Estimating nonlinear DSGE models with moments based methods
AbstractThis article suggests the new approach to an approximation of nonlinear DSGE models moments. This approach is fast and accurate enough to use it for an estimation of nonlinear DSGE models. The small financial DSGE model is repeatedly estimated by several modifications of suggested approach. Approximations of moments are close to the results of large sample Monte Carlo estimation. Quality of parameters estimation with suggested approach is close to the Central Difference Kalman Filter (the CDKF) based. At the same time suggested approach is much faster.
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Bibliographic InfoPaper provided by CEPREMAP in its series Dynare Working Papers with number 32.
Length: 18 pages
Date of creation: Jan 2014
Date of revision:
DSGE; DSGE-VAR; GMM; nonlinear estimation;
Other versions of this item:
- Sergei Ivashchenko, 2013. "Estimating nonlinear DSGE models with moments based methods," EUSP Deparment of Economics Working Paper Series Ec-03/13, European University at St. Petersburg, Department of Economics.
- C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
- C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
- 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-2014-02-02 (All new papers)
- NEP-DGE-2014-02-02 (Dynamic General Equilibrium)
- NEP-MAC-2014-02-02 (Macroeconomics)
- NEP-ORE-2014-02-02 (Operations Research)
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- Martin Møller Andreasen, 2008. "Non-linear DSGE Models, The Central Difference Kalman Filter, and The Mean Shifted Particle Filter," CREATES Research Papers 2008-33, School of Economics and Management, University of Aarhus.
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Journal of Economic Dynamics and Control,
Elsevier, vol. 25(6-7), pages 979-999, June.
- Collard, Fabrice & Juillard, Michel, 1999. "Accuracy of stochastic perturbuation methods: the case of asset pricing models," CEPREMAP Working Papers (Couverture Orange) 9922, CEPREMAP.
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