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A Monte Carlo Analysis of the VAR-Based Indirect Inference Estimation of DSGE Models

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  • David Dubois

Abstract

In 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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  • David Dubois, 2011. "A Monte Carlo Analysis of the VAR-Based Indirect Inference Estimation of DSGE Models," CREPP Working Papers 1104, Centre de Recherche en Economie Publique et de la Population (CREPP) (Research Center on Public and Population Economics) HEC-Management School, University of Liège.
    • Handle: RePEc:rpp:wpaper:1104
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    File URL: http://www2.ulg.ac.be/crepp/papers/crepp-wp201104.pdf
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    References listed on IDEAS

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    1. 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.
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