Nonparametric multidimensional fixed effects panel data models

Multidimensional panel datasets are routinely employed to identify marginal effects in empirical research. Fixed effects estimators are typically used to deal with potential correlation between unobserved effects and regressors. Nonparametric estimators for one-way fixed effects models exist, but ar...

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Detalles Bibliográficos
Autores: Henderson, Daniel J., Soberón Velez, Alexandra Pilar|||0000-0001-5268-6751, Rodríguez-Poo, Juan M.|||0000-0001-8751-3025
Tipo de recurso: artículo
Fecha de publicación:2022
País:España
Institución:Universidad de Cantabria (UC)
Repositorio:UCrea Repositorio Abierto de la Universidad de Cantabria
Idioma:inglés
OAI Identifier:oai:repositorio.unican.es:10902/31423
Acceso en línea:https://hdl.handle.net/10902/31423
Access Level:acceso abierto
Palabra clave:Panel
Fixed effects
Multidimensional
Nonparametric
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spelling Nonparametric multidimensional fixed effects panel data modelsHenderson, Daniel J.Soberón Velez, Alexandra Pilar|||0000-0001-5268-6751 Rodríguez-Poo, Juan M.|||0000-0001-8751-3025PanelFixed effectsMultidimensionalNonparametricMultidimensional panel datasets are routinely employed to identify marginal effects in empirical research. Fixed effects estimators are typically used to deal with potential correlation between unobserved effects and regressors. Nonparametric estimators for one-way fixed effects models exist, but are cumbersome to employ in practice as they typically require iteration, marginal integration or profile estimation. We develop a nonparametric estimator that works for essentially any dimension fixed effects model, has a closed form solution and can be estimated in a single step. A cross-validation bandwidth selection procedure is proposed and asymptotic properties (for either a fixed or large time dimension) are given. Finite sample properties are shown via simulations, as well as with an empirical application, which further extends our model to the partially linear setting.Taylor & FrancisUniversidad de Cantabria20222022-01-01journal articlehttp://purl.org/coar/resource_type/c_6501NAhttp://purl.org/coar/version/c_be7fb7dd8ff6fe43info:eu-repo/semantics/articlehttps://hdl.handle.net/10902/31423Econometric Reviews, 2022, 41(3), 321-358reponame:UCrea Repositorio Abierto de la Universidad de Cantabriainstname:Universidad de Cantabria (UC)Inglésengopen accesshttp://purl.org/coar/access_right/c_abf2info:eu-repo/semantics/openAccessoai:repositorio.unican.es:10902/314232026-06-02T12:39:31Z
dc.title.none.fl_str_mv Nonparametric multidimensional fixed effects panel data models
title Nonparametric multidimensional fixed effects panel data models
spellingShingle Nonparametric multidimensional fixed effects panel data models
Henderson, Daniel J.
Panel
Fixed effects
Multidimensional
Nonparametric
title_short Nonparametric multidimensional fixed effects panel data models
title_full Nonparametric multidimensional fixed effects panel data models
title_fullStr Nonparametric multidimensional fixed effects panel data models
title_full_unstemmed Nonparametric multidimensional fixed effects panel data models
title_sort Nonparametric multidimensional fixed effects panel data models
dc.creator.none.fl_str_mv Henderson, Daniel J.
Soberón Velez, Alexandra Pilar|||0000-0001-5268-6751
Rodríguez-Poo, Juan M.|||0000-0001-8751-3025
author Henderson, Daniel J.
author_facet Henderson, Daniel J.
Soberón Velez, Alexandra Pilar|||0000-0001-5268-6751
Rodríguez-Poo, Juan M.|||0000-0001-8751-3025
author_role author
author2 Soberón Velez, Alexandra Pilar|||0000-0001-5268-6751
Rodríguez-Poo, Juan M.|||0000-0001-8751-3025
author2_role author
author
dc.contributor.none.fl_str_mv Universidad de Cantabria
dc.subject.none.fl_str_mv Panel
Fixed effects
Multidimensional
Nonparametric
topic Panel
Fixed effects
Multidimensional
Nonparametric
description Multidimensional panel datasets are routinely employed to identify marginal effects in empirical research. Fixed effects estimators are typically used to deal with potential correlation between unobserved effects and regressors. Nonparametric estimators for one-way fixed effects models exist, but are cumbersome to employ in practice as they typically require iteration, marginal integration or profile estimation. We develop a nonparametric estimator that works for essentially any dimension fixed effects model, has a closed form solution and can be estimated in a single step. A cross-validation bandwidth selection procedure is proposed and asymptotic properties (for either a fixed or large time dimension) are given. Finite sample properties are shown via simulations, as well as with an empirical application, which further extends our model to the partially linear setting.
publishDate 2022
dc.date.none.fl_str_mv 2022
2022-01-01
dc.type.none.fl_str_mv journal article
http://purl.org/coar/resource_type/c_6501
NA
http://purl.org/coar/version/c_be7fb7dd8ff6fe43
dc.type.openaire.fl_str_mv info:eu-repo/semantics/article
format article
dc.identifier.none.fl_str_mv https://hdl.handle.net/10902/31423
url https://hdl.handle.net/10902/31423
dc.language.none.fl_str_mv Inglés
eng
language_invalid_str_mv Inglés
language eng
dc.rights.none.fl_str_mv open access
http://purl.org/coar/access_right/c_abf2
dc.rights.openaire.fl_str_mv info:eu-repo/semantics/openAccess
rights_invalid_str_mv open access
http://purl.org/coar/access_right/c_abf2
eu_rights_str_mv openAccess
dc.publisher.none.fl_str_mv Taylor & Francis
publisher.none.fl_str_mv Taylor & Francis
dc.source.none.fl_str_mv Econometric Reviews, 2022, 41(3), 321-358
reponame:UCrea Repositorio Abierto de la Universidad de Cantabria
instname:Universidad de Cantabria (UC)
instname_str Universidad de Cantabria (UC)
reponame_str UCrea Repositorio Abierto de la Universidad de Cantabria
collection UCrea Repositorio Abierto de la Universidad de Cantabria
repository.name.fl_str_mv
repository.mail.fl_str_mv
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score 15.300719

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