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Title: Identification Versus Misspecification in New Keynesian Monetary Policy Models

Author(s): Stefan Laséen, Jesper Lindé and Marco Ratto

Publication Date: January 2019

Keyword(s): Bayesian estimation, Closed economy, DSGE model, Maximum Likelihood Estimation, Monte-Carlo methods and Open economy

Programme Area(s): Monetary Economics and Fluctuations

Abstract: In this paper, we study identification and misspecification problems in standard closed and open-economy empirical New-Keynesian DSGE models used in monetary policy analysis. We find that problems with model misspecification still appear to be a first-order issue in monetary DSGE models, and argue that it is problems with model misspecification that may benefit the most from moving from a classical to a Bayesian framework. We also argue that lack of identification should neither be ignored nor be assumed to affect all DSGE models. Fortunately, identification problems can be readily assessed on a case-by-case basis, by applying recently developed pre-tests of identification.

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Bibliographic Reference

Laséen, S, Lindé, J and Ratto, M. 2019. 'Identification Versus Misspecification in New Keynesian Monetary Policy Models'. London, Centre for Economic Policy Research. https://cepr.org/active/publications/discussion_papers/dp.php?dpno=13492