On Identification of Bayesian DSGE Models
AbstractIn recent years there has been increasing concern about the identification of parameters in dynamic stochastic general equilibrium (DSGE) models. Given the structure of DSGE models it may be difficult to determine whether a parameter is identified. For the researcher using Bayesian methods, a lack of identification may not be evident since the posterior of a parameter of interest may differ from its prior even if the parameter is unidentified. We show that this can be the case even if the priors assumed on the structural parameters are independent. We suggest two Bayesian identification indicators that do not suffer from this difficulty and are relatively easy to compute. The first applies to DSGE models where the parameters can be partitioned into those that are known to be identified and the rest where it is not known whether they are identified. In such cases the marginal posterior of an unidentified parameter will equal the posterior expectation of the prior for that parameter conditional on the identified parameters. The second indicator is more generally applicable and considers the rate at which the posterior precision gets updated as the sample size (T) is increased. For identified parameters the posterior precision rises with T, whilst for an unidentified parameter its posterior precision may be updated but its rate of update will be slower than T. This result assumes that the identified parameters are -consistent, but similar differential rates of updates for identified and unidentified parameters can be established in the case of super consistent estimators. These results are illustrated by means of simple DSGE models.
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Bibliographic InfoPaper provided by Institute for the Study of Labor (IZA) in its series IZA Discussion Papers with number 5638.
Length: 39 pages
Date of creation: Apr 2011
Date of revision:
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Other versions of this item:
- Gary Koop & M. Hashem Pesaran & Ron Smith, 2011. "On Identification of Bayesian DSGE Models," Working Papers 1108, University of Strathclyde Business School, Department of Economics.
- Koop, Gary & Pesaran, M. Hashem & Smith, Ron P., 2011. "On Identification of Bayesian DSGE Models," SIRE Discussion Papers 2011-18, Scottish Institute for Research in Economics (SIRE).
- Gary Koop & M. Hashem Pesaran & Ron P. Smith, 2011. "On Identification of Bayesian DSGE Models," CESifo Working Paper Series 3423, CESifo Group Munich.
- Koop, G. & Pesaran, M.H. & Smith, R., 2011. "On Identification of Bayesian DSGE Models," Cambridge Working Papers in Economics 1131, Faculty of Economics, University of Cambridge.
- C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
- C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
- E17 - Macroeconomics and Monetary Economics - - General Aggregative Models - - - Forecasting and Simulation: Models and Applications
This paper has been announced in the following NEP Reports:
- NEP-ALL-2011-04-23 (All new papers)
- NEP-CBA-2011-04-23 (Central Banking)
- NEP-DGE-2011-04-23 (Dynamic General Equilibrium)
- NEP-ECM-2011-04-23 (Econometrics)
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