EFFECTS OF SKEWNESS AND KURTOSIS ON MODEL SELECTION CRITERIA

We consider the behavior of model selection criteria in AR models wher e the error terms are not normal by varying skewness and kurtosis. The probability of estimating the true lag order for varying degrees of f reedom (k) is the interest. For both small and large samples skewness does not effect the performance of criteria under consideration. On th e 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 whic h were not considered in Monte Carlo studies before are better. (C) 19 98 Elsevier Science S.A.