Fabio Canova (BI Norwegian Business School): Dealing with misspecification in macroeconometrics
Co-author: Christian Matthes, Federal Reserve Bank of Richmond
We describe how to use the composite likelihood to ameliorate estimation, computational and inferential problems in misspecied dynamic stochastic general equilibrium models. We show how to perform quasi-Bayesian inference, how to construct density forecasts and scenario analyses, and discuss differences with finite mixture models and Bayesian model averaging. We present situations where the methodology has the potential to reduce model misspecification and provide an example to illustrate its properties in practice.
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