Testing for persistence in the error component model: a one-sided approach

Autores
Sosa Escudero, Walter
Año de publicación
2013
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
This article proposes new simple testing procedures for the joint null hypothesis of absence of persistent effects, in the form of random effects and first-order serial correlation in the error component model. The fact that the presence of random effects is clearly of a one-sided nature, together with the fact that in many empirical applications researchers worry about positive serial correlation leaves room for a power gain that arises from restricting the parameter space under the alternative hypothesis, compared to existing procedures that allow for two-sided alternatives. A Monte Carlo experiment shows that the proposed statistics have good size and power performance in very small samples like those typically used in applied work in panel data. An empirical example illustrates the usefulness of the proposed statistics.
Fil: Sosa Escudero, Walter. Universidad de San Andrés. Departamento de Economía; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina
Materia
Error Component Model
One-Sided Alternatives
Random Effects
Serial Correlations
Testing
Nivel de accesibilidad
acceso abierto
Condiciones de uso
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
Repositorio
CONICET Digital (CONICET)
Institución
Consejo Nacional de Investigaciones Científicas y Técnicas
OAI Identificador
oai:ri.conicet.gov.ar:11336/24593

id CONICETDig_83d3c51566e4f91f64ce0e0045fc62c5
oai_identifier_str oai:ri.conicet.gov.ar:11336/24593
network_acronym_str CONICETDig
repository_id_str 3498
network_name_str CONICET Digital (CONICET)
spelling Testing for persistence in the error component model: a one-sided approachSosa Escudero, WalterError Component ModelOne-Sided AlternativesRandom EffectsSerial CorrelationsTestinghttps://purl.org/becyt/ford/5.2https://purl.org/becyt/ford/5This article proposes new simple testing procedures for the joint null hypothesis of absence of persistent effects, in the form of random effects and first-order serial correlation in the error component model. The fact that the presence of random effects is clearly of a one-sided nature, together with the fact that in many empirical applications researchers worry about positive serial correlation leaves room for a power gain that arises from restricting the parameter space under the alternative hypothesis, compared to existing procedures that allow for two-sided alternatives. A Monte Carlo experiment shows that the proposed statistics have good size and power performance in very small samples like those typically used in applied work in panel data. An empirical example illustrates the usefulness of the proposed statistics.Fil: Sosa Escudero, Walter. Universidad de San Andrés. Departamento de Economía; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaTaylor & Francis2013-06info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/24593Sosa Escudero, Walter; Testing for persistence in the error component model: a one-sided approach; Taylor & Francis; Communications In Statistics-theory And Methods; 42; 14; 6-2013; 2601-26160361-0926CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/url/http://www.tandfonline.com/doi/abs/10.1080/03610926.2011.611606info:eu-repo/semantics/altIdentifier/doi/10.1080/03610926.2011.611606info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-sa/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-09-03T10:09:29Zoai:ri.conicet.gov.ar:11336/24593instacron:CONICETInstitucionalhttp://ri.conicet.gov.ar/Organismo científico-tecnológicoNo correspondehttp://ri.conicet.gov.ar/oai/requestdasensio@conicet.gov.ar; lcarlino@conicet.gov.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:34982025-09-03 10:09:29.383CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv Testing for persistence in the error component model: a one-sided approach
title Testing for persistence in the error component model: a one-sided approach
spellingShingle Testing for persistence in the error component model: a one-sided approach
Sosa Escudero, Walter
Error Component Model
One-Sided Alternatives
Random Effects
Serial Correlations
Testing
title_short Testing for persistence in the error component model: a one-sided approach
title_full Testing for persistence in the error component model: a one-sided approach
title_fullStr Testing for persistence in the error component model: a one-sided approach
title_full_unstemmed Testing for persistence in the error component model: a one-sided approach
title_sort Testing for persistence in the error component model: a one-sided approach
dc.creator.none.fl_str_mv Sosa Escudero, Walter
author Sosa Escudero, Walter
author_facet Sosa Escudero, Walter
author_role author
dc.subject.none.fl_str_mv Error Component Model
One-Sided Alternatives
Random Effects
Serial Correlations
Testing
topic Error Component Model
One-Sided Alternatives
Random Effects
Serial Correlations
Testing
purl_subject.fl_str_mv https://purl.org/becyt/ford/5.2
https://purl.org/becyt/ford/5
dc.description.none.fl_txt_mv This article proposes new simple testing procedures for the joint null hypothesis of absence of persistent effects, in the form of random effects and first-order serial correlation in the error component model. The fact that the presence of random effects is clearly of a one-sided nature, together with the fact that in many empirical applications researchers worry about positive serial correlation leaves room for a power gain that arises from restricting the parameter space under the alternative hypothesis, compared to existing procedures that allow for two-sided alternatives. A Monte Carlo experiment shows that the proposed statistics have good size and power performance in very small samples like those typically used in applied work in panel data. An empirical example illustrates the usefulness of the proposed statistics.
Fil: Sosa Escudero, Walter. Universidad de San Andrés. Departamento de Economía; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina
description This article proposes new simple testing procedures for the joint null hypothesis of absence of persistent effects, in the form of random effects and first-order serial correlation in the error component model. The fact that the presence of random effects is clearly of a one-sided nature, together with the fact that in many empirical applications researchers worry about positive serial correlation leaves room for a power gain that arises from restricting the parameter space under the alternative hypothesis, compared to existing procedures that allow for two-sided alternatives. A Monte Carlo experiment shows that the proposed statistics have good size and power performance in very small samples like those typically used in applied work in panel data. An empirical example illustrates the usefulness of the proposed statistics.
publishDate 2013
dc.date.none.fl_str_mv 2013-06
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
http://purl.org/coar/resource_type/c_6501
info:ar-repo/semantics/articulo
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv http://hdl.handle.net/11336/24593
Sosa Escudero, Walter; Testing for persistence in the error component model: a one-sided approach; Taylor & Francis; Communications In Statistics-theory And Methods; 42; 14; 6-2013; 2601-2616
0361-0926
CONICET Digital
CONICET
url http://hdl.handle.net/11336/24593
identifier_str_mv Sosa Escudero, Walter; Testing for persistence in the error component model: a one-sided approach; Taylor & Francis; Communications In Statistics-theory And Methods; 42; 14; 6-2013; 2601-2616
0361-0926
CONICET Digital
CONICET
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/url/http://www.tandfonline.com/doi/abs/10.1080/03610926.2011.611606
info:eu-repo/semantics/altIdentifier/doi/10.1080/03610926.2011.611606
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
eu_rights_str_mv openAccess
rights_invalid_str_mv https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
dc.format.none.fl_str_mv application/pdf
application/pdf
dc.publisher.none.fl_str_mv Taylor & Francis
publisher.none.fl_str_mv Taylor & Francis
dc.source.none.fl_str_mv reponame:CONICET Digital (CONICET)
instname:Consejo Nacional de Investigaciones Científicas y Técnicas
reponame_str CONICET Digital (CONICET)
collection CONICET Digital (CONICET)
instname_str Consejo Nacional de Investigaciones Científicas y Técnicas
repository.name.fl_str_mv CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicas
repository.mail.fl_str_mv dasensio@conicet.gov.ar; lcarlino@conicet.gov.ar
_version_ 1842270083012886528
score 12.885934