Estimating nonlinear DSGE models by the simulated method of moments: With an application to business cycles

Francisco Ruge-Murcia

Journal of Economic Dynamics and Control, 2012, vol. 36, issue 6, 914-938

Abstract: This paper studies the application of the simulated method of moments (SMM) to the estimation of nonlinear dynamic stochastic general equilibrium (DSGE) models. Monte-Carlo analysis is employed to examine the small-sample properties of SMM in specifications with different curvatures and departures from certainty equivalence. Results show that SMM is computationally efficient and delivers accurate estimates, even when the simulated series are relatively short. However, the small-sample distribution of the estimates is not always well approximated by the asymptotic Normal distribution. An empirical application to the macroeconomic effects of skewed disturbances shows that negatively skewed productivity shocks induce agents to accumulate additional capital and can generate asymmetric business cycles.

Keywords: Monte-Carlo analysis; Method of moments; Perturbation methods; Skewness; Asymmetric shocks (search for similar items in EconPapers)
JEL-codes: C15 E2 (search for similar items in EconPapers)
Date: 2012
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Citations: View citations in EconPapers (91)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:dyncon:v:36:y:2012:i:6:p:914-938

DOI: 10.1016/j.jedc.2012.01.008

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