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The Educational Bias in Commuting Patterns: Micro-Evidence for the Netherlands

Author

Listed:
  • Stefan P.T. Groot

    (VU University Amsterdam)

  • Henri L.F. de Groot

    (VU University Amsterdam, and Ecorys NEI)

  • Paolo Veneri

    (OECD, Paris)

Abstract

This study analyses the relation between education and commuting behaviour of Dutch workers. Results show that, ceteris paribus, higher educated workers commute further, both in terms of distance and time. In addition, higher educated workers are more frequent users of public transport and of bicycles. Furthermore, we find that higher educated workers are relatively more likely to commute towards agglomerated areas and areas that pay relatively high wages, while they are more likely to live in and commute from areas with higher land rents.

Suggested Citation

  • Stefan P.T. Groot & Henri L.F. de Groot & Paolo Veneri, 2012. "The Educational Bias in Commuting Patterns: Micro-Evidence for the Netherlands," Tinbergen Institute Discussion Papers 12-080/3, Tinbergen Institute.
    • Handle: RePEc:tin:wpaper:20120080
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    References listed on IDEAS

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    Citations

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    Cited by:

    1. Sergejs Gubins & Jos Ommeren & Thomas Graaff, 2019. "Does new information technology change commuting behavior?," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 62(1), pages 187-210, February.
    2. J. Ignacio Gimenez-Nadal & José Alberto Molina, 2016. "Commuting Time And Household Responsibilities: Evidence Using Propensity Score Matching," Journal of Regional Science, Wiley Blackwell, vol. 56(2), pages 332-359, March.
    3. Chiara Castelli & Angela Parenti, 2020. "Commuting in Europe: An Inter-regional Analysis on its Determinants and Spatial Effects," Working Papers 2020.19, Fondazione Eni Enrico Mattei.
    4. Anette Haas & Malte Reichelt, 2014. "Would you commute further for extra money? Region specific income effects on commuting distances," ERSA conference papers ersa14p1320, European Regional Science Association.
    5. Reichelt, Malte & Haas, Anette, 2015. "Commuting farther and earning more? : how employment density moderates workers commuting distance," IAB-Discussion Paper 201533, Institut für Arbeitsmarkt- und Berufsforschung (IAB), Nürnberg [Institute for Employment Research, Nuremberg, Germany].
    6. Anette Haas & Malte Reichelt, 2015. "Larger pay, longer drives? Location specific wage effects on commuting distances," ERSA conference papers ersa15p1139, European Regional Science Association.
    7. Castelli, Chiara & Parenti, Angela, 2020. "Commuting in Europe: An Inter-regional Analysis on its Determinants and Spatial Effects," 2030 Agenda 307985, Fondazione Eni Enrico Mattei (FEEM).
    8. Moritz Kersting & Eike Matthies & Jörg Lahner & Jan Schlüter, 2021. "A socioeconomic analysis of commuting professionals," Transportation, Springer, vol. 48(5), pages 2127-2158, October.
    9. Verkade, Emiel & Bakens, Jessie, 2020. "Commuter flow predictions in POA: Evaluation study," ROA Technical Report 005, Maastricht University, Research Centre for Education and the Labour Market (ROA).

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    More about this item

    Keywords

    commuting; education; urban amenities; agglomeration;
    All these keywords.

    JEL classification:

    • R12 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General Regional Economics - - - Size and Spatial Distributions of Regional Economic Activity; Interregional Trade (economic geography)
    • R21 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Household Analysis - - - Housing Demand
    • R23 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Household Analysis - - - Regional Migration; Regional Labor Markets; Population

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