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Institutional Fragmentation and Urbanisation in the EU Cities

Author

Listed:
  • Federica Cappelli

    (Roma Tre University)

  • Gianni Guastella

    (Università Cattolica del Sacro Cuore and Fondazione Eni Enrico Mattei)

  • Stefano Pareglio

    (Università Cattolica del Sacro Cuore and Fondazione Eni Enrico Mattei)

Abstract

This article examines the relationship between institutional fragmentation and the spatial extent of cities in Europe’s Functional Urban Areas. European Union planning regulations vary across member states, but in most cases, local authorities determine land use within the more general regulatory frameworks set by national or subnational authorities. More decentralised and fragmented settings may favour urban sprawl, allowing developers to avoid land-use restrictions in one municipality by moving to adjacent ones and providing incentives for municipalities to adopt less strict land-conversion regulations to attract households and workers. The empirical results fully support this hypothesis and unveil significant differences between small and large cities, the effect of governance fragmentation being a substantial factor in the latter case.

Suggested Citation

  • Federica Cappelli & Gianni Guastella & Stefano Pareglio, 2020. "Institutional Fragmentation and Urbanisation in the EU Cities," Working Papers 2020.08, Fondazione Eni Enrico Mattei.
    • Handle: RePEc:fem:femwpa:2020.08
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    References listed on IDEAS

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    More about this item

    Keywords

    Urban Sprawl; Institutional Fragmentation; Threshold Regression;
    All these keywords.

    JEL classification:

    • R52 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Regional Government Analysis - - - Land Use and Other Regulations
    • R58 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Regional Government Analysis - - - Regional Development Planning and Policy
    • C24 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Truncated and Censored Models; Switching Regression Models; Threshold Regression Models

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