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‘Estimation of Discrete Choice Models Using DCM for Ox’


  • Eklöf, M.
  • Weeks, M.


DCM (Discrete Choice Models) is a package for estimating a class of discrete choice models. Written in Ox, DCM is a class that implements a wide range of discrete choice models including standard binary response models, with notable extensions including conditional mixed logit, mixed probit, multinomial probit, and random coefficient ordered choice models. The current version can handle both cross-section and static panel data. DCM represents an important development for the discrete choice computing environment in making available a broad range of models which are now widely used by academics and practitioners. Developed as a derived class of Modelbase, users may access the functions within DCM by either writing Ox programs which create and use an object of the DCM class, or use the program in an interactive fashion via OxPack in GiveWin. We demonstrate the capabilities of DCM by using a number of applications from the discrete choice literature.

Suggested Citation

  • Eklöf, M. & Weeks, M., 2004. "‘Estimation of Discrete Choice Models Using DCM for Ox’," Cambridge Working Papers in Economics 0427, Faculty of Economics, University of Cambridge.
  • Handle: RePEc:cam:camdae:0427
    Note: EM

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    References listed on IDEAS

    1. Manski, C.F., 1992. "Identification Problems in the Social Sciences," Working papers 9217, Wisconsin Madison - Social Systems.
    2. McFadden, Daniel, 1989. "A Method of Simulated Moments for Estimation of Discrete Response Models without Numerical Integration," Econometrica, Econometric Society, vol. 57(5), pages 995-1026, September.
    3. Pakes, Ariel & Pollard, David, 1989. "Simulation and the Asymptotics of Optimization Estimators," Econometrica, Econometric Society, vol. 57(5), pages 1027-1057, September.
    4. Louviere,Jordan J. & Hensher,David A. & Swait,Joffre D. With contributions by-Name:Adamowicz,Wiktor, 2000. "Stated Choice Methods," Cambridge Books, Cambridge University Press, number 9780521788304, March.
    5. Bhat, Chandra R., 2003. "Simulation estimation of mixed discrete choice models using randomized and scrambled Halton sequences," Transportation Research Part B: Methodological, Elsevier, vol. 37(9), pages 837-855, November.
    6. Manski, C.F., 1989. "The Use Of Intentions Data To Predict Behaviour : A Best- Case Analysis," Working papers 8905, Wisconsin Madison - Social Systems.
    7. Daniel McFadden & Kenneth Train, 2000. "Mixed MNL models for discrete response," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 15(5), pages 447-470.
    8. Alan Duncan & Melvyn Weeks, "undated". "Non-Nested Models of Labour Supply with Discrete Choices," Discussion Papers 97/20, Department of Economics, University of York.
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    More about this item


    discrete choice models; simulation methods; multinomial probit; mixed logit; ordinal response; revealed preference;

    JEL classification:

    • C87 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Econometric Software
    • C25 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions; Probabilities
    • C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General

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