A small-sample criterion based on Kullback's symmetric divergence for vector autoregressive modeling

In this note, we propose a small-sample criterion KICc for selecting vector autoregressive models. KICc is an approximately unbiased estimator of the expected Kullback's symmetric divergence. A simulation study shows that KICc provides better model order choices than the KIC criterion in small samples.