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Information Criteria for Impulse Response Function Matching Estimation of DSGE Models Author info | Abstract | Publisher info | Download info | Related research | Statistics Hall, Alastair
Inoue, Atsushi
Nason M, James
Rossi, Barbara
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registered author(s):
We propose a new Information Criterion for Impulse Response Function Matching estimators of the structural parameters of macroeconomic models. The main advantage of our procedure is that it allows the researcher to select the impulse responses that are most informative about the deep parameters, therefore reducing the bias and improving the efficiency of the estimates of the model's parameters. We show that our method substantially changes key parameter estimates of representative Dynamic Stochastic General Equilibrium models, thus reconciling their empirical results with the existing literature. Our criterion is general enough to apply to impulse responses estimated by VARs, local projections, as well as simulation methods.
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Paper provided by Duke University, Department of Economics in its series Working Papers with number
07-04.
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Length: 39 Pages
Date of creation: 2007Date of revision:
Handle: RePEc:duk:dukeec:07-04Contact details of provider: Postal: Department of Economics Duke University 213 Social Sciences Building Box 90097 Durham, NC 27708-0097 Phone: (919) 660-1800 Fax: (919) 684-8974 Web page: http://www.econ.duke.edu/
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Keywords: impulse responses ; matching ; information criteria ; DSGE models ; structural macroeconomic models ; estimation ; Other versions of this item:
Find related papers by JEL classification: C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions E47 - Macroeconomics and Monetary Economics - - Money and Interest Rates - - - Forecasting and Simulation C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation and Testing C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Other Model Applications
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