This file is part of IDEAS, which uses RePEc data


[ Papers | Articles | Software | Books | Chapters | Authors | Institutions | JEL Classification | NEP reports | Search | New papers by email | Author registration | Rankings | Volunteers | FAQ | Blog | Help! ]

Simulated Score Methods and Indirect Inference for Continuous-time Models

Author info | Abstract | Publisher info | Download info | Related research | Statistics
Author Info
Gallant, A. Ronald
Tauchen, George

Additional information is available for the following registered author(s):

Abstract

We describe a simulated method of moments estimator that is implemented by choosing the vector valued moment function to be the expectation under the structural model of the score function of an auxiliary model, where the parameters of the auxiliary model are eliminated by replacing them with their quasi-maximum likelihood estimates. This leaves a moment vector depending only the parameters of the structural model. Structural parameter estimates are those parameter values that put the moment vector as closely to zero as possible in a suitable GMM metric. This methodology can also be interpreted as a practical computational strategy for implementing indirect inference. We argue that considerations from statistical science dictate that the auxiliary model should approximate the true data generating process as closely as possible and show that using the SNP model is one means to that end. When the view of close approximation is accepted in implementation, the methodology described is usually referred to as Efficient Method of Moments (EMM) in the literature because (i) the estimator is asymptotically as efficient as maximum likelihood under correct specification, and (ii) detection of model error is assured under incorrect specification. There are alternative views toward the desirability of close approximation to the data, which we discuss.

Download Info
To download:

If you experience problems downloading a file, check if you have the proper application to view it first. Information about this may be contained in the File-Format links below. 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://www.econ.duke.edu/Papers/Abstracts02/abstract.02.09.html
File Format:
File Function: main text
Download Restriction: no

Publisher Info
Paper provided by Duke University, Department of Economics in its series Working Papers with number 02-09.

Download reference. The following formats are available: HTML (with abstract), plain text (with abstract), BibTeX, RIS (EndNote, RefMan, ProCite), ReDIF
Length:
Date of creation: 2002
Date of revision:
Handle: RePEc:duk:dukeec:02-09

Contact details of provider:
Postal: Department of Economics Duke University 213 Social Sciences Building Box 90097 Durham, NC 27708-0097
Phone: (919) 660-1800
Fax: (919) 684-8974
Web page: http://www.econ.duke.edu/

For technical questions regarding this item, or to correct its listing, contact: (Department of Economics Webmaster).

Related research
Keywords:

Other versions of this item:

This paper has been announced in the following NEP Reports: Cited by:
(explanations, 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. Siddhartha Chib & Michael K Pitt & Neil Shephard, 2004. "Likelihood based inference for diffusion driven models," Economics Papers 2004-W20, Economics Group, Nuffield College, University of Oxford. [Downloadable!]
    Other versions:
  2. In Kim & In-Seok Baek & Jaesun Noh & Sol Kim, 2007. "The role of stochastic volatility and return jumps: reproducing volatility and higher moments in the KOSPI 200 returns dynamics," Review of Quantitative Finance and Accounting, Springer, vol. 29(1), pages 69-110, July. [Downloadable!] (restricted)
  3. Jérôme B. Detemple & René Garcia & Marcel Rindisbacher, 2003. "Asymptotic Properties of Monte Carlo Estimators of Diffusion Processes," CIRANO Working Papers 2003s-11, CIRANO. [Downloadable!]
    Other versions:
  4. David S. Bates, 2003. "Maximum Likelihood Estimation of Latent Affine Processes," NBER Working Papers 9673, National Bureau of Economic Research, Inc. [Downloadable!] (restricted)
  5. Francisco Peñaranda & Jón Daníelsson, 2007. "On the Impact of Fundamentals, Liquidity and Coordination on Market Stability," Economics Working Papers 1003, Department of Economics and Business, Universitat Pompeu Fabra. [Downloadable!]
    Other versions:
  6. 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!]
    Other versions:
  7. Peter N Smith & Michael R Wickens, . "Asset Pricing with Observable Stochastic Discount Factors," Discussion Papers 02/03, Department of Economics, University of York. [Downloadable!]
    Other versions:
  8. Ravi Bansal & A. Ronald Gallant & George Tauchen, 2007. "Rational Pessimism, Rational Exuberance, and Asset Pricing Models," NBER Working Papers 13107, National Bureau of Economic Research, Inc. [Downloadable!] (restricted)
  9. Torben G. Andersen & Tim Bollerslev & Nour Meddahi, 2002. "Analytic Evaluation of Volatility Forecasts," CIRANO Working Papers 2002s-90, CIRANO. [Downloadable!]
    Other versions:
Statistics
Access and download statistics

Did you know? You can use IDEAS to provide links to papers and articles in your course syllabus.

This page was last updated on 2009-11-25.

This information is provided to you by IDEAS at the Department of Economics, College of Liberal Arts and Sciences, University of Connecticut using RePEc data on a server sponsored by the Society for Economic Dynamics.