A Composite Likelihood Approach for Dynamic Structural Models

45 Pages Posted: 22 Oct 2018

See all articles by Fabio Canova

Fabio Canova

Bi norwegian business school

Christian Matthes

Federal Reserve Bank of Richmond

Multiple version iconThere are 2 versions of this paper

Date Written: October 2018

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.

Keywords: composite likelihood, dynamic structural models, identification, large scale models, panel data, singularity

JEL Classification: C10, E27, E32

Suggested Citation

Canova, Fabio and Matthes, Christian, A Composite Likelihood Approach for Dynamic Structural Models (October 2018). CEPR Discussion Paper No. DP13245. Available at SSRN: https://ssrn.com/abstract=3270921

Fabio Canova (Contact Author)

Bi norwegian business school ( email )

Nydalsveien 37
Oslo, 0484
Norway

Christian Matthes

Federal Reserve Bank of Richmond ( email )

P.O. Box 27622
Richmond, VA 23261
United States

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