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
- Institución
- Universidad Nacional de La Plata
- OAI Identificador
- oai:sedici.unlp.edu.ar:10915/169110
Ver los metadatos del registro completo
id |
SEDICI_ece58c7f29710712980ca0bea30e0c18 |
---|---|
oai_identifier_str |
oai:sedici.unlp.edu.ar:10915/169110 |
network_acronym_str |
SEDICI |
repository_id_str |
1329 |
network_name_str |
SEDICI (UNLP) |
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 Objeto de conferencia http://purl.org/coar/resource_type/c_5794 info:ar-repo/semantics/documentoDeConferencia |
format |
conferenceObject |
status_str |
publishedVersion |
dc.identifier.none.fl_str_mv |
http://sedici.unlp.edu.ar/handle/10915/169110 |
url |
http://sedici.unlp.edu.ar/handle/10915/169110 |
dc.language.none.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
info:eu-repo/semantics/altIdentifier/isbn/978-987-28590-6-0 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 |
dc.source.none.fl_str_mv |
reponame:SEDICI (UNLP) instname:Universidad Nacional de La Plata instacron:UNLP |
reponame_str |
SEDICI (UNLP) |
collection |
SEDICI (UNLP) |
instname_str |
Universidad Nacional de La Plata |
instacron_str |
UNLP |
institution |
UNLP |
repository.name.fl_str_mv |
SEDICI (UNLP) - Universidad Nacional de La Plata |
repository.mail.fl_str_mv |
alira@sedici.unlp.edu.ar |
_version_ |
1844616303191523328 |
score |
13.070432 |