Bayesian estimation of DSGE models: identification using a diagnostic indicator

Chadha, Jagjit S. and Shibayama, Katsuyuki (2018) Bayesian estimation of DSGE models: identification using a diagnostic indicator. CFM Discussion Paper Series (CFM-DP2018-25). Centre For Macroeconomics, London School of Economics and Political Science, London, UK.

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Abstract

Koop, Pesaran and Smith (2013) suggest a simple diagnostic indicator for the Bayesian estimation of the parameters of a DSGE model. They show that, if a parameter is well identiÖed, the precision of the posterior should improve as the (artiÖcial) data size T increases, and the indicator checks the speed at which precision improves. As it does not require any additional programming, a researcher just needs to generate artiÖcial data and estimate the model with increasing sample size, T. We apply this indicator to the benchmark Smets and Woutersí(2007) DSGE model of the US economy, and suggest how to implement this indicator on DSGE models

Item Type:	Monograph (Discussion Paper)
Official URL:	http://www.centreformacroeconomics.ac.uk/Home.aspx
Additional Information:	© 2018 Centre for Macroeconomics
Divisions:	Centre for Macroeconomics
Subjects:	H Social Sciences > HB Economic Theory
JEL classification:	C - Mathematical and Quantitative Methods > C5 - Econometric Modeling > C51 - Model Construction and Estimation C - Mathematical and Quantitative Methods > C5 - Econometric Modeling > C52 - Model Evaluation and Selection E - Macroeconomics and Monetary Economics > E3 - Prices, Business Fluctuations, and Cycles > E32 - Business Fluctuations; Cycles
Date Deposited:	05 Oct 2018 15:49
Last Modified:	11 Dec 2024 19:28
URI:	http://eprints.lse.ac.uk/id/eprint/90383

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