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Commuting Time and Accessibility in a Joint Residential Location, Workplace, and Job Type Choice Model

Author

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  • Ignacio A. Inoa

    (THEMA - Théorie économique, modélisation et applications - UCP - Université de Cergy Pontoise - Université Paris-Seine - CNRS - Centre National de la Recherche Scientifique)

  • Nathalie Picard

    (THEMA - Théorie économique, modélisation et applications - UCP - Université de Cergy Pontoise - Université Paris-Seine - CNRS - Centre National de la Recherche Scientifique)

  • André de Palma

    (ENS Cachan - École normale supérieure - Cachan)

Abstract

The effect of an individual-specific measure of accessibility to jobs is analyzed using a three-level nested logit model of residential location, workplace, and job type choice. This measure takes into account the attractiveness of different job types when the workplace choice is anticipated in the residential location decision. The model allows for variation in the preferences for job types across individuals and accounts for individual heterogeneity of preferences at each choice level in the following dimensions: education, age, gender and children. Using data from the Greater Paris Area, estimation results indicate that the individual-specific accessibility measure is an important determinant of the residential location choice and its effect differ along the life cycle. Results also show that the job type attractiveness measure is a more significant predictor of workplace location than the standard measures.

Suggested Citation

  • Ignacio A. Inoa & Nathalie Picard & André de Palma, 2013. "Commuting Time and Accessibility in a Joint Residential Location, Workplace, and Job Type Choice Model," Working Papers hal-00776945, HAL.
    • Handle: RePEc:hal:wpaper:hal-00776945
    Note: View the original document on HAL open archive server: https://hal.science/hal-00776945
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    References listed on IDEAS

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    Cited by:

    1. André de Palma & Nathalie Picard & Robin Lindsey, 2024. "Activity and transportation decisions within households," Chapters, in: Stephane Hess & Andrew Daly (ed.), Handbook of Choice Modelling, chapter 16, pages 426-451, Edward Elgar Publishing.
    2. André de Palma & Nathalie Picard & Ignacio Inoa, 2014. "Discrete choice decision-making with multiple decision-makers within the household," Chapters, in: Stephane Hess & Andrew Daly (ed.), Handbook of Choice Modelling, chapter 16, pages 363-382, Edward Elgar Publishing.

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    More about this item

    Keywords

    residential location; job location; accessibility; nested logit; Greater Paris;
    All these keywords.

    JEL classification:

    • R21 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Household Analysis - - - Housing Demand
    • C35 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions
    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation

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