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Latent Variables in a Travel Mode Choice Model: Attitudinal and Behavioural Indicator Variables

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  • Vredin Johansson, Maria

    (Department of Economics)

  • Heldt, Tobias

    (Department of Economics)

  • Johansson, Per

    (Department of Economics)

Abstract

In a travel mode choice context, we use survey data to construct and test the significance of five individual specific latent variables – environmental preferences, safety, comfort, convenience and flexibility - postulated to be important for modal choice. Whereas the construction of the safety and environmental preference variables is based on behavioural indicator variables, the construction of the comfort, convenience and flexibility variables is based on attitudinal indicator variables. Our main findings are that the latent variables enriched discrete choice model outperforms the traditional discrete choice model and that the construct reliability of the “attitudinal” latent variables is higher than that of the “behavioural” latent variables. Important for the choice of travel mode are modal travel time and cost and the individual’s preferences for flexibility and comfort as well as her environmental preferences.

Suggested Citation

  • Vredin Johansson, Maria & Heldt, Tobias & Johansson, Per, 2005. "Latent Variables in a Travel Mode Choice Model: Attitudinal and Behavioural Indicator Variables," Working Paper Series 2005:5, Uppsala University, Department of Economics.
    • Handle: RePEc:hhs:uunewp:2005_005
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    References listed on IDEAS

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    1. Murphy, Kevin M & Topel, Robert H, 2002. "Estimation and Inference in Two-Step Econometric Models," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(1), pages 88-97, January.
    2. Smith, V Kerry & Desvousges, William H, 1987. "An Empirical Analysis of the Economic Value of Risk Changes," Journal of Political Economy, University of Chicago Press, vol. 95(1), pages 89-114, February.
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    Cited by:

    1. Stephane Hess & Nesha Beharry-Borg, 2012. "Accounting for Latent Attitudes in Willingness-to-Pay Studies: The Case of Coastal Water Quality Improvements in Tobago," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 52(1), pages 109-131, May.
    2. Chen, Jie, 2006. "The Dynamics of Housing Allowance Claims in Sweden: A discrete-time hazard analysis," Working Paper Series 2006:1, Uppsala University, Department of Economics.
    3. Yáñez, M.F. & Raveau, S. & Ortúzar, J. de D., 2010. "Inclusion of latent variables in Mixed Logit models: Modelling and forecasting," Transportation Research Part A: Policy and Practice, Elsevier, vol. 44(9), pages 744-753, November.
    4. Fredrik Johansson-Tormod & Anders Klevmarken, 2022. "Explaining the Size and Nature of Response in a Survey on Health Status and Economic Standard," International Journal of Microsimulation, International Microsimulation Association, vol. 15(1), pages 63-77.
    5. Dirk Temme & Marcel Paulssen & Till Dannewald, 2007. "Integrating latent variables in discrete choice models – How higher-order values and attitudes determine consumer choice," SFB 649 Discussion Papers SFB649DP2007-065, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    6. Berg, Lennart & Berger, Tommy, 2005. "The Q theory and the Swedish housing market –an empirical test," Working Paper Series 2005:19, Uppsala University, Department of Economics.
    7. Eva Heinen & Bert van Wee & Kees Maat, 2009. "Commuting by Bicycle: An Overview of the Literature," Transport Reviews, Taylor & Francis Journals, vol. 30(1), pages 59-96, June.
    8. Bühler, Georg & Hoffmann, Tim & Wölfing, Nikolas & Schmidt, Markus, 2009. "Wettbewerb und Umweltregulierung im Verkehr: Eine Analyse zur unterschiedlichen Einbindung der Verkehrsarten in den Emissionshandel," ZEW Expertises, ZEW - Leibniz Centre for European Economic Research, number 110505, September.

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    More about this item

    Keywords

    Modal choice; latent variable; discrete choice model; modal safety;
    All these keywords.

    JEL classification:

    • C35 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions
    • R41 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Transportation Economics - - - Transportation: Demand, Supply, and Congestion; Travel Time; Safety and Accidents; Transportation Noise

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