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
- Institución
- Consejo Nacional de Investigaciones Científicas y Técnicas
- OAI Identificador
- oai:ri.conicet.gov.ar:11336/24593
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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 |
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1842270083012886528 |
score |
12.885934 |