A composite likelihood approach for dynamic structural models

Fabio Canova and Christian Matthes

No 13245, CEPR Discussion Papers from Centre for Economic Policy Research

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: Dynamic structural models; Composite likelihood; Identification; Singularity; Large scale models; Panel data (search for similar items in EconPapers)
JEL-codes: C10 E27 E32 (search for similar items in EconPapers)
Date: 2018-10
New Economics Papers: this item is included in nep-mac
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Citations: View citations in EconPapers (2)

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Related works:
Journal Article: A Composite Likelihood Approach for Dynamic Structural Models (2021)
Working Paper: A composite likelihood approach for dynamic structural models (2018)
Working Paper: A Composite Likelihood Approach for Dynamic Structural Models (2018)
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