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dc.contributor.authorMartins, Luis Filipeen_US
dc.contributor.authorPerron, Pierreen_US
dc.date.accessioned2018-01-19T17:00:32Z
dc.date.available2018-01-19T17:00:32Z
dc.date.issued2016-09-01
dc.identifierhttp://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000380913600004&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=6e74115fe3da270499c3d65c9b17d654
dc.identifier.citationLuis Filipe Martins, Pierre Perron. 2016. "Improved Tests for Forecast Comparisons in the Presence of Instabilities." JOURNAL OF TIME SERIES ANALYSIS, v. 37, Issue 5, pp. 650-659 (10).
dc.identifier.issn0143-9782
dc.identifier.issn1467-9892
dc.identifier.urihttps://hdl.handle.net/2144/26213
dc.description.abstractOf interest is comparing the out-of-sample forecasting performance of two competing models in the presence of possible instabilities. To that effect, we suggest using simple structural change tests, sup-Wald and UDmax for changes in the mean of the loss differences. It is shown that Giacomini and Rossi (2010) tests have undesirable power properties, power that can be low and non-increasing as the alternative becomes further from the null hypothesis. On the contrary, our statistics are shown to have higher monotonic power, especially the UDmax version. We use their empirical examples to show the practical relevance of the issues raised.en_US
dc.format.extentp. 650-659 (10)en_US
dc.languageEnglish
dc.language.isoen_US
dc.publisherWILEYen_US
dc.relation.ispartofJOURNAL OF TIME SERIES ANALYSIS
dc.rightsCopyright © 1999 - 2018 John Wiley & Sons, Inc. All Rights Reserveden_US
dc.subjectMathematicsen_US
dc.subjectNon‐monotonic poweren_US
dc.subjectEconometricsen_US
dc.subjectScience & technologyen_US
dc.subjectPhysical sciencesen_US
dc.subjectMathematics, interdisciplinary applicationsen_US
dc.subjectStatistics & probabilityen_US
dc.subjectStructural changeen_US
dc.subjectLong-run varianceen_US
dc.subjectPredictive abilityen_US
dc.subjectForecastsen_US
dc.titleImproved tests for forecast comparisons in the presence of instabilitiesen_US
dc.typeArticleen_US
dc.identifier.doi10.1111/jtsa.12179
pubs.elements-sourceweb-of-scienceen_US
pubs.notesEmbargo: Not knownen_US
pubs.organisational-groupBoston Universityen_US
pubs.organisational-groupBoston University, College of Arts & Sciencesen_US
pubs.organisational-groupBoston University, College of Arts & Sciences, Department of Economicsen_US
pubs.publication-statusPublisheden_US


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