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Correcting for endogeneity due to omitted crowding in public transport choice using the Multiple Indicator Solution (MIS) method

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  • Guevara, C. Angelo
  • Tirachini, Alejandro
  • Hurtubia, Ricardo
  • Dekker, Thijs

Abstract

Crowding levels are very relevant for the analysis and evaluation of the performance of public transport as they strongly affect the level of service and the overall perceived quality of the system. However, crowding is not an easy variable to measure and, hence, demand models often tend to ignore or use abstract proxies for it. In this paper, we assess the Multiple Indicator Solution (MIS) method in a Stated Preference (SP) experiment where crowding conditions were displayed to the respondent but are artificially omitted in the estimation of a curtailed model to cause endogeneity. Results provide evidence that the MIS method can be used to control for a wide range of omitted attributes in SP data. We also discuss the potential application of this approach to Revealed Preferences (RP) models of public transport by asking suitable post-trip questions to users. Two MIS variations were applied to this SP case study and both provided outcomes that were superior to those of the curtailed model. We enrich the analysis with the aid of Monte Carlo simulation. Results suggest that potential problems may arise in the presence of neglected interactions and if indicators are only weakly correlated with the omitted attribute. For the SP case study analysed, only the former issue seems to play a role in the results. The article finishes by discussing the implications of these findings for the correction of endogeneity on SP and RP data on public transport and suggesting future lines of research in this area.

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  • Guevara, C. Angelo & Tirachini, Alejandro & Hurtubia, Ricardo & Dekker, Thijs, 2020. "Correcting for endogeneity due to omitted crowding in public transport choice using the Multiple Indicator Solution (MIS) method," Transportation Research Part A: Policy and Practice, Elsevier, vol. 137(C), pages 472-484.
  • Handle: RePEc:eee:transa:v:137:y:2020:i:c:p:472-484
    DOI: 10.1016/j.tra.2018.10.030
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    1. Guevara, Cristian Angelo & Thomas, Alan, 2007. "Multiple classification analysis in trip production models," Transport Policy, Elsevier, vol. 14(6), pages 514-522, November.
    2. Cox, Tom & Houdmont, Jonathan & Griffiths, Amanda, 2006. "Rail passenger crowding, stress, health and safety in Britain," Transportation Research Part A: Policy and Practice, Elsevier, vol. 40(3), pages 244-258, March.
    3. Guevara, C. Angelo, 2015. "Critical assessment of five methods to correct for endogeneity in discrete-choice models," Transportation Research Part A: Policy and Practice, Elsevier, vol. 82(C), pages 240-254.
    4. Hausman, Jerry & McFadden, Daniel, 1984. "Specification Tests for the Multinomial Logit Model," Econometrica, Econometric Society, vol. 52(5), pages 1219-1240, September.
    5. Jeffrey M Wooldridge, 2010. "Econometric Analysis of Cross Section and Panel Data," MIT Press Books, The MIT Press, edition 2, volume 1, number 0262232588, April.
    6. Heckman, James J, 1978. "Dummy Endogenous Variables in a Simultaneous Equation System," Econometrica, Econometric Society, vol. 46(4), pages 931-959, July.
    7. Tirachini, Alejandro & Hurtubia, Ricardo & Dekker, Thijs & Daziano, Ricardo A., 2017. "Estimation of crowding discomfort in public transport: Results from Santiago de Chile," Transportation Research Part A: Policy and Practice, Elsevier, vol. 103(C), pages 311-326.
    8. James H. Stock & Motohiro Yogo, 2002. "Testing for Weak Instruments in Linear IV Regression," NBER Technical Working Papers 0284, National Bureau of Economic Research, Inc.
    9. Tirachini, Alejandro & Hensher, David A. & Rose, John M., 2014. "Multimodal pricing and optimal design of urban public transport: The interplay between traffic congestion and bus crowding," Transportation Research Part B: Methodological, Elsevier, vol. 61(C), pages 33-54.
    10. Cristian Angelo Guevara & Moshe E. Ben-Akiva, 2012. "Change of Scale and Forecasting with the Control-Function Method in Logit Models," Transportation Science, INFORMS, vol. 46(3), pages 425-437, August.
    11. Guevara, C. Angelo, 2018. "Overidentification tests for the exogeneity of instruments in discrete choice models," Transportation Research Part B: Methodological, Elsevier, vol. 114(C), pages 241-253.
    12. Pinar Karaca-Mandic & Kenneth Train, 2003. "Standard error correction in two-stage estimation with nested samples," Econometrics Journal, Royal Economic Society, vol. 6(2), pages 401-407, December.
    13. Raveau, Sebastián & Muñoz, Juan Carlos & de Grange, Louis, 2011. "A topological route choice model for metro," Transportation Research Part A: Policy and Practice, Elsevier, vol. 45(2), pages 138-147, February.
    14. Mark Wardman & Gerard Whelan, 2011. "Twenty Years of Rail Crowding Valuation Studies: Evidence and Lessons from British Experience," Transport Reviews, Taylor & Francis Journals, vol. 31(3), pages 379-398.
    15. Tirachini, Alejandro & Sun, Lijun & Erath, Alexander & Chakirov, Artem, 2016. "Valuation of sitting and standing in metro trains using revealed preferences," Transport Policy, Elsevier, vol. 47(C), pages 94-104.
    16. Sergio Jara-Díaz & Antonio Gschwender, 2003. "Towards a general microeconomic model for the operation of public transport," Transport Reviews, Taylor & Francis Journals, vol. 23(4), pages 453-469, July.
    17. Fernández-Antolín, Anna & Guevara, C. Angelo & de Lapparent, Matthieu & Bierlaire, Michel, 2016. "Correcting for endogeneity due to omitted attitudes: Empirical assessment of a modified MIS method using RP mode choice data," Journal of choice modelling, Elsevier, vol. 20(C), pages 1-15.
    18. Train, Kenneth & Wilson, Wesley W., 2008. "Estimation on stated-preference experiments constructed from revealed-preference choices," Transportation Research Part B: Methodological, Elsevier, vol. 42(3), pages 191-203, March.
    19. Joel L. Horowitz, 1983. "Statistical Comparison of Non-Nested Probabilistic Discrete Choice Models," Transportation Science, INFORMS, vol. 17(3), pages 319-350, August.
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