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DSGE pileups
Affiliation:1. International Monetary Fund (IMF), Washington, DC, USA;2. University of Paris Ouest, Nanterre-La Défense, Nanterre, France
Abstract:The sampling distribution of estimators for DSGE structural parameters tends to be non-normal and/or pile up on the boundary of the theoretically admissible parameter space. This calls into question both the reliability of asymptotic approximations and the presumption of correct specification. This paper seeks to develop a conceptual framework for understanding how these phenomena arise, and to provide pragmatic methods for dealing with them in practice. The results are presented in three examples and a medium scale DSGE model.
Keywords:Global identification  Maximum likelihood estimation  Posterior probability
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