Forming Priors for DSGE Models (and How It Affects the Assessment of Nominal Rigidities)
Marco Del Negro and Frank Schorfheide
Working Paper 2006-16
In Bayesian analysis of dynamic stochastic general equilibrium (DSGE) models, prior distributions for some of the taste-and-technology parameters can be obtained from microeconometric or presample evidence, but it is difficult to elicit priors for the parameters that govern the law of motion of unobservable exogenous processes. Moreover, since it is challenging to formulate beliefs about the correlation of parameters, most researchers assume that all model parameters are independent of each other. We provide a simple method of constructing prior distributions for a subset of DSGE model parameters from beliefs about the moments of the endogenous variables. We use our approach to investigate the importance of nominal rigidities and show how the specification of prior distributions affects our assessment of the relative importance of different frictions.
JEL classification: C32, E3
Key words: Bayesian analysis, DSGE models, model comparisons, prior elicitation, nominal rigidities
The authors thank Simon Potter, Frank Smets, colleagues at the St. Louis Fed and the Federal Reserve Board of Governors, and participants in the Bank of Finland’s conference, “Practical Issues in DSGE Modeling at Central Banks,” and the seventh Euro Area Business Cycle Network workshop, “Estimation and Empirical Validation of Structural Models for Business Cycle Analysis,” for helpful comments and suggestions. Schorfheide gratefully acknowledges financial support from the Alfred P. Sloan Foundation and the National Science Foundation. The views expressed here are the authors’ and not necessarily those of the Federal Reserve Bank of Atlanta or the Federal Reserve System. Any remaining errors are the authors’ responsibility.
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