A Composite Likelihood Approach for Dynamic Structural Models

41 Pages Posted: 20 Aug 2018 Last revised: 21 Feb 2019

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: 2018-07-23

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.

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

JEL Classification: C10, E27, E32

Suggested Citation

Canova, Fabio and Matthes, Christian, A Composite Likelihood Approach for Dynamic Structural Models (2018-07-23). FRB Richmond Working Paper No. 18-12. Available at SSRN: https://ssrn.com/abstract=3234198

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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