The copula information criterion

Abstract

When estimating parametric copula models by the semiparametric pseudo maximum likelihood procedure (MPLE), many practitioners have used the Akaike Information Criterion (AIC) for model selection in spite of the fact that the AIC formula has no theoretical basis in this setting. We adapt the arguments leading to the original AIC formula in the fully parametric case to the MPLE. This gives a significantly different formula than the AIC, which we name the Copula Information Criterion (CIC). However, we also show that such a model-selection procedure cannot exist for a large class of commonly used copula models.

We note that this research report is a revision of a research report dated June 2008. The current version encorporates corrections of the proof of Theorem 1. The conclusions of the previous manuscript are still valid, however.