IDEAS home Printed from https://ideas.repec.org/a/eee/transb/v41y2007i7p784-794.html
   My bibliography  Save this article

A practical test for the choice of mixing distribution in discrete choice models

Author

Listed:
  • Fosgerau, Mogens
  • Bierlaire, Michel

Abstract

The choice of a specific distribution for random parameters of discrete choice models is a critical issue in transportation analysis. Indeed, various pieces of research have demonstrated that an inappropriate choice of the distribution may lead to serious bias in model forecast and in the estimated means of random parameters. In this paper, we propose a practical test, based on seminonparametric techniques. The test is analyzed both on synthetic and real data, and is shown to be simple and powerful.

Suggested Citation

  • Fosgerau, Mogens & Bierlaire, Michel, 2007. "A practical test for the choice of mixing distribution in discrete choice models," Transportation Research Part B: Methodological, Elsevier, vol. 41(7), pages 784-794, August.
  • Handle: RePEc:eee:transb:v:41:y:2007:i:7:p:784-794
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0191-2615(07)00013-6
    Download Restriction: Full text for ScienceDirect subscribers only

    As the access to this document is restricted, you may want to look for a different version below or search for a different version of it.

    Other versions of this item:

    References listed on IDEAS

    as
    1. Frejinger, E. & Bierlaire, M., 2007. "Capturing correlation with subnetworks in route choice models," Transportation Research Part B: Methodological, Elsevier, vol. 41(3), pages 363-378, March.
    2. Horowitz, Joel L., 1993. "Semiparametric estimation of a work-trip mode choice model," Journal of Econometrics, Elsevier, vol. 58(1-2), pages 49-70, July.
    3. Fosgerau, Mogens, 2006. "Investigating the distribution of the value of travel time savings," Transportation Research Part B: Methodological, Elsevier, vol. 40(8), pages 688-707, September.
    4. Pagan,Adrian & Ullah,Aman, 1999. "Nonparametric Econometrics," Cambridge Books, Cambridge University Press, number 9780521355643.
    5. Train,Kenneth E., 2009. "Discrete Choice Methods with Simulation," Cambridge Books, Cambridge University Press, number 9780521766555, January.
    6. Brownstone, David & Small, Kenneth A., 2005. "Valuing time and reliability: assessing the evidence from road pricing demonstrations," Transportation Research Part A: Policy and Practice, Elsevier, vol. 39(4), pages 279-293, May.
    7. Kenneth A. Small & Clifford Winston & Jia Yan, 2005. "Uncovering the Distribution of Motorists' Preferences for Travel Time and Reliability," Econometrica, Econometric Society, vol. 73(4), pages 1367-1382, July.
    8. David Revelt & Kenneth Train, 1998. "Mixed Logit With Repeated Choices: Households' Choices Of Appliance Efficiency Level," The Review of Economics and Statistics, MIT Press, vol. 80(4), pages 647-657, November.
    9. Philip A. Viton, 2004. "Will Mixed Logit Change Urban Transport Policies?," Journal of Transport Economics and Policy, University of Bath, vol. 38(3), pages 403-423, September.
    10. Kenneth E. Train, 1998. "Recreation Demand Models with Taste Differences over People," Land Economics, University of Wisconsin Press, vol. 74(2), pages 230-239.
    11. Fosgerau, Mogens, 2007. "Using nonparametrics to specify a model to measure the value of travel time," Transportation Research Part A: Policy and Practice, Elsevier, vol. 41(9), pages 842-856, November.
    12. Hess, Stephane & Bierlaire, Michel & Polak, John W., 2005. "Estimation of value of travel-time savings using mixed logit models," Transportation Research Part A: Policy and Practice, Elsevier, vol. 39(2-3), pages 221-236.
    13. Algers, S. & Bergstrom, P. & Dahlberg, M. & Dillen, J.L., 1998. "Mixed Logit Estimation of the Value of Travel Time," Papers 1998:15, Uppsala - Working Paper Series.
    14. Hess, Stephane & Train, Kenneth E. & Polak, John W., 2006. "On the use of a Modified Latin Hypercube Sampling (MLHS) method in the estimation of a Mixed Logit Model for vehicle choice," Transportation Research Part B: Methodological, Elsevier, vol. 40(2), pages 147-163, February.
    15. Klein, Roger W & Spady, Richard H, 1993. "An Efficient Semiparametric Estimator for Binary Response Models," Econometrica, Econometric Society, vol. 61(2), pages 387-421, March.
    16. Gallant, A Ronald & Nychka, Douglas W, 1987. "Semi-nonparametric Maximum Likelihood Estimation," Econometrica, Econometric Society, vol. 55(2), pages 363-390, March.
    17. Greene, William H. & Hensher, David A. & Rose, John, 2006. "Accounting for heterogeneity in the variance of unobserved effects in mixed logit models," Transportation Research Part B: Methodological, Elsevier, vol. 40(1), pages 75-92, January.
    18. Bhat, Chandra R. & Castelar, Saul, 2002. "A unified mixed logit framework for modeling revealed and stated preferences: formulation and application to congestion pricing analysis in the San Francisco Bay area," Transportation Research Part B: Methodological, Elsevier, vol. 36(7), pages 593-616, August.
    19. Hess, Stephane & Polak, John W., 2005. "Mixed logit modelling of airport choice in multi-airport regions," Journal of Air Transport Management, Elsevier, vol. 11(2), pages 59-68.
    20. Brownstone, David & Bunch, David S. & Train, Kenneth, 2000. "Joint mixed logit models of stated and revealed preferences for alternative-fuel vehicles," Transportation Research Part B: Methodological, Elsevier, vol. 34(5), pages 315-338, June.
    21. 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.
    22. David Hensher & William Greene, 2003. "The Mixed Logit model: The state of practice," Transportation, Springer, vol. 30(2), pages 133-176, May.
    23. Mogens Fosgerau, 2005. "Unit income elasticity of the value of travel time savings," Urban/Regional 0508007, University Library of Munich, Germany.
    Full references (including those not matched with items on IDEAS)

    More about this item

    JEL classification:

    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • C25 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions; Probabilities

    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:eee:transb:v:41:y:2007:i:7:p:784-794. 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: (Dana Niculescu). General contact details of provider: http://www.elsevier.com/wps/find/journaldescription.cws_home/548/description#description .

    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 CitEc recognized a reference but did not link an item in RePEc 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 RePEc Author Service 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.

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.