Effects of skewness and kurtosis on model selection criteria

dc.citation.epage22en_US
dc.citation.issueNumber1en_US
dc.citation.spage17en_US
dc.citation.volumeNumber59en_US
dc.contributor.authorBaşçı, S.en_US
dc.contributor.authorZaman, A.en_US
dc.date.accessioned2015-07-28T11:56:19Z
dc.date.available2015-07-28T11:56:19Z
dc.date.issued1998en_US
dc.departmentDepartment of Economicsen_US
dc.description.abstractWe consider the behavior of model selection criteria in AR models where the error terms are not normal by varying skewness and kurtosis. The probability of estimating the true lag order for varying degrees of freedom (k) is the interest. For both small and large samples skewness does not effect the performance of criteria under consideration. On the other hand, kurtosis does effect some of the criteria considerably. In large samples and for large values of k the usual asymptotic theory results for normal models are confirmed. Moreover, we showed that for small sample sizes performance of some newly introduced criteria which were not considered in Monte Carlo studies before are better. (C) 1998 Elsevier Science S.A.en_US
dc.description.provenanceMade available in DSpace on 2015-07-28T11:56:19Z (GMT). No. of bitstreams: 1 10.1016-S0165-1765(98)00036-6.pdf: 2111273 bytes, checksum: 30fc0c73bccb200b457afd6c33f78134 (MD5)en
dc.identifier.doi10.1016/S0165-1765(98)00036-6en_US
dc.identifier.eissn1873-7374
dc.identifier.issn0165-1765
dc.identifier.urihttp://hdl.handle.net/11693/10924
dc.language.isoEnglishen_US
dc.publisherElsevier BVen_US
dc.relation.isversionofhttp://dx.doi.org/10.1016/S0165-1765(98)00036-6en_US
dc.source.titleEconomics Lettersen_US
dc.subjectModel selection criteriaen_US
dc.subjectAR lag order determinationen_US
dc.subjectRobustnessen_US
dc.titleEffects of skewness and kurtosis on model selection criteriaen_US
dc.typeArticleen_US

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