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A multi-level cross-classified model for discrete response variables

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  • Bhat, Chandra R.

Abstract

In many spatial analysis contexts, the variable of interest is discrete and there is spatial clustering of observations. This paper formulates a model that accommodates clustering along more than one dimension in the context of a discrete response variable. For example, in a travel mode choice context, individuals are clustered by both the home zone in which they live as well as by their work locations. The model formulation takes the form of a mixed logit structure and is estimated by maximum likelihood using a combination of Gaussian quadrature and quasi-Monte Carlo simulation techniques. An application to travel mode choice suggests that ignoring the spatial context in which individuals make mode choice decisions can lead to an inferior data fit as well as provide inconsistent evaluations of transportation policy measures.

Suggested Citation

  • Bhat, Chandra R., 2000. "A multi-level cross-classified model for discrete response variables," Transportation Research Part B: Methodological, Elsevier, vol. 34(7), pages 567-582, September.
  • Handle: RePEc:eee:transb:v:34:y:2000:i:7:p:567-582
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    References listed on IDEAS

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    1. N Bullen & K Jones & C Duncan, 1997. "Modelling complexity: analysing between-individual and between-place variation -- a multilevel tutorial," Environment and Planning A, Pion Ltd, London, vol. 29(4), pages 585-609, April.
    2. Bhat, Chandra R., 1998. "Accommodating variations in responsiveness to level-of-service measures in travel mode choice modeling," Transportation Research Part A: Policy and Practice, Elsevier, vol. 32(7), pages 495-507, September.
    3. Feenberg, Daniel & Skinner, Jonathan, 1994. "The Risk and Duration of Catastrophic Health Care Expenditures," The Review of Economics and Statistics, MIT Press, vol. 76(4), pages 633-647, November.
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    Cited by:

    1. Arbués, Pelayo & Baños, José F. & Mayor, Matías & Suárez, Patricia, 2016. "Determinants of ground transport modal choice in long-distance trips in Spain," Transportation Research Part A: Policy and Practice, Elsevier, vol. 84(C), pages 131-143.
    2. Héctor López-Ospina & Francisco Martínez & Cristián Cortés, 2015. "A time-hierarchical microeconomic model of activities," Transportation, Springer, vol. 42(2), pages 211-236, March.
    3. Makoto Chikaraishi & Akimasa Fujiwara & Junyi Zhang & Kay Axhausen, 2011. "Identifying variations and co-variations in discrete choice models," Transportation, Springer, vol. 38(6), pages 993-1016, November.
    4. repec:gam:jsusta:v:9:y:2017:i:10:p:1824-:d:114594 is not listed on IDEAS
    5. Stephane Hess & John W. Polak, 2004. "An analysis of parking behaviour using discrete choice models calibrated on SP datasets," ERSA conference papers ersa04p60, European Regional Science Association.
    6. Bhat, Chandra R., 2015. "A comprehensive dwelling unit choice model accommodating psychological constructs within a search strategy for consideration set formation," Transportation Research Part B: Methodological, Elsevier, vol. 79(C), pages 161-188.
    7. Mikaela Backman, 2014. "Human capital in firms and regions: Impact on firm productivity," Papers in Regional Science, Wiley Blackwell, vol. 93(3), pages 557-575, August.
    8. Bhat, Chandra & Zhao, Huimin, 2002. "The spatial analysis of activity stop generation," Transportation Research Part B: Methodological, Elsevier, vol. 36(6), pages 557-575, July.
    9. Bhat, Chandra R. & Sener, Ipek N. & Eluru, Naveen, 2010. "A flexible spatially dependent discrete choice model: Formulation and application to teenagers' weekday recreational activity participation," Transportation Research Part B: Methodological, Elsevier, vol. 44(8-9), pages 903-921, September.
    10. Chandra Bhat & Ipek Sener, 2009. "A copula-based closed-form binary logit choice model for accommodating spatial correlation across observational units," Journal of Geographical Systems, Springer, vol. 11(3), pages 243-272, September.
    11. Jie Lin & Liang Long, 2008. "What neighborhood are you in? Empirical findings of relationships between household travel and neighborhood characteristics," Transportation, Springer, vol. 35(6), pages 739-758, November.
    12. Maksim Belitski & Sameeksha Desai, 2016. "What drives ICT clustering in European cities?," The Journal of Technology Transfer, Springer, vol. 41(3), pages 430-450, June.
    13. Konstadinos Goulias, 2002. "Multilevel analysis of daily time use and time allocation to activity types accounting for complex covariance structures using correlated random effects," Transportation, Springer, vol. 29(1), pages 31-48, February.
    14. Bhat, Chandra R. & Astroza, Sebastian & Bhat, Aarti C. & Nagel, Kai, 2016. "Incorporating a multiple discrete-continuous outcome in the generalized heterogeneous data model: Application to residential self-selection effects analysis in an activity time-use behavior model," Transportation Research Part B: Methodological, Elsevier, vol. 91(C), pages 52-76.
    15. 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.
    16. Jinhyun Hong & Qing Shen & Lei Zhang, 2014. "How do built-environment factors affect travel behavior? A spatial analysis at different geographic scales," Transportation, Springer, vol. 41(3), pages 419-440, May.
    17. Yu, Jie & Goos, Peter & Vandebroek, Martina, 2010. "Comparing different sampling schemes for approximating the integrals involved in the efficient design of stated choice experiments," Transportation Research Part B: Methodological, Elsevier, vol. 44(10), pages 1268-1289, December.
    18. Bhat, Chandra R. & Castro, Marisol & Pinjari, Abdul Rawoof, 2015. "Allowing for complementarity and rich substitution patterns in multiple discrete–continuous models," Transportation Research Part B: Methodological, Elsevier, vol. 81(P1), pages 59-77.
    19. Chuan Ding & Yaowu Wang & Binglei Xie & Chao Liu, 2014. "Understanding the Role of Built Environment in Reducing Vehicle Miles Traveled Accounting for Spatial Heterogeneity," Sustainability, MDPI, Open Access Journal, vol. 6(2), pages 1-13, January.

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