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Estimating Nonlinear DSGE Models by the Simulated Method of Moments

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  • Francisco J. Ruge-Murcia

    ()
    (Department of Economics, University of Montréal; The Rimini Centre for Economic Analysis (RCEA))

Abstract

This paper studies the application of the simulated method of moments (SMM) for 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 curvature. Results show that SMM is computationally efficient and delivers accurate estimates, even when the simulated series are relatively short. However, asymptotic standard errors tend to overstate the actual variability of the estimates and, consequently, statistical inference is conservative. A simple strategy to incorporate priors in a method of moments context is proposed. An empirical application to the macroeconomic effects of rare events indicates that negatively skewed productivity shocks induce agents to accumulate additional capital and can endogenously generate asymmetric business cycles.

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Bibliographic Info

Paper provided by The Rimini Centre for Economic Analysis in its series Working Paper Series with number 49_10.

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Date of creation: Jan 2010
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Handle: RePEc:rim:rimwps:49_10

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Keywords: Monte-Carlo analysis; priors; perturbation methods; rare events; skewness;

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  1. Lombardo, Giovanni, 2010. "On approximating DSGE models by series expansions," Working Paper Series 1264, European Central Bank.
  2. Fernández-Villaverde, Jesús & Rubio-Ramirez, Juan Francisco, 2006. "Estimating Macroeconomic Models: A Likelihood Approach," CEPR Discussion Papers 5513, C.E.P.R. Discussion Papers.
  3. Kim, Jinill & Ruge-Murcia, Francisco J., 2009. "How much inflation is necessary to grease the wheels?," Journal of Monetary Economics, Elsevier, vol. 56(3), pages 365-377, April.
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Cited by:
  1. KIM, Jinill & RUGE-MURCIA, Francisco J., 2009. "Monetary Policy When Wages Are Downwardly Rigid : Friedman Meets Tobin," Cahiers de recherche 15-2009, Centre interuniversitaire de recherche en économie quantitative, CIREQ.
  2. Caterina Mendicino, 2012. "Collateral Requirements: Macroeconomic Fluctuations and Macro-Prudential Policy," Working Papers w201211, Banco de Portugal, Economics and Research Department.
  3. Benjamin Born & Johannes Pfeifer, 2011. "Policy Risk and the Business Cycle," Bonn Econ Discussion Papers bgse06_2011, University of Bonn, Germany.
  4. Michael Creel & Dennis Kristensen, 2011. "Indirect likelihood inference," UFAE and IAE Working Papers 874.11, Unitat de Fonaments de l'Anàlisi Econòmica (UAB) and Institut d'Anàlisi Econòmica (CSIC).
  5. Hong Lan & Alexander Meyer-Gohde, 2013. "Pruning in Perturbation DSGE Models - Guidance from Nonlinear Moving Average Approximations," SFB 649 Discussion Papers SFB649DP2013-024, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.

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