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Autoregressive continuous logit: Formulation and application to time-of-day choice modeling

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  • Ghader, Sepehr
  • Carrion, Carlos
  • Zhang, Lei

Abstract

In this paper, we formulate the autoregressive continuous logit model as a novel continuous choice model capable of representing correlations across alternatives in the continuous spectrum. We formulate this model by considering two approaches: combining a discrete-time autoregressive process of order one (i.e., a linear stochastic difference equation) with the continuous logit model, which leads to the discrete-time autoregressive continuous logit; and combining a continuous-time autoregressive process (i.e., a linear stochastic differential equation), known in the stochastic process literature as Ornstein-Uhlenbeck process with the continuous logit model, which leads to the continuous-time autoregressive continuous logit. The autoregressive nature of the model is in its error structure, allowing correlations in unobserved heterogeneity. For both approaches, we study their properties numerically. We also compare both approaches to highlight their relation to each other.

Suggested Citation

  • Ghader, Sepehr & Carrion, Carlos & Zhang, Lei, 2019. "Autoregressive continuous logit: Formulation and application to time-of-day choice modeling," Transportation Research Part B: Methodological, Elsevier, vol. 123(C), pages 240-257.
    • Handle: RePEc:eee:transb:v:123:y:2019:i:c:p:240-257
    DOI: 10.1016/j.trb.2019.03.023
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    References listed on IDEAS

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    1. Small, Kenneth A, 1987. "A Discrete Choice Model for Ordered Alternatives," Econometrica, Econometric Society, vol. 55(2), pages 409-424, March.
    2. Chiou, Lesley & Walker, Joan L., 2007. "Masking identification of discrete choice models under simulation methods," Journal of Econometrics, Elsevier, vol. 141(2), pages 683-703, December.
    3. Bhat, Chandra R., 1998. "Accommodating flexible substitution patterns in multi-dimensional choice modeling: formulation and application to travel mode and departure time choice," Transportation Research Part B: Methodological, Elsevier, vol. 32(7), pages 455-466, September.
    4. Stephane Hess & John Polak & Andrew Daly & Geoffrey Hyman, 2007. "Flexible substitution patterns in models of mode and time of day choice: new evidence from the UK and the Netherlands," Transportation, Springer, vol. 34(2), pages 213-238, March.
    5. Train,Kenneth E., 2009. "Discrete Choice Methods with Simulation," Cambridge Books, Cambridge University Press, number 9780521766555.
    6. Joan L. Walker & Moshe Ben-Akiva & Denis Bolduc, 2007. "Identification of parameters in normal error component logit-mixture (NECLM) models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 22(6), pages 1095-1125.
    7. de Jong, Gerard & Daly, Andrew & Pieters, Marits & Vellay, Carine & Bradley, Mark & Hofman, Frank, 2003. "A model for time of day and mode choice using error components logit," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 39(3), pages 245-268, May.
    8. Walker, Joan & Ben-Akiva, Moshe, 2002. "Generalized random utility model," Mathematical Social Sciences, Elsevier, vol. 43(3), pages 303-343, July.
    9. Bhat, Chandra R., 1996. "A hazard-based duration model of shopping activity with nonparametric baseline specification and nonparametric control for unobserved heterogeneity," Transportation Research Part B: Methodological, Elsevier, vol. 30(3), pages 189-207, June.
    10. Small, Kenneth A, 1982. "The Scheduling of Consumer Activities: Work Trips," American Economic Review, American Economic Association, vol. 72(3), pages 467-479, June.
    11. Bhat, Chandra R. & Steed, Jennifer L., 2002. "A continuous-time model of departure time choice for urban shopping trips," Transportation Research Part B: Methodological, Elsevier, vol. 36(3), pages 207-224, March.
    12. Mahmassani, Hani S. & Chang, Gang-Len, 1986. "Experiments with departure time choice dynamics of urban commuters," Transportation Research Part B: Methodological, Elsevier, vol. 20(4), pages 297-320, August.
    13. Lemp, Jason D. & Kockelman, Kara M. & Damien, Paul, 2010. "The continuous cross-nested logit model: Formulation and application for departure time choice," Transportation Research Part B: Methodological, Elsevier, vol. 44(5), pages 646-661, June.
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