Nearly unbiased estimation of autoregressive models for bounded near‐integrated stochastic processes

The paper investigates the estimation bias of autoregressive models for bounded near‐integrated stochastic processes and the performance of the standard procedures in the literature that aim to correct the estimation bias. In some cases, the bounded nature of the stochastic processes worsens the est...

Descripción completa

Detalles Bibliográficos
Autores: Carrión i Silvestre, Josep Lluís, Gadea Rivas, María Dolores, Montañés, Antonio
Tipo de recurso: artículo
Estado:Versión aceptada para publicación
Fecha de publicación:2021
País:España
Institución:Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya)
Repositorio:Recercat. Dipósit de la Recerca de Catalunya
OAI Identifier:oai:recercat.cat:2445/173440
Acceso en línea:https://hdl.handle.net/2445/173440
Access Level:acceso abierto
Palabra clave:Econometria
Anàlisi de regressió
Anàlisi estocàstica
Mètode de Montecarlo
Econometrics
Regression analysis
Analyse stochastique
Monte Carlo method
id ES_fbc110fa3c5d671b5918b22daaf9babf
oai_identifier_str oai:recercat.cat:2445/173440
network_acronym_str ES
network_name_str España
repository_id_str
spelling Nearly unbiased estimation of autoregressive models for bounded near‐integrated stochastic processesCarrión i Silvestre, Josep LluísGadea Rivas, María DoloresMontañés, AntonioEconometriaAnàlisi de regressióAnàlisi estocàsticaMètode de MontecarloEconometricsRegression analysisAnalyse stochastiqueMonte Carlo methodThe paper investigates the estimation bias of autoregressive models for bounded near‐integrated stochastic processes and the performance of the standard procedures in the literature that aim to correct the estimation bias. In some cases, the bounded nature of the stochastic processes worsens the estimation bias effect. The paper extends two popular autoregressive estimation bias correction procedures to cover bounded stochastic processes. Monte Carlo simulations reveal that accounting for the bounded nature of the stochastic processes leads to improvements in the estimation of autoregressive models. Finally, an illustration is given using the unemployment rate of the G7 countries.John Wiley & Sons2021202320212021info:eu-repo/semantics/articleinfo:eu-repo/semantics/acceptedVersion25 p.application/pdfhttps://hdl.handle.net/2445/173440Articles publicats en revistes (Econometria, Estadística i Economia Aplicada)reponame:Recercat. Dipósit de la Recerca de Catalunyainstname:Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya)InglésVersió postprint del document publicat a: https://doi.org/10.1111/obes.12399Oxford Bulletin of Economics and Statistics, 2021, vol. 83, num. 1, p. 273-297https://doi.org/10.1111/obes.12399(c) The Department of Economics, University of Oxford and John Wiley & Sons , 2021info:eu-repo/semantics/openAccessoai:recercat.cat:2445/1734402026-05-29T05:05:01Z
dc.title.none.fl_str_mv Nearly unbiased estimation of autoregressive models for bounded near‐integrated stochastic processes
title Nearly unbiased estimation of autoregressive models for bounded near‐integrated stochastic processes
spellingShingle Nearly unbiased estimation of autoregressive models for bounded near‐integrated stochastic processes
Carrión i Silvestre, Josep Lluís
Econometria
Anàlisi de regressió
Anàlisi estocàstica
Mètode de Montecarlo
Econometrics
Regression analysis
Analyse stochastique
Monte Carlo method
title_short Nearly unbiased estimation of autoregressive models for bounded near‐integrated stochastic processes
title_full Nearly unbiased estimation of autoregressive models for bounded near‐integrated stochastic processes
title_fullStr Nearly unbiased estimation of autoregressive models for bounded near‐integrated stochastic processes
title_full_unstemmed Nearly unbiased estimation of autoregressive models for bounded near‐integrated stochastic processes
title_sort Nearly unbiased estimation of autoregressive models for bounded near‐integrated stochastic processes
dc.creator.none.fl_str_mv Carrión i Silvestre, Josep Lluís
Gadea Rivas, María Dolores
Montañés, Antonio
author Carrión i Silvestre, Josep Lluís
author_facet Carrión i Silvestre, Josep Lluís
Gadea Rivas, María Dolores
Montañés, Antonio
author_role author
author2 Gadea Rivas, María Dolores
Montañés, Antonio
author2_role author
author
dc.subject.none.fl_str_mv Econometria
Anàlisi de regressió
Anàlisi estocàstica
Mètode de Montecarlo
Econometrics
Regression analysis
Analyse stochastique
Monte Carlo method
topic Econometria
Anàlisi de regressió
Anàlisi estocàstica
Mètode de Montecarlo
Econometrics
Regression analysis
Analyse stochastique
Monte Carlo method
description The paper investigates the estimation bias of autoregressive models for bounded near‐integrated stochastic processes and the performance of the standard procedures in the literature that aim to correct the estimation bias. In some cases, the bounded nature of the stochastic processes worsens the estimation bias effect. The paper extends two popular autoregressive estimation bias correction procedures to cover bounded stochastic processes. Monte Carlo simulations reveal that accounting for the bounded nature of the stochastic processes leads to improvements in the estimation of autoregressive models. Finally, an illustration is given using the unemployment rate of the G7 countries.
publishDate 2021
dc.date.none.fl_str_mv 2021
2021
2021
2023
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/acceptedVersion
format article
status_str acceptedVersion
dc.identifier.none.fl_str_mv https://hdl.handle.net/2445/173440
url https://hdl.handle.net/2445/173440
dc.language.none.fl_str_mv Inglés
language_invalid_str_mv Inglés
dc.relation.none.fl_str_mv Versió postprint del document publicat a: https://doi.org/10.1111/obes.12399
Oxford Bulletin of Economics and Statistics, 2021, vol. 83, num. 1, p. 273-297
https://doi.org/10.1111/obes.12399
dc.rights.none.fl_str_mv (c) The Department of Economics, University of Oxford and John Wiley & Sons , 2021
info:eu-repo/semantics/openAccess
rights_invalid_str_mv (c) The Department of Economics, University of Oxford and John Wiley & Sons , 2021
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv 25 p.
application/pdf
dc.publisher.none.fl_str_mv John Wiley & Sons
publisher.none.fl_str_mv John Wiley & Sons
dc.source.none.fl_str_mv Articles publicats en revistes (Econometria, Estadística i Economia Aplicada)
reponame:Recercat. Dipósit de la Recerca de Catalunya
instname:Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya)
instname_str Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya)
reponame_str Recercat. Dipósit de la Recerca de Catalunya
collection Recercat. Dipósit de la Recerca de Catalunya
repository.name.fl_str_mv
repository.mail.fl_str_mv
_version_ 1869425358685601792
score 15.812429

Similares en LA Referencia