A Power Booster Factor for Out-of-Sample Tests of Predictability

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In this paper we introduce a “power booster factor” for out-of-sample tests of predictability. The relevant econometric environment is one in which the econometrician wants to compare the population Mean Squared Prediction Errors (MSPE) of two models: one big nesting model, and another smaller neste...

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Detalles Bibliográficos
Autor: Pincheira Brown, Pablo
Formato: artículo
Fecha de Publicación:2022
Institución:Pontificia Universidad Católica del Perú
Repositorio:PUCP-Institucional
Lenguaje:inglés
OAI Identifier:oai:repositorio.pucp.edu.pe:20.500.14657/186811
Enlace del recurso:https://revistas.pucp.edu.pe/index.php/economia/article/view/25655/24154
https://doi.org/10.18800/economia.202201.006
Nivel de acceso:acceso abierto
Materia:Time-series
Inflation
Exchange rates
Random walk
Out-of-sample
https://purl.org/pe-repo/ocde/ford#5.02.01
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spelling Pincheira Brown, Pablo2022-10-03T16:47:05Z2022-10-03T21:18:36Z2022-10-03T16:47:05Z2022-10-03T21:18:36Z2022-08-01https://revistas.pucp.edu.pe/index.php/economia/article/view/25655/24154https://doi.org/10.18800/economia.202201.006In this paper we introduce a “power booster factor” for out-of-sample tests of predictability. The relevant econometric environment is one in which the econometrician wants to compare the population Mean Squared Prediction Errors (MSPE) of two models: one big nesting model, and another smaller nested model. Although our factor can be used to improve finite sample properties of several out-of-sample tests of predictability, in this paper we focus on the widely used test developed by Clark and West (2006, 2007). Our new test multiplies the Clark and West t-statistic by a factor that should be close to one under the null hypothesis that the short nested model is the true model, but that should be greater than one under the alternative hypothesis that the big nesting model is more adequate. We use Monte Carlo simulations to explore the size and power of our approach. Our simulations reveal that the new test is well sized and powerful. In particular, it tends to be less undersized and more powerful than the test by Clark and West (2006, 2007). Although most of the gains in power are associated to size improvements, we also obtain gains in size-adjusted-power. Finally we illustrate the use of our approach when evaluating the ability that an international core inflation factor has to predict core inflation in a sample of 30 OECD economies. With our “power booster factor” more rejections of the null hypothesis are obtained, indicating a strong influence of global inflation in a selected group of these OECD countries.application/pdfengPontificia Universidad Católica del PerúPEurn:issn:2304-4306urn:issn:0254-4415info:eu-repo/semantics/openAccesshttp://creativecommons.org/licenses/by/4.0Economía; Volume 45 Issue 89 (2022): Recent Developments in Inflation Dynamicsreponame:PUCP-Institucionalinstname:Pontificia Universidad Católica del Perúinstacron:PUCPTime-seriesInflationExchange ratesRandom walkOut-of-samplehttps://purl.org/pe-repo/ocde/ford#5.02.01A Power Booster Factor for Out-of-Sample Tests of Predictabilityinfo:eu-repo/semantics/articleArtículo20.500.14657/186811oai:repositorio.pucp.edu.pe:20.500.14657/1868112025-03-21 15:33:14.095http://creativecommons.org/licenses/by/4.0info:eu-repo/semantics/openAccessmetadata.onlyhttps://repositorio.pucp.edu.peRepositorio Institucional de la PUCPrepositorio@pucp.pe
dc.title.en_US.fl_str_mv A Power Booster Factor for Out-of-Sample Tests of Predictability
title A Power Booster Factor for Out-of-Sample Tests of Predictability
spellingShingle A Power Booster Factor for Out-of-Sample Tests of Predictability
Pincheira Brown, Pablo
Time-series
Inflation
Exchange rates
Random walk
Out-of-sample
https://purl.org/pe-repo/ocde/ford#5.02.01
title_short A Power Booster Factor for Out-of-Sample Tests of Predictability
title_full A Power Booster Factor for Out-of-Sample Tests of Predictability
title_fullStr A Power Booster Factor for Out-of-Sample Tests of Predictability
title_full_unstemmed A Power Booster Factor for Out-of-Sample Tests of Predictability
title_sort A Power Booster Factor for Out-of-Sample Tests of Predictability
author Pincheira Brown, Pablo
author_facet Pincheira Brown, Pablo
author_role author
dc.contributor.author.fl_str_mv Pincheira Brown, Pablo
dc.subject.en_US.fl_str_mv Time-series
Inflation
Exchange rates
Random walk
Out-of-sample
topic Time-series
Inflation
Exchange rates
Random walk
Out-of-sample
https://purl.org/pe-repo/ocde/ford#5.02.01
dc.subject.ocde.none.fl_str_mv https://purl.org/pe-repo/ocde/ford#5.02.01
description In this paper we introduce a “power booster factor” for out-of-sample tests of predictability. The relevant econometric environment is one in which the econometrician wants to compare the population Mean Squared Prediction Errors (MSPE) of two models: one big nesting model, and another smaller nested model. Although our factor can be used to improve finite sample properties of several out-of-sample tests of predictability, in this paper we focus on the widely used test developed by Clark and West (2006, 2007). Our new test multiplies the Clark and West t-statistic by a factor that should be close to one under the null hypothesis that the short nested model is the true model, but that should be greater than one under the alternative hypothesis that the big nesting model is more adequate. We use Monte Carlo simulations to explore the size and power of our approach. Our simulations reveal that the new test is well sized and powerful. In particular, it tends to be less undersized and more powerful than the test by Clark and West (2006, 2007). Although most of the gains in power are associated to size improvements, we also obtain gains in size-adjusted-power. Finally we illustrate the use of our approach when evaluating the ability that an international core inflation factor has to predict core inflation in a sample of 30 OECD economies. With our “power booster factor” more rejections of the null hypothesis are obtained, indicating a strong influence of global inflation in a selected group of these OECD countries.
publishDate 2022
dc.date.accessioned.none.fl_str_mv 2022-10-03T16:47:05Z
2022-10-03T21:18:36Z
dc.date.available.none.fl_str_mv 2022-10-03T16:47:05Z
2022-10-03T21:18:36Z
dc.date.issued.fl_str_mv 2022-08-01
dc.type.none.fl_str_mv info:eu-repo/semantics/article
dc.type.other.none.fl_str_mv Artículo
format article
dc.identifier.uri.none.fl_str_mv https://revistas.pucp.edu.pe/index.php/economia/article/view/25655/24154
dc.identifier.doi.none.fl_str_mv https://doi.org/10.18800/economia.202201.006
url https://revistas.pucp.edu.pe/index.php/economia/article/view/25655/24154
https://doi.org/10.18800/economia.202201.006
dc.language.iso.none.fl_str_mv eng
language eng
dc.relation.ispartof.none.fl_str_mv urn:issn:2304-4306
urn:issn:0254-4415
dc.rights.es_ES.fl_str_mv info:eu-repo/semantics/openAccess
dc.rights.uri.*.fl_str_mv http://creativecommons.org/licenses/by/4.0
eu_rights_str_mv openAccess
rights_invalid_str_mv http://creativecommons.org/licenses/by/4.0
dc.format.none.fl_str_mv application/pdf
dc.publisher.es_ES.fl_str_mv Pontificia Universidad Católica del Perú
dc.publisher.country.none.fl_str_mv PE
dc.source.es_ES.fl_str_mv Economía; Volume 45 Issue 89 (2022): Recent Developments in Inflation Dynamics
dc.source.none.fl_str_mv reponame:PUCP-Institucional
instname:Pontificia Universidad Católica del Perú
instacron:PUCP
instname_str Pontificia Universidad Católica del Perú
instacron_str PUCP
institution PUCP
reponame_str PUCP-Institucional
collection PUCP-Institucional
repository.name.fl_str_mv Repositorio Institucional de la PUCP
repository.mail.fl_str_mv repositorio@pucp.pe
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