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Allowing for intra-respondent variations in coefficients estimated on repeated choice data

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  • Hess, Stephane
  • Rose, John M.
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    Abstract

    Partly as a result of the increasing reliance on Stated Choice (SC) data, the vast majority of discrete choice modelling applications are now estimated on data containing multiple observations for each respondent. At the same time there has been growing interest in the representation of unexplained heterogeneity in choice data, using random coefficients models such as Mixed Multinomial Logit (MMNL). The presence of multiple observations for each respondent can indeed be a great asset in the identification of such variations in tastes. However, in this paper, we question the validity of the common assumption that tastes vary across respondents but stay constant across repeated choices for the same respondent. We extend the existing framework for the MMNL analysis of panel data by allowing for intra-respondent heterogeneity on top of inter-respondent heterogeneity. An empirical analysis making use of a SC dataset for route choice confirms our hypotheses and shows that superior performance is obtained by our more general model.

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    Bibliographic Info

    Article provided by Elsevier in its journal Transportation Research Part B: Methodological.

    Volume (Year): 43 (2009)
    Issue (Month): 6 (July)
    Pages: 708-719

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    Handle: RePEc:eee:transb:v:43:y:2009:i:6:p:708-719

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    Related research

    Keywords: Taste heterogeneity Panel data Repeated choice Stated Choice Mixed logit;

    References

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    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.:
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    1. 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.
    2. 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.
    3. Brownstone, David & Train, Kenneth, 1999. "Forecasting new product penetration with flexible substitution patterns," University of California Transportation Center, Working Papers qt1j6814b3, University of California Transportation Center.
    4. John Rose & Iain Black, 2006. "Means matter, but variance matter too: Decomposing response latency influences on variance heterogeneity in stated preference experiments," Marketing Letters, Springer, vol. 17(4), pages 295-310, December.
    5. Train,Kenneth E., 2009. "Discrete Choice Methods with Simulation," Cambridge Books, Cambridge University Press, number 9780521747387, April.
    6. David Hensher & William Greene, 2003. "The Mixed Logit model: The state of practice," Transportation, Springer, vol. 30(2), pages 133-176, May.
    7. DeShazo, J. R. & Fermo, German, 2002. "Designing Choice Sets for Stated Preference Methods: The Effects of Complexity on Choice Consistency," Journal of Environmental Economics and Management, Elsevier, vol. 44(1), pages 123-143, July.
    8. Ben-Akiva, M. & Bolduc, D. & Bradley, M., 1993. "Estimation of Travel Choice Models with Randomly Distributed Values of Time," Papers 9303, Laval - Recherche en Energie.
    9. Cirillo, C. & Axhausen, K.W., 2006. "Evidence on the distribution of values of travel time savings from a six-week diary," Transportation Research Part A: Policy and Practice, Elsevier, vol. 40(5), pages 444-457, June.
    10. Bo E. Honoré & Ekaterini Kyriazidou, 2000. "Panel Data Discrete Choice Models with Lagged Dependent Variables," Econometrica, Econometric Society, vol. 68(4), pages 839-874, July.
    11. Ferrini, Silvia & Scarpa, Riccardo, 2007. "Designs with a priori information for nonmarket valuation with choice experiments: A Monte Carlo study," Journal of Environmental Economics and Management, Elsevier, vol. 53(3), pages 342-363, May.
    12. 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.
    13. Arentze, Theo & Borgers, Aloys & Timmermans, Harry & DelMistro, Romano, 2003. "Transport stated choice responses: effects of task complexity, presentation format and literacy," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 39(3), pages 229-244, May.
    14. 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.
    15. Hess, Stephane, 2007. "Posterior analysis of random taste coefficients in air travel behaviour modelling," Journal of Air Transport Management, Elsevier, vol. 13(4), pages 203-212.
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    Citations

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    Cited by:
    1. Thijs Dekker & Paul Koster & Roy Brouwer, 2013. "Changing with the Tide: Semi-Parametric Estimation of Preference Dynamics," Tinbergen Institute Discussion Papers 13-074/VIII, Tinbergen Institute.
    2. Stephane Hess & Denis Bolduc & John Polak, 2010. "Random covariance heterogeneity in discrete choice models," Transportation, Springer, vol. 37(3), pages 391-411, May.
    3. Dekker, T. & Koster, P.R. & Brouwer, R., 2012. "Changing with the tide: Semi-parametric estimation of preference dynamics," Serie Research Memoranda 0005, VU University Amsterdam, Faculty of Economics, Business Administration and Econometrics.
    4. Yáñez, M.F. & Raveau, S. & Ortúzar, J. de D., 2010. "Inclusion of latent variables in Mixed Logit models: Modelling and forecasting," Transportation Research Part A: Policy and Practice, Elsevier, vol. 44(9), pages 744-753, November.
    5. Riera, Pere & Giergiczny, Marek & Peñuelas, Josep & Mahieu, Pierre-Alexandre, 2012. "A choice modelling case study on climate change involving two-way interactions," Journal of Forest Economics, Elsevier, vol. 18(4), pages 345-354.
    6. Clifton, Geoffrey T. & Rose, John M., 2013. "A simulation of the simple Mohring model to predict patronage and value of resources consumed for enhanced bus services," Research in Transportation Economics, Elsevier, vol. 39(1), pages 259-269.
    7. Bhat, Chandra R., 2011. "The maximum approximate composite marginal likelihood (MACML) estimation of multinomial probit-based unordered response choice models," Transportation Research Part B: Methodological, Elsevier, vol. 45(7), pages 923-939, August.
    8. Bhat, Chandra R. & Sidharthan, Raghuprasad, 2011. "A simulation evaluation of the maximum approximate composite marginal likelihood (MACML) estimator for mixed multinomial probit models," Transportation Research Part B: Methodological, Elsevier, vol. 45(7), pages 940-953, August.
    9. Bliemer, Michiel C.J. & Rose, John M., 2011. "Experimental design influences on stated choice outputs: An empirical study in air travel choice," Transportation Research Part A: Policy and Practice, Elsevier, vol. 45(1), pages 63-79, January.
    10. Hess, Stephane & Train, Kenneth E., 2011. "Recovery of inter- and intra-personal heterogeneity using mixed logit models," Transportation Research Part B: Methodological, Elsevier, vol. 45(7), pages 973-990, August.

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