Advanced Search
MyIDEAS: Login

Finite Sample Properties of the Efficient Method of Moments

Contents:

Author Info

  • 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.)

Download Info

If you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.
File URL: http://bucky.stanford.edu/cef97/abstracts/chumacero.html
Our checks indicate that this address may not be valid because: 500 Can't connect to bucky.stanford.edu:80 (10060). If this is indeed the case, please notify (Christopher F. Baum)
File Function: paper abstract
Download Restriction: no

Bibliographic Info

Paper provided by Society for Computational Economics in its series Computing in Economics and Finance 1997 with number 5.

as in new window
Length:
Date of creation:
Date of revision:
Handle: RePEc:sce:scecf7:5

Contact details of provider:
Postal: CEF97, Stanford University, Department of Economics, Stanford CA USA
Web page: http://bucky.stanford.edu/cef97/
More information through EDIRC

Related research

Keywords:

Other versions of this item:

References

No references listed on IDEAS
You can help add them by filling out this form.

Citations

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

Cited by:
  1. Coppejans, Mark & Gallant, A. Ronald, 2000. "Cross Validated SNP Density Estimates," Working Papers 00-10, Duke University, Department of Economics.
  2. 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.
  3. 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.
  4. Rómulo Chumacero, 2003. "A Toolkit for Analyzing Alternative Policies in The Chilean Economy," Working Papers Central Bank of Chile 241, Central Bank of Chile.
  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.).
  6. Romulo A. Chumacero, 1999. "Estimating Stationary ARMA Models Efficiently," Computing in Economics and Finance 1999 1333, Society for Computational Economics.
  7. 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.
  8. Rómulo Chumacero, 2001. "Estimating ARMA Models Efficiently," Working Papers Central Bank of Chile 92, Central Bank of Chile.
  9. 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.

Lists

This item is not listed on Wikipedia, on a reading list or among the top items on IDEAS.

Statistics

Access and download statistics

Corrections

When requesting a correction, please mention this item's handle: RePEc:sce:scecf7:5. See general information about how to correct material in RePEc.

For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Christopher F. Baum).

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.

If references are entirely missing, you can add them using this form.

If the full references list an item that is present in RePEc, but the system did not link to it, you can help with 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 profile, as there may be some citations waiting for confirmation.

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