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A spatial rank-ordered probit model with an application to travel mode choice

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  • Mondal, Aupal
  • Bhat, Chandra R.

Abstract

Ranking data provide important additional information related to valuation because of the implied preference sequence among all alternatives, rather than just the top choice preference. This additional information from a preference ranking can be exploited to achieve a certain desired precision in choice model estimation with a much smaller sample size, making ranked data surveys much more cost-effective than first-choice surveys. In this paper, we propose a spatial rank-ordered probit (SROP) model that accommodates both spatial lag effects as well as spatial drift effects. To our knowledge, this is the first such formulation and application of an SROP model in the econometric and transportation literature. An application of the proposed model is demonstrated in a travel mode choice ranking experiment among seven alternatives, including autonomous vehicle (AV) private ride-hailing and AV pooled ride-hailing.

Suggested Citation

  • Mondal, Aupal & Bhat, Chandra R., 2022. "A spatial rank-ordered probit model with an application to travel mode choice," Transportation Research Part B: Methodological, Elsevier, vol. 155(C), pages 374-393.
    • Handle: RePEc:eee:transb:v:155:y:2022:i:c:p:374-393
    DOI: 10.1016/j.trb.2021.12.008
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    1. Daniel P. McMillen, 2010. "Issues In Spatial Data Analysis," Journal of Regional Science, Wiley Blackwell, vol. 50(1), pages 119-141, February.
    2. Chandra Bhat, 2015. "A new spatial (social) interaction discrete choice model accommodating for unobserved effects due to endogenous network formation," Transportation, Springer, vol. 42(5), pages 879-914, September.
    3. Cristiano Varin & Paolo Vidoni, 2005. "A note on composite likelihood inference and model selection," Biometrika, Biometrika Trust, vol. 92(3), pages 519-528, September.
    4. Bhat, Chandra R. & Astroza, Sebastian & Hamdi, Amin S., 2017. "A spatial generalized ordered-response model with skew normal kernel error terms with an application to bicycling frequency," Transportation Research Part B: Methodological, Elsevier, vol. 95(C), pages 126-148.
    5. 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.
    6. Carrión-Flores, Carmen E. & Flores-Lagunes, Alfonso & Guci, Ledia, 2018. "An estimator for discrete-choice models with spatial lag dependence using large samples, with an application to land-use conversions," Regional Science and Urban Economics, Elsevier, vol. 69(C), pages 77-93.
    7. Klier, Thomas & McMillen, Daniel P, 2008. "Clustering of Auto Supplier Plants in the United States," Journal of Business & Economic Statistics, American Statistical Association, vol. 26, pages 460-471.
    8. Bhat, Chandra R., 2014. "The Composite Marginal Likelihood (CML) Inference Approach with Applications to Discrete and Mixed Dependent Variable Models," Foundations and Trends(R) in Econometrics, now publishers, vol. 7(1), pages 1-117, July.
    9. 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.
    10. Rachel Croson & Uri Gneezy, 2009. "Gender Differences in Preferences," Journal of Economic Literature, American Economic Association, vol. 47(2), pages 448-474, June.
    11. Yan, Jin & Yoo, Hong Il, 2014. "The seeming unreliability of rank-ordered data as a consequence of model misspecification," MPRA Paper 56285, University Library of Munich, Germany.
    12. 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.
    13. Gopindra Sivakumar Nair & Sebastian Astroza & Chandra R. Bhat & Sara Khoeini & Ram M. Pendyala, 2018. "An application of a rank ordered probit modeling approach to understanding level of interest in autonomous vehicles," Transportation, Springer, vol. 45(6), pages 1623-1637, November.
    14. D. R. Cox, 2004. "A note on pseudolikelihood constructed from marginal densities," Biometrika, Biometrika Trust, vol. 91(3), pages 729-737, September.
    15. Munkin, Murat K. & Trivedi, Pravin K., 2008. "Bayesian analysis of the ordered probit model with endogenous selection," Journal of Econometrics, Elsevier, vol. 143(2), pages 334-348, April.
    16. Dannemiller, Katherine A. & Mondal, Aupal & Asmussen, Katherine E. & Bhat, Chandra R., 2021. "Investigating autonomous vehicle impacts on individual activity-travel behavior," Transportation Research Part A: Policy and Practice, Elsevier, vol. 148(C), pages 402-422.
    17. Alejandro Tirachini, 2020. "Ride-hailing, travel behaviour and sustainable mobility: an international review," Transportation, Springer, vol. 47(4), pages 2011-2047, August.
    18. Nazneen Ferdous & Chandra Bhat, 2013. "A spatial panel ordered-response model with application to the analysis of urban land-use development intensity patterns," Journal of Geographical Systems, Springer, vol. 15(1), pages 1-29, January.
    19. Alejandro Caparrós & José L. Oviedo & Pablo Campos, 2008. "Would You Choose Your Preferred Option? Comparing Choice and Recoded Ranking Experiments," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 90(3), pages 843-855.
    20. Kurt J. Beron & Wim P. M. Vijverberg, 2004. "Probit in a Spatial Context: A Monte Carlo Analysis," Advances in Spatial Science, in: Luc Anselin & Raymond J. G. M. Florax & Sergio J. Rey (ed.), Advances in Spatial Econometrics, chapter 8, pages 169-195, Springer.
    21. Hausman, Jerry A. & Ruud, Paul A., 1987. "Specifying and testing econometric models for rank-ordered data," Journal of Econometrics, Elsevier, vol. 34(1-2), pages 83-104.
    22. Keane, Michael P, 1992. "A Note on Identification in the Multinomial Probit Model," Journal of Business & Economic Statistics, American Statistical Association, vol. 10(2), pages 193-200, April.
    23. Anna Gloria Billé & Giuseppe Arbia, 2019. "Spatial Limited Dependent Variable Models: A Review Focused On Specification, Estimation, And Health Economics Applications," Journal of Economic Surveys, Wiley Blackwell, vol. 33(5), pages 1531-1554, December.
    24. Wesley Hartmann & Puneet Manchanda & Harikesh Nair & Matthew Bothner & Peter Dodds & David Godes & Kartik Hosanagar & Catherine Tucker, 2008. "Modeling social interactions: Identification, empirical methods and policy implications," Marketing Letters, Springer, vol. 19(3), pages 287-304, December.
    25. Luc Anselin, 2010. "Thirty years of spatial econometrics," Papers in Regional Science, Wiley Blackwell, vol. 89(1), pages 3-25, March.
    26. Sonja Haustein, 2021. "The hidden value of car ownership," Nature Sustainability, Nature, vol. 4(9), pages 752-753, September.
    27. Beggs, S. & Cardell, S. & Hausman, J., 1981. "Assessing the potential demand for electric cars," Journal of Econometrics, Elsevier, vol. 17(1), pages 1-19, September.
    28. Bhat, Chandra R., 2018. "New matrix-based methods for the analytic evaluation of the multivariate cumulative normal distribution function," Transportation Research Part B: Methodological, Elsevier, vol. 109(C), pages 238-256.
    29. Franzese, Robert J. & Hays, Jude C. & Cook, Scott J., 2016. "Spatial- and Spatiotemporal-Autoregressive Probit Models of Interdependent Binary Outcomes," Political Science Research and Methods, Cambridge University Press, vol. 4(1), pages 151-173, January.
    30. Foster, Vivien & Mourato, Susana, 2002. "Testing for Consistency in Contingent Ranking Experiments," Journal of Environmental Economics and Management, Elsevier, vol. 44(2), pages 309-328, September.
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