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Methods to Estimate Dynamic Stochastic General Equilibrium Models

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Author Info
Francisco Ruge-Murcia (University of Montreal)

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Abstract

This paper employs the one-sector Real Business Cycle model as a testing ground for four different procedures to estimate Dynamic Stochastic General Equilibrium (DSGE) models. The procedures are: 1) Maximum Likelihood (with and without measurement errors and incorporating priors), 2) Generalized Method of Moments, 3) Simulated Method of Moments, and 4) the Extended Method of Simulated Moments proposed by Smith (1993). Monte Carlo analysis shows that although all procedures deliver reasonably good estimates, there are substantial differences in statistical and computational efficiency in the small samples currently available to estimate DSGE models. The implications of the singularity of DSGE models for each estimation procedure are fully discussed.

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Paper provided by Department of Economics, UC San Diego in its series University of California at San Diego, Economics Working Paper Series with number 2002-18.

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Date of creation: 01 Oct 2002
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Handle: RePEc:cdl:ucsdec:2002-18

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Keywords: DSGE models; estimation methods; Monte Carlo analysis; singularity;

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