_str_mv 2018-11
dc.type.none.fl_str_mv info:eu-repo/semantics/conferenceObject
info:eu-repo/semantics/publishedVersion
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http://purl.org/coar/resource_type/c_5794
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dc.language.none.fl_str_mv eng
language eng
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info:eu-repo/semantics/altIdentifier/url/https://bd.aaep.org.ar/anales/works/works2018/alejo.pdf
info:eu-repo/semantics/altIdentifier/issn/1852-0022
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
http://creativecommons.org/licenses/by-nc-sa/4.0/
Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)
eu_rights_str_mv openAccess
rights_invalid_str_mv http://creativecommons.org/licenses/by-nc-sa/4.0/
Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)
dc.format.none.fl_str_mv application/pdf
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