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Detection of income effect in mode choice: Theory and application

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  • Jara-Díaz, Sergio R.
  • Videla, Jorge
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    Abstract

    Although income effect is likely to be present in mode choice for most of the population within the developing world, presently used approaches do not take it into account. In fact, the income variable that sometimes enters utility specifications has been justified as a proxy for other variables, which makes its role rather ambiguous. In this paper, the problem is restated from its microeconomic foundations, showing that the usual non-income-sensitive specifications can be interpreted as a particular case within a more general framework which provides the basis for a methodology to test the presence of income effect. The methodology, which does not require additional information besides the usual data collected for disaggregate models, is applied to trips to work originated in a middle-income corridor of Santiago, Chile. The results quantitatively confirm previous qualitative analysis, and show empirically the need to employ income-sensitive mode choice models.

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    Bibliographic Info

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

    Volume (Year): 23 (1989)
    Issue (Month): 6 (December)
    Pages: 393-400

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    Handle: RePEc:eee:transb:v:23:y:1989:i:6:p:393-400

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    Cited by:
    1. Espino, Raquel & Ortuzar, Juan de Dios & Roman, Concepcion, 2004. "Simulation Techniques to Obtain Confidence Intervals for Willingness to Pay Measures," Institute of Transportation Studies, Research Reports, Working Papers, Proceedings qt9543q88g, Institute of Transportation Studies, UC Berkeley.
    2. Eliasson, Jonas & Mattsson, Lars-Göran, 2000. "A model for integrated analysis of household location and travel choices," Transportation Research Part A: Policy and Practice, Elsevier, vol. 34(5), pages 375-394, June.
    3. Benjamin Kickhöfer & Dominik Grether & Kai Nagel, 2011. "Income-contingent user preferences in policy evaluation: application and discussion based on multi-agent transport simulations," Transportation, Springer, vol. 38(6), pages 849-870, November.
    4. Francisco Javier Amador & Rosa Marina González & Juan de Dios Ortúzar, 2004. "Preference heterogeneity and willingness to pay for travel time," Documentos de trabajo conjunto ULL-ULPGC 2004-12, Facultad de Ciencias Económicas de la ULPGC.
    5. Francisco Amador & Rosa González & Juan Dios Ortúzar, 2008. "On Confounding Preference Heterogeneity and Income Effect in Discrete Choice Models," Networks and Spatial Economics, Springer, vol. 8(2), pages 97-108, September.
    6. Amador, Francisco Javier & González, Rosa Marina & Ramos-Real, Francisco Javier, 2013. "Supplier choice and WTP for electricity attributes in an emerging market: The role of perceived past experience, environmental concern and energy saving behavior," Energy Economics, Elsevier, vol. 40(C), pages 953-966.
    7. Vredin Johansson, Maria & Heldt, Tobias & Johansson, Per, 2006. "The effects of attitudes and personality traits on mode choice," Transportation Research Part A: Policy and Practice, Elsevier, vol. 40(6), pages 507-525, July.
    8. Raquel Espino & Juan Ortúzar & Concepción Román, 2006. "Confidence Interval for Willingness to Pay Measures in Mode Choice Models," Networks and Spatial Economics, Springer, vol. 6(2), pages 81-96, June.
    9. Golub, Aaron David, 2003. "Welfare Analysis of Informal Transit Services in Brazil and the Effects of Regulation," Institute of Transportation Studies, Research Reports, Working Papers, Proceedings qt4z3826fg, Institute of Transportation Studies, UC Berkeley.
    10. Golub, Aaron David, 2003. "Welfare Analysis of Informal Transit Services in Brazil and the Effects of Regulation," University of California Transportation Center, Working Papers qt0pf40632, University of California Transportation Center.
    11. Espino, Raquel & de Dios Ortúzar, Juan & Román, Concepción, 2007. "Understanding suburban travel demand: Flexible modelling with revealed and stated choice data," Transportation Research Part A: Policy and Practice, Elsevier, vol. 41(10), pages 899-912, December.
    12. Batley, Richard & Nicolás Ibáñez, J., 2013. "On the path independence conditions for discrete-continuous demand," Journal of choice modelling, Elsevier, vol. 7(C), pages 13-23.
    13. Benjamin Bureau & Matthieu Glachant, 2008. "Distributional effects of road pricing: Assessment of nine scenarios for Paris," Post-Print hal-00437759, HAL.
    14. Paolo Delle Site & Marco Valerio Salucci, 2012. "The Impact Of The Before-After Error Term Correlation On Welfare Measurement In Logit," Working Papers 0412, CREI Università degli Studi Roma Tre, revised 2012.
    15. Elisabetta Cherchi & Juan Ortúzar, 2002. "Mixed RP/SP models incorporating interaction effects," Transportation, Springer, vol. 29(4), pages 371-395, November.
    16. 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.
    17. Madden, Gary G & Simpson, Michael & Savage, Scott, 2002. "Broadband delivered entertainment services: forecasting Australian subscription intentions," MPRA Paper 10915, University Library of Munich, Germany.
    18. Delle Site, Paolo & Salucci, Marco Valerio, 2013. "Transition choice probabilities and welfare analysis in random utility models with imperfect before–after correlation," Transportation Research Part B: Methodological, Elsevier, vol. 58(C), pages 215-242.
    19. Ginés Guirao & Rosa M. González Marrero & Nieves R. Pérez Marante, 1995. "Una aplicación de los modelos de elección discreta al transporte interinsular de pasajeros," Estudios de Economía Aplicada, Estudios de Economía Aplicada, vol. 4, pages 71-86, Diciembre.
    20. Truong, Truong P. & Hensher, David A., 2012. "Linking discrete choice to continuous demand within the framework of a computable general equilibrium model," Transportation Research Part B: Methodological, Elsevier, vol. 46(9), pages 1177-1201.

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