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A hazard-based duration model of shopping activity with nonparametric baseline specification and nonparametric control for unobserved heterogeneity

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  • Bhat, Chandra R.
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    Abstract

    Activity duration is an important component of the activity participation behavior of individuals, and therefore, an important determinant of individual travel behavior. In this paper, we examine the factors affecting shopping activity duration during the return home from work and develop a comprehensive methodological framework to estimate a stochastic hazard-based duration model from grouped (interval-level) failure data. The framework accommodates a nonparametric baseline hazard distribution and allows for nonparametric control of unobserved heterogeneity, while incorporating the effects of covariates. The framework also facilitates statistical testing of alternative parametric assumptions on the baseline hazard distribution and on the unobserved heterogeneity distribution. Our empirical results indicate significant effects of unobserved heterogeneity on shopping activity duration of individuals. Further, we find that parametric forms for the baseline hazard and unobserved heterogeneity distributions are inadequate, and are likely to lead to substantial biases in covariate effects and hazard dynamics. The empirical results also provide insights into the determinants of shopping activity duration during the commute trip.

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

    Volume (Year): 30 (1996)
    Issue (Month): 3 (June)
    Pages: 189-207

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    Handle: RePEc:eee:transb:v:30:y:1996:i:3:p:189-207

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    1. Sueyoshi, Glenn T., 1992. "Semiparametric proportional hazards estimation of competing risks models with time-varying covariates," Journal of Econometrics, Elsevier, vol. 51(1-2), pages 25-58.
    2. Lancaster, Tony, 1985. "Generalised residuals and heterogeneous duration models : With applications to the Weilbull model," Journal of Econometrics, Elsevier, vol. 28(1), pages 155-169, April.
    3. Flinn, C. & Heckman, J., 1982. "New methods for analyzing structural models of labor force dynamics," Journal of Econometrics, Elsevier, vol. 18(1), pages 115-168, January.
    4. Han, Aaron & Hausman, Jerry A, 1990. "Flexible Parametric Estimation of Duration and Competing Risk Models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 5(1), pages 1-28, January-M.
    5. Heckman, James & Singer, Burton, 1984. "A Method for Minimizing the Impact of Distributional Assumptions in Econometric Models for Duration Data," Econometrica, Econometric Society, vol. 52(2), pages 271-320, March.
    6. Bruce D. Meyer, 1988. "Unemployment Insurance And Unemployment Spells," NBER Working Papers 2546, National Bureau of Economic Research, Inc.
    7. Dipak C. Jain & Naufel J. Vilcassim, 1991. "Investigating Household Purchase Timing Decisions: A Conditional Hazard Function Approach," Marketing Science, INFORMS, vol. 10(1), pages 1-23.
    8. Kiefer, Nicholas M, 1988. "Economic Duration Data and Hazard Functions," Journal of Economic Literature, American Economic Association, vol. 26(2), pages 646-79, June.
    9. Uncles, Mark D., 1987. "A beta-logistic model of mode choice: Goodness of fit and intertemporal dependence," Transportation Research Part B: Methodological, Elsevier, vol. 21(3), pages 195-205, June.
    10. Bhat, Chandra R. & Koppelman, Frank S., 1993. "A conceptual framework of individual activity program generation," Transportation Research Part A: Policy and Practice, Elsevier, vol. 27(6), pages 433-446, November.
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