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Finite Sample Properties of the Efficient Method of Moments

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Author Info
Rómulo Chumacero (University of Chile)

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Abstract

Gallant and Tauchen (1996) describe an estimation technique, known as Efficient Method of Moments (EMM), that uses numerical methods to estimate parameters of a structural model. The technique uses as matching conditions (or moments, in the GMM jargon) the gradients of an auxiliary model that fits a subset of variables that may be simulated from the structural model.This paper presents three Monte Carlo experiments to assess the finite sample properties of EMM. The first one compares it with a fully efficient procedure (Maximum Likelihood) by estimating an invertible moving-average (MA) process. The second and third experiments compare the finite sample properties of the EMM estimators with those of GMM by using stochastic volatility models and consumption-based asset-pricing models. The experiments show that the gains in efficiency are impressive; however, given that both EMM and GMM share the same type of objective function, finite sample inference based on asymptotic theory continues to lead, in some cases, to "over rejections," even though they are not as significant as in GMM.

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Publisher Info
Article provided by Berkeley Electronic Press in its journal Studies in Nonlinear Dynamics & Econometrics.

Volume (Year): 2 (1997)
Issue (Month): 2 ()
Pages: 35-51
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Handle: RePEc:bep:sndecm:2:1997:2:35-51

Note: oai:bepress:snde-1028
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Related research
Keywords: Monte Carlo efficient method of moments maximum likelihood generalized method of

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References listed on IDEAS
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
  1. Breeden, Douglas T., 1979. "An intertemporal asset pricing model with stochastic consumption and investment opportunities," Journal of Financial Economics, Elsevier, vol. 7(3), pages 265-296, September. [Downloadable!] (restricted)
  2. Andrews, Donald W K, 1991. "Heteroskedasticity and Autocorrelation Consistent Covariance Matrix Estimation," Econometrica, Econometric Society, vol. 59(3), pages 817-58, May. [Downloadable!] (restricted)
    Other versions:
  3. Andrews, Donald W K & Monahan, J Christopher, 1992. "An Improved Heteroskedasticity and Autocorrelation Consistent Covariance Matrix Estimator," Econometrica, Econometric Society, vol. 60(4), pages 953-66, July. [Downloadable!] (restricted)
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  4. Bansal, Ravi & Gallant, A. Ronald & Hussey, Robert & Tauchen, George, 1995. "Nonparametric estimation of structural models for high-frequency currency market data," Journal of Econometrics, Elsevier, vol. 66(1-2), pages 251-287. [Downloadable!] (restricted)
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  1. Michael Creel, 2008. "Estimation of Dynamic Latent Variable Models Using Simulated Nonparametric Moments," UFAE and IAE Working Papers 725.08, Unitat de Fonaments de l'Anàlisi Econòmica (UAB) and Institut d'Anàlisi Econòmica (CSIC), revised 02 Jun 2008. [Downloadable!]
  2. Rómulo Chumacero, 2001. "Estimating ARMA Models Efficiently," Studies in Nonlinear Dynamics & Econometrics, Berkeley Electronic Press, vol. 5(2), pages 1074-1074. [Downloadable!] (restricted)
    Other versions:
  3. Monica Gentile & Roberto Renò, 2002. "Which Model for the Italian Interest Rates?," LEM Papers Series 2002/02, Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy. [Downloadable!]
  4. Helena Veiga, 2006. "A Two Factor Long Memory Stochastic Volatility Model," Statistics and Econometrics Working Papers ws061303, Universidad Carlos III, Departamento de Estadística y Econometría. [Downloadable!]
  5. Hao Zhou, 2000. "A study of the finite sample properties of EMM, GMM, QMLE, and MLE for a square-root interest rate diffusion model," Finance and Economics Discussion Series 2000-45, Board of Governors of the Federal Reserve System (U.S.). [Downloadable!]
  6. Laurini, Márcio P. & Hotta, Luiz K., 2008. "Inferência indireta em modelos fracionários de taxas de juros de curto prazo," Ibmec Working Papers wpe_119, Ibmec Working Paper, Ibmec São Paulo. [Downloadable!]
  7. Romulo A. Chumacero, 1999. "Estimating Stationary ARMA Models Efficiently," Computing in Economics and Finance 1999 1333, Society for Computational Economics. [Downloadable!]
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