A Composite Likelihood Approach for Dynamic Structural Models

Abstract We explain how to use the composite likelihood function ameliorate estimation, computational and inferential problems in dynamic stochastic general equilibrium models. combine information present different models or data sets estimate parameters common across provide intuition for why methodology works alternative interpretations of estimators we construct statistics employ. a number situations where has potential resolve well-known justification existing practices that pool estimates. In each case, an example illustrate approach its properties practice.