Quantiles via moments

Detalhes bibliográficos
Autor(a) principal: Machado, José A.F.
Data de Publicação: 2019
Outros Autores: Santos Silva, J. M.C.
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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spelling 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
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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
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eu_rights_str_mv openAccess
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