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dc.contributor.authorΧατζηνικολάου, Δημήτριοςel
dc.contributor.authorΣταυρακούδης, Αθανάσιοςel
dc.date.accessioned2015-11-24T17:04:43Z-
dc.date.available2015-11-24T17:04:43Z-
dc.identifier.issn0377-7332-
dc.identifier.urihttps://olympias.lib.uoi.gr/jspui/handle/123456789/11217-
dc.rightsDefault Licence-
dc.subjectsizeen
dc.subjectpoweren
dc.subjectsimulationen
dc.subjectreseten
dc.subjectdiagnostic testsen
dc.subjectspecification error testsen
dc.subjectsensitivityen
dc.titleEmpirical size and power of some diagnostic tests applied to a distributed lag modelen
heal.typejournalArticle-
heal.type.enJournal articleen
heal.type.elΆρθρο Περιοδικούel
heal.identifier.primaryDOI 10.1007/s00181-005-0039-0-
heal.identifier.secondary<Go to ISI>://000239869000006-
heal.identifier.secondaryhttp://www.springerlink.com/content/mw742h7237057635/fulltext.pdf-
heal.languageen-
heal.accesscampus-
heal.recordProviderΠανεπιστήμιο Ιωαννίνων. Σχολή Οικονομικών και Κοινωνικών Επιστημών. Τμήμα Οικονομικών Επιστημώνel
heal.publicationDate2006-
heal.abstractWe produce Monte Carlo evidence on the size and power of the RESET, a heteroscedasticity test, and a test for autocorrelation applied to realistic distributed-lag models. We find that the autocorrelation test has the correct size and high power to detect not only autocorrelation (given a correct model), but also the erroneous omission of several lags of an explanatory variable, whereas the RESET and heteroscedasticity tests are oversized in the presence of positive disturbance autocorrelation, especially when the regressors are also positively autocorrelated, and have no power to detect such misspecification errors. In large samples, size distortion may be avoided by using autocorrelation-robust methods.en
heal.publisherSpringer-Verlagen
heal.journalNameEmpirical Economicsen
heal.journalTypepeer reviewed-
heal.fullTextAvailabilityTRUE-
Appears in Collections:Άρθρα σε επιστημονικά περιοδικά ( Ανοικτά) - ΟΕ

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