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Title: A composite likelihood approach for dynamic structural models

Author(s): Fabio Canova and Christian Matthes

Publication Date: October 2018

Keyword(s): composite likelihood, dynamic structural models, identification, large scale models, panel data and singularity

Programme Area(s): International Macroeconomics and Finance and Monetary Economics and Fluctuations

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.

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Bibliographic Reference

Canova, F and Matthes, C. 2018. 'A composite likelihood approach for dynamic structural models'. London, Centre for Economic Policy Research. https://cepr.org/active/publications/discussion_papers/dp.php?dpno=13245