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Classifying small (TL3) regions based on metropolitan population, low density and remoteness

Author

Listed:
  • Milenko Fadic
  • José Enrique Garcilazo
  • Ana Moreno Monroy
  • Paolo Veneri

Abstract

This paper provides a method to classify TL3regions across OECD countries based on their level of access to metropolitan areas. TL3 regions are classified as ‘metropolitan’ if more than half of their population lives in one or more functional urban area (FUA) of at least 250 thousand inhabitants and as ‘non-metropolitan’ otherwise. The method sub-classifies metropolitan regions into ‘large metro’ or ‘metro’ regions based on the population size of the FUAs located within those regions. Non-metropolitan TL3 regions are sub-classified into: with accessto a metro, with access to a small/medium city, or remote based on their level of access to a FUA with population above a predetermined threshold. The method relies on publicly available grid-level population data and localised information on driving conditions.

Suggested Citation

  • Milenko Fadic & José Enrique Garcilazo & Ana Moreno Monroy & Paolo Veneri, 2019. "Classifying small (TL3) regions based on metropolitan population, low density and remoteness," OECD Regional Development Working Papers 2019/06, OECD Publishing.
    • Handle: RePEc:oec:govaab:2019/06-en
    DOI: 10.1787/b902cc00-en
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    Cited by:

    1. Marcos Díaz Ramírez & Paolo Veneri & Alexander C. Lembcke, 2022. "Where did it hit harder? Understanding the geography of excess mortality during the COVID‐19 pandemic," Journal of Regional Science, Wiley Blackwell, vol. 62(3), pages 889-908, June.
    2. Eugenio Cejudo García & José Antonio Cañete Pérez & Francisco Navarro Valverde & Noelia Ruiz Moya, 2020. "Entrepreneurs and Territorial Diversity: Success and Failure in Andalusia 2007–2015," Land, MDPI, vol. 9(8), pages 1-19, August.
    3. Eugenio Cejudo-García & Francisco Navarro-Valverde & José Antonio Cañete-Pérez, 2022. "Who Decides and Who Invests? The Role of the Public, Private and Third Sectors in Rural Development according to Geographical Contexts: The LEADER Approach in Andalusia, 2007–2015," Sustainability, MDPI, vol. 14(7), pages 1-20, March.
    4. A.C. Pinate & A. Faggian & M.G. Brandano, 2023. "The impact of COVID-19 on the tourism sector in Italy: a regional spatial perspective," Working Paper CRENoS 202309, Centre for North South Economic Research, University of Cagliari and Sassari, Sardinia.
    5. Martin Thomas Falk & Eva Hagsten & Xiang Lin, 2022. "Domestic tourism demand in the North and the South of Europe in the Covid-19 summer of 2020," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 69(2), pages 537-553, October.

    More about this item

    Keywords

    culture; Indigenous peoples; place; regional and rural development; sustainable development goals; well-being;
    All these keywords.

    JEL classification:

    • C80 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - General
    • R41 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Transportation Economics - - - Transportation: Demand, Supply, and Congestion; Travel Time; Safety and Accidents; Transportation Noise
    • 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

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