A composite likelihood approach for dynamic structural models

Abstract

We describe how to use the composite likelihood to ameliorate estimation, computational, and inferential problems in dynamic stochastic general equilibrium models. We present a number of situations where the methodology has the potential to resolve well-known problems and formally justifies existing practices. In each case we consider, we provide an example to illustrate how the approach works and its properties in practice.