Bayesian Estimation of DSGE Models: Is the Workhorse Model Identified?
AbstractKoop, Pesaran and Smith (2011) suggest a simple diagnostic indicator for the Bayesian estimation of the parameters of a DSGE model. They show that, if a parameter is well identified, the precision of the posterior should improve as the (artificial) data size T increases, and the indicator checks the speed at which precision improves. It does not require any additional programming; a researcher just needs to generate artificial data and estimate the model with different T. Applying this to Smets and Wouters'(2007) medium size US model, we find that while exogenous shock processes are well identified, most of the parameters in the structural equations are not.
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Bibliographic InfoPaper provided by Koc University-TUSIAD Economic Research Forum in its series Koç University-TUSIAD Economic Research Forum Working Papers with number 1205.
Length: 24 pages
Date of creation: Feb 2012
Date of revision:
Bayesian Estimation; Dynamic stochastic general equilibrium models; Identification.;
Other versions of this item:
- Evren Caglar & Jagjit S. Chadha & Katsuyuki Shibayama, 2011. "Bayesian Estimation of DSGE models: Is the Workhorse Model Identified?," Studies in Economics 1125, Department of Economics, University of Kent.
- C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
- C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
- E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles
This paper has been announced in the following NEP Reports:
- NEP-ALL-2012-02-20 (All new papers)
- NEP-CBA-2012-02-20 (Central Banking)
- NEP-DGE-2012-02-20 (Dynamic General Equilibrium)
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