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Federal Reserve Bank of Richmond
Working Paper
A Composite Likelihood Approach for Dynamic Structural Models
Fabio Canova
Christian Matthes
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. In each case we consider, we provide an example to illustrate how the approach works and its properties in practice.


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Fabio Canova & Christian Matthes, A Composite Likelihood Approach for Dynamic Structural Models, Federal Reserve Bank of Richmond, Working Paper 18-12, 23 Jul 2018.
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Keywords: dynamic structural models; composite likelihood; identification; singularity; large scale models; panel data
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