DP13245 A composite likelihood approach for dynamic structural models

Author(s): Fabio Canova, Christian Matthes
Publication Date: October 2018
Date Revised: October 2018
Keyword(s): composite likelihood, dynamic structural models, identification, large scale models, panel data, singularity
JEL(s): C10, E27, E32
Programme Areas: International Macroeconomics and Finance, Monetary Economics and Fluctuations
Link to this Page: cepr.org/active/publications/discussion_papers/dp.php?dpno=13245

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.