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! ]

Asymptotic Bias in Simulated Maximum Likelihood Estimation of Discrete Choice Models

Author info | Abstract | Publisher info | Download info | Related research | Statistics
Author Info
Lee, Lung-Fei
Abstract

In this article, we investigate a bias in an asymptotic expansion of the simulated maximum likelihood estimator introduced by Lerman and Manski (pp. 305 319 in C. Manski and D. McFadden (eds.), Structural Analysis of Discrete Data with Econometric Applications, Cambridge: MIT Press, 1981) for the estimation of discrete choice models. This bias occurs due to the nonlinearity of the derivatives of the log likelihood function and the statistically independent simulation errors of the choice probabilities across observations. This bias can be the dominating bias in an asymptotic expansion of the simulated maximum likelihood estimator when the number of simulated random variables per observation does not increase at least as fast as the sample size. The properly normalized simulated maximum likelihood estimator even has an asymptotic bias in its limiting distribution if the number of simulated random variables increases only as fast as the square root of the sample size. A bias-adjustment is introduced that can reduce the bias. Some Monte Carlo experiments have demonstrated the usefulness of the bias-adjustment procedure.

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://journals.cambridge.org/abstract_S0266466600009361
File Format: text/html
File Function: link to article abstract page
Download Restriction: no

Publisher Info
Article provided by Cambridge University Press in its journal Econometric Theory.

Volume (Year): 11 (1995)
Issue (Month): 03 (June)
Pages: 437-483
Download reference. The following formats are available: HTML (with abstract), plain text (with abstract), BibTeX, RIS (EndNote, RefMan, ProCite), ReDIF
Handle: RePEc:cup:etheor:v:11:y:1995:i:03:p:437-483_00

Contact details of provider:
Postal: The Edinburgh Building, Shaftesbury Road, Cambridge CB2 2RU UK
Fax: +44 (0)1223 325150
Email:
Web page: http://journals.cambridge.org/jid_ECT

For technical questions regarding this item, or to correct its listing, contact: (Mike Eden).

Related research
Keywords:

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. Erik Meijer & Arie Kapteyn & Tatiana Andreyeva, 2008. "Health Indexes and Retirement Modeling in International Comparisons," Working Papers 614, RAND Corporation Publications Department. [Downloadable!]
  2. Chappell, Henry & Guimaraes, Paulo & Ozturk, Orgul, 2006. "Confessions of an Internet Monopolist: Demand Estimation for a Versioned Information Good," MPRA Paper 10106, University Library of Munich, Germany, revised 2008. [Downloadable!]
  3. Ziegler, Andreas R., 2001. "Simulated z-tests in multinomial probit models," ZEW Discussion Papers 01-53, ZEW - Zentrum für Europäische Wirtschaftsforschung / Center for European Economic Research. [Downloadable!]
  4. Kamhon Kan & Chihwa Kao, 2005. "Simulation-Based Two-Step Estimation with Endogenous Regressors," Center for Policy Research Working Papers 76, Center for Policy Research, Maxwell School, Syracuse University. [Downloadable!]
  5. Daniel A. Ackerberg, 2001. "A New Use of Importance Sampling to Reduce Computational Burden in Simulation Estimation," NBER Technical Working Papers 0273, National Bureau of Economic Research, Inc. [Downloadable!] (restricted)
  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. Kenneth A. Small & Clifford Winston & Jia Yan, 2005. "Differentiated Road Pricing, Express Lanes and Carpools: Exploiting Heterogeneous Preferences in Policy Design," Working Papers 050616, University of California-Irvine, Department of Economics, revised Mar 2006. [Downloadable!]
  8. Ziegler, Andreas & Eymann, Angelika, . "Zur Simulated Maximum-Likelihood-Schätzung von Mehrperioden-Mehralternativen-Probitmodellen," IVS discussion paper series 588, Institut für Volkswirtschaft und Statistik (IVS), University of Mannheim. [Downloadable!]
  9. Ziegler, Andreas, . "Die Parameterschätzung in fehlspezifizierten Independent Probitmodellen: Eine Monte-Carlo-Studie," IVS discussion paper series 596, Institut für Volkswirtschaft und Statistik (IVS), University of Mannheim. [Downloadable!]
  10. Dick van Dijk & Dennis Fok & Philip Hans Franses, 2005. "A multi-level panel STAR model for US manufacturing sectors," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 20(6), pages 811-827. [Downloadable!]
  11. Ziegler, Andreas, . "Simulierte klassische Parameterschätzung in Probitmodellen," IVS discussion paper series 578, Institut für Volkswirtschaft und Statistik (IVS), University of Mannheim. [Downloadable!]
Statistics
Access and download statistics

Did you know? Cannot find something on IDEAS? Encourage the publisher to index it! Instructions.

This page was last updated on 2009-11-24.

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.