Response surface models for the Leybourne unit root tests and lag order dependence

This paper calculates response surface models for a large range of quantiles of the Leybourne (Oxf Bull Econ Stat 57:559-571, 1995) test for the null hypothesis of a unit root against the alternative of (trend) stationarity. The response surface models allow the estimation of critical values for dif...

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Tipo de recurso:
Fecha de publicación:
2012
Institución:
Universidad del Rosario
Repositorio:
Repositorio EdocUR - U. Rosario
Idioma:
eng
OAI Identifier:
oai:repository.urosario.edu.co:10336/23766
Acceso en línea:
https://doi.org/10.1007/s00180-011-0268-y
https://repository.urosario.edu.co/handle/10336/23766
Palabra clave:
Critical values
Lag length
Monte Carlo
P-values
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Abierto (Texto Completo)
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network_acronym_str EDOCUR2
network_name_str Repositorio EdocUR - U. Rosario
repository_id_str
spelling 79242814600ed53a3e2-2b2c-46a6-a77d-51e23954fa8f-12020-05-26T00:05:12Z2020-05-26T00:05:12Z2012This paper calculates response surface models for a large range of quantiles of the Leybourne (Oxf Bull Econ Stat 57:559-571, 1995) test for the null hypothesis of a unit root against the alternative of (trend) stationarity. The response surface models allow the estimation of critical values for different combinations of number of observations, T, and lag order in the test regressions, p, where the latter can be either specified by the user or optimally selected using a data-dependent procedure. The results indicate that the critical values depend on the method used to select the number of lags. An Excel spreadsheet is available to calculate the p-value associated with a test statistic. © 2011 Springer-Verlag.application/pdfhttps://doi.org/10.1007/s00180-011-0268-y9434062https://repository.urosario.edu.co/handle/10336/23766eng486No. 3473Computational StatisticsVol. 27Computational Statistics, ISSN:9434062, Vol.27, No.3 (2012); pp. 473-486https://www.scopus.com/inward/record.uri?eid=2-s2.0-84864388024&doi=10.1007%2fs00180-011-0268-y&partnerID=40&md5=636ad3440bb55fe7e3f5668e17294a45Abierto (Texto Completo)http://purl.org/coar/access_right/c_abf2instname:Universidad del Rosarioreponame:Repositorio Institucional EdocURCritical valuesLag lengthMonte CarloP-valuesResponse surface models for the Leybourne unit root tests and lag order dependencearticleArtículohttp://purl.org/coar/version/c_970fb48d4fbd8a85http://purl.org/coar/resource_type/c_6501Otero Cardona, Jesús GilbertoSmith, Jeremy10336/23766oai:repository.urosario.edu.co:10336/237662022-05-02 07:37:14.653957https://repository.urosario.edu.coRepositorio institucional EdocURedocur@urosario.edu.co
dc.title.spa.fl_str_mv Response surface models for the Leybourne unit root tests and lag order dependence
title Response surface models for the Leybourne unit root tests and lag order dependence
spellingShingle Response surface models for the Leybourne unit root tests and lag order dependence
Critical values
Lag length
Monte Carlo
P-values
title_short Response surface models for the Leybourne unit root tests and lag order dependence
title_full Response surface models for the Leybourne unit root tests and lag order dependence
title_fullStr Response surface models for the Leybourne unit root tests and lag order dependence
title_full_unstemmed Response surface models for the Leybourne unit root tests and lag order dependence
title_sort Response surface models for the Leybourne unit root tests and lag order dependence
dc.subject.keyword.spa.fl_str_mv Critical values
Lag length
Monte Carlo
P-values
topic Critical values
Lag length
Monte Carlo
P-values
description This paper calculates response surface models for a large range of quantiles of the Leybourne (Oxf Bull Econ Stat 57:559-571, 1995) test for the null hypothesis of a unit root against the alternative of (trend) stationarity. The response surface models allow the estimation of critical values for different combinations of number of observations, T, and lag order in the test regressions, p, where the latter can be either specified by the user or optimally selected using a data-dependent procedure. The results indicate that the critical values depend on the method used to select the number of lags. An Excel spreadsheet is available to calculate the p-value associated with a test statistic. © 2011 Springer-Verlag.
publishDate 2012
dc.date.created.spa.fl_str_mv 2012
dc.date.accessioned.none.fl_str_mv 2020-05-26T00:05:12Z
dc.date.available.none.fl_str_mv 2020-05-26T00:05:12Z
dc.type.eng.fl_str_mv article
dc.type.coarversion.fl_str_mv http://purl.org/coar/version/c_970fb48d4fbd8a85
dc.type.coar.fl_str_mv http://purl.org/coar/resource_type/c_6501
dc.type.spa.spa.fl_str_mv Artículo
dc.identifier.doi.none.fl_str_mv https://doi.org/10.1007/s00180-011-0268-y
dc.identifier.issn.none.fl_str_mv 9434062
dc.identifier.uri.none.fl_str_mv https://repository.urosario.edu.co/handle/10336/23766
url https://doi.org/10.1007/s00180-011-0268-y
https://repository.urosario.edu.co/handle/10336/23766
identifier_str_mv 9434062
dc.language.iso.spa.fl_str_mv eng
language eng
dc.relation.citationEndPage.none.fl_str_mv 486
dc.relation.citationIssue.none.fl_str_mv No. 3
dc.relation.citationStartPage.none.fl_str_mv 473
dc.relation.citationTitle.none.fl_str_mv Computational Statistics
dc.relation.citationVolume.none.fl_str_mv Vol. 27
dc.relation.ispartof.spa.fl_str_mv Computational Statistics, ISSN:9434062, Vol.27, No.3 (2012); pp. 473-486
dc.relation.uri.spa.fl_str_mv https://www.scopus.com/inward/record.uri?eid=2-s2.0-84864388024&doi=10.1007%2fs00180-011-0268-y&partnerID=40&md5=636ad3440bb55fe7e3f5668e17294a45
dc.rights.coar.fl_str_mv http://purl.org/coar/access_right/c_abf2
dc.rights.acceso.spa.fl_str_mv Abierto (Texto Completo)
rights_invalid_str_mv Abierto (Texto Completo)
http://purl.org/coar/access_right/c_abf2
dc.format.mimetype.none.fl_str_mv application/pdf
institution Universidad del Rosario
dc.source.instname.spa.fl_str_mv instname:Universidad del Rosario
dc.source.reponame.spa.fl_str_mv reponame:Repositorio Institucional EdocUR
repository.name.fl_str_mv Repositorio institucional EdocUR
repository.mail.fl_str_mv edocur@urosario.edu.co
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