Composite indirect inference with application to corporate risks

It is frequent to deal with parametric models that are difficult to analyze, due to the large number of data and/or parameters, complicated nonlinearities, or unobservable variables. The aim is to explain how to analyze such models by means of a set of simplified models, called instrumental models, and how to combine these instrumental models in an optimal way. In this respect a bridge between the econometric literature on indirect inference and the statistical literature on composite likelihood is provided. The composite indirect inference principle is illustrated by an application to the analysis of corporate risks.