Quantiles via moments
Autor(a) principal: | |
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Data de Publicação: | 2019 |
Outros Autores: | |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
Texto Completo: | http://hdl.handle.net/10362/161234 |
Resumo: | We study the conditions under which it is possible to estimate regression quantiles by estimating conditional means. The advantage of this approach is that it allows the use of methods that are only valid in the estimation of conditional means, while still providing information on how the regressors affect the entire conditional distribution. The methods we propose are not meant to replace the well-established quantile regression estimator, but provide an additional tool that can allow the estimation of regression quantiles in settings where otherwise that would be difficult or even impossible. We consider two settings in which our approach can be particularly useful: panel data models with individual effects and models with endogenous explanatory variables. Besides presenting the estimator and establishing the regularity conditions needed for valid inference, we perform a small simulation experiment, present two simple illustrative applications, and discuss possible extensions. |
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Quantiles via momentsEndogeneityFixed effectsLinear heteroskedasticityLocation-scale modelQuantile regressionEconomics and EconometricsWe study the conditions under which it is possible to estimate regression quantiles by estimating conditional means. The advantage of this approach is that it allows the use of methods that are only valid in the estimation of conditional means, while still providing information on how the regressors affect the entire conditional distribution. The methods we propose are not meant to replace the well-established quantile regression estimator, but provide an additional tool that can allow the estimation of regression quantiles in settings where otherwise that would be difficult or even impossible. We consider two settings in which our approach can be particularly useful: panel data models with individual effects and models with endogenous explanatory variables. Besides presenting the estimator and establishing the regularity conditions needed for valid inference, we perform a small simulation experiment, present two simple illustrative applications, and discuss possible extensions.NOVA School of Business and Economics (NOVA SBE)RUNMachado, José A.F.Santos Silva, J. M.C.2023-12-13T22:14:29Z2019-11-012019-11-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://hdl.handle.net/10362/161234eng0304-4076PURE: 13072537https://doi.org/10.1016/j.jeconom.2019.04.009info:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2024-03-11T05:44:05Zoai:run.unl.pt:10362/161234Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-20T03:58:26.472553Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse |
dc.title.none.fl_str_mv |
Quantiles via moments |
title |
Quantiles via moments |
spellingShingle |
Quantiles via moments Machado, José A.F. Endogeneity Fixed effects Linear heteroskedasticity Location-scale model Quantile regression Economics and Econometrics |
title_short |
Quantiles via moments |
title_full |
Quantiles via moments |
title_fullStr |
Quantiles via moments |
title_full_unstemmed |
Quantiles via moments |
title_sort |
Quantiles via moments |
author |
Machado, José A.F. |
author_facet |
Machado, José A.F. Santos Silva, J. M.C. |
author_role |
author |
author2 |
Santos Silva, J. M.C. |
author2_role |
author |
dc.contributor.none.fl_str_mv |
NOVA School of Business and Economics (NOVA SBE) RUN |
dc.contributor.author.fl_str_mv |
Machado, José A.F. Santos Silva, J. M.C. |
dc.subject.por.fl_str_mv |
Endogeneity Fixed effects Linear heteroskedasticity Location-scale model Quantile regression Economics and Econometrics |
topic |
Endogeneity Fixed effects Linear heteroskedasticity Location-scale model Quantile regression Economics and Econometrics |
description |
We study the conditions under which it is possible to estimate regression quantiles by estimating conditional means. The advantage of this approach is that it allows the use of methods that are only valid in the estimation of conditional means, while still providing information on how the regressors affect the entire conditional distribution. The methods we propose are not meant to replace the well-established quantile regression estimator, but provide an additional tool that can allow the estimation of regression quantiles in settings where otherwise that would be difficult or even impossible. We consider two settings in which our approach can be particularly useful: panel data models with individual effects and models with endogenous explanatory variables. Besides presenting the estimator and establishing the regularity conditions needed for valid inference, we perform a small simulation experiment, present two simple illustrative applications, and discuss possible extensions. |
publishDate |
2019 |
dc.date.none.fl_str_mv |
2019-11-01 2019-11-01T00:00:00Z 2023-12-13T22:14:29Z |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://hdl.handle.net/10362/161234 |
url |
http://hdl.handle.net/10362/161234 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
0304-4076 PURE: 13072537 https://doi.org/10.1016/j.jeconom.2019.04.009 |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
application/pdf |
dc.source.none.fl_str_mv |
reponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação instacron:RCAAP |
instname_str |
Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
instacron_str |
RCAAP |
institution |
RCAAP |
reponame_str |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
collection |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
repository.name.fl_str_mv |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
repository.mail.fl_str_mv |
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1799138165200519168 |