IDEAS home Printed from https://ideas.repec.org/p/sce/scecf7/5.html
   My bibliography  Save this paper

Finite Sample Properties of the Efficient Method of Moments

Author

Listed:
  • Romulo Chumacero

    (University of Chile)

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.
(This abstract was borrowed from another version of this item.)

Suggested Citation

  • Romulo Chumacero, "undated". "Finite Sample Properties of the Efficient Method of Moments," Computing in Economics and Finance 1997 5, Society for Computational Economics.
    • Handle: RePEc:sce:scecf7:5
    as

    Download full text from publisher

    File URL: http://bucky.stanford.edu/cef97/abstracts/chumacero.html
    File Function: paper abstract
    Download Restriction: no
    ---><---

    Other versions of this item:

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Chumacero Rómulo A., 2001. "Estimating ARMA Models Efficiently," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 5(2), pages 1-14, July.
    2. Gallant, A. Ronald & Tauchen, George, 2002. "Simulated Score Methods and Indirect Inference for Continuous-time Models," Working Papers 02-09, Duke University, Department of Economics.
    3. 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.).
    4. Coppejans, Mark & Gallant, A. Ronald, 2002. "Cross-validated SNP density estimates," Journal of Econometrics, Elsevier, vol. 110(1), pages 27-65, September.
    5. Rómulo A. Chumacero, 2005. "A Toolkit for Analyzing Alternative Policies in the Chilean Economy," Central Banking, Analysis, and Economic Policies Book Series, in: Rómulo A. Chumacero & Klaus Schmidt-Hebbel & Norman Loayza (Series Editor) & Klaus Schmidt-Hebbel (S (ed.),General Equilibrium Models for the Chilean Economy, edition 1, volume 9, chapter 8, pages 261-302, Central Bank of Chile.
    6. Veiga, Helena, 2006. "A two factor long memory stochastic volatility model," DES - Working Papers. Statistics and Econometrics. WS ws061303, Universidad Carlos III de Madrid. Departamento de Estadística.
    7. 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.
    8. Ronald Gallant, A. & Tauchen, George, 1999. "The relative efficiency of method of moments estimators1," Journal of Econometrics, Elsevier, vol. 92(1), pages 149-172, September.
    9. 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.
    10. Laurini, Márcio Poletti & Hotta, Luiz Koodi, 2013. "Indirect Inference in fractional short-term interest rate diffusions," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 94(C), pages 109-126.
    11. Romulo A. Chumacero, 1999. "Estimating Stationary ARMA Models Efficiently," Computing in Economics and Finance 1999 1333, Society for Computational Economics.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:sce:scecf7:5. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Christopher F. Baum (email available below). General contact details of provider: https://edirc.repec.org/data/sceeeea.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.