dc.contributor.author Başçı, S. en_US dc.contributor.author Zaman, A. en_US dc.date.accessioned 2015-07-28T11:56:19Z dc.date.available 2015-07-28T11:56:19Z dc.date.issued 1998 en_US dc.identifier.issn 0165-1765 dc.identifier.uri http://hdl.handle.net/11693/10924 dc.description.abstract We 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.language.iso English en_US dc.source.title Economics Letters en_US dc.relation.isversionof http://dx.doi.org/10.1016/S0165-1765(98)00036-6 en_US dc.subject Model selection criteria en_US dc.subject AR lag order determination en_US dc.subject Robustness en_US dc.title Effects of skewness and kurtosis on model selection criteria en_US dc.type Article en_US dc.department Department of Economics en_US dc.citation.spage 17 en_US dc.citation.epage 22 en_US dc.citation.volumeNumber 59 en_US dc.citation.issueNumber 1 en_US dc.identifier.doi 10.1016/S0165-1765(98)00036-6 en_US dc.publisher Elsevier BV en_US dc.identifier.eissn 1873-7374
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