A CORRECTED AKAIKE INFORMATION CRITERION FOR VECTOR AUTOREGRESSIVE MODEL SELECTION

Abstract

Abstract. We develop a small‐sample criterion (AIC C ) for the selection of the order of vector autoregressive models. AIC C is an approximately unbiased estimator of the expected Kullback‐Leibler information. Furthermore, AIC C provides better model order choices than the Akaike information criterion in small samples.