A Monte Carlo Analysis of the VAR-Based Indirect Inference Estimation of DSGE Models
AbstractIn this paper we study estimation of DSGE models. More specifically, in the indirect inference framework, we analyze how critical is the choice of the reduced form model for estimation purposes. As it turns out, simple VAR parameters performs better than commonly used impulse response functions. This can be attributed to the fact that IRF worsen identification issues for models that are already plagued by that phenomenon.
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Bibliographic InfoPaper provided by Centre de Recherche en Economie Publique et de la Population (CREPP) (Research Center on Public and Population Economics) HEC-Management School, University of Liège in its series CREPP Working Papers with number 1104.
Date of creation: 2011
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This paper has been announced in the following NEP Reports:
- NEP-ALL-2011-04-23 (All new papers)
- NEP-DGE-2011-04-23 (Dynamic General Equilibrium)
- NEP-ECM-2011-04-23 (Econometrics)
- NEP-ETS-2011-04-23 (Econometric Time Series)
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- Ruge-Murcia, Francisco J., 2002.
"Methods to Estimate Dynamic Stochastic General Equilibrium Models,"
University of California at San Diego, Economics Working Paper Series
qt4fc8x822, Department of Economics, UC San Diego.
- Ruge-Murcia, Francisco J., 2007. "Methods to estimate dynamic stochastic general equilibrium models," Journal of Economic Dynamics and Control, Elsevier, vol. 31(8), pages 2599-2636, August.
- Francisco J. Ruge-Murcia, 2004. "Methods to Estimate Dynamic Stochastic General Equilibrium Models," 2004 Meeting Papers 83, Society for Economic Dynamics.
- RUGE-MURCIA, Francisco J., 2003. "Methods to Estimate Dynamic Stochastic General Equilibrium Models," Cahiers de recherche 2003-23, Universite de Montreal, Departement de sciences economiques.
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