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 Department of Economics, University of Kent in its series Studies in Economics with number 1125.
Date of creation: Nov 2011
Date of revision:
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Postal: Department of Economics, University of Kent at Canterbury, Canterbury, Kent, CT2 7NP
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Other versions of this item:
- Evren Caglar & Jagjit S. Chadha & Katsuyuki Shibayama, 2012. "Bayesian Estimation of DSGE Models: Is the Workhorse Model Identified?," KoÃ§ University-TUSIAD Economic Research Forum Working Papers 1205, Koc University-TUSIAD Economic Research Forum.
- 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-2012-01-03 (All new papers)
- NEP-CBA-2012-01-03 (Central Banking)
- NEP-DGE-2012-01-03 (Dynamic General Equilibrium)
- NEP-ECM-2012-01-03 (Econometrics)
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