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Are functional regions more homogeneous than administrative regions? A test using hierarchical linear models

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  • Alexandra Wicht
  • Per Kropp
  • Barbara Schwengler

Abstract

We investigate whether economic functional regions capture spatial clustering of core economic indicators better than administrative regions. For this purpose, we use hierarchical linear models to measure the degree of homogenization of different regional delineations. Our results for Germany show that economic functional regions tend to capture spatial clustering better than administrative ones. However, a considerable amount of clustering at a lower aggregation level cannot be accounted for by economic functional regions, especially around metropolitan centres. Furthermore, economic functional regions, which depict commuting interrelations well, are less able to capture spatial homogenization than other economic functional delineations. El artículo investiga si las regiones económicas funcionales capturan la agrupación espacial de los indicadores económicos básicos mejor que las regiones administrativas. Para ello utiliza modelos lineales jerárquicos, con el fin de medir el grado de homogeneización de las diferentes delimitaciones regionales. Los resultados para Alemania muestran que las regiones económicas funcionales tienden a capturar mejor la agrupación espacial que las administrativas. Sin embargo, las regiones económicas funcionales, especialmente aquellas alrededor de los centros metropolitanos, no pueden explicar una cantidad considerable de agrupaciones a un nivel de agregación inferior. Además, las regiones económicas funcionales, que representan bien las interrelaciones de desplazamiento al trabajo, capturan peor la homogeneización espacial que otras delimitaciones económicas funcionales. 本稿では、経済的機能区域が、行政区域よりもコア経済指標の空間的クラスタリングをよく捉えるかどうか検討する。そこで、階層的線形モデルを使用し、異なる区域の均質化の程度を測定する。ドイツの結果は、経済的機能区域は、行政区域よりもコア経済指標の空間的クラスタリングをよく捉えることを示す。しかし、低い集積レベルでは多数のクラスタリングがあるが、経済的機能区域、特に大都市中心部の周辺には重要ではない。さらに、経済的機能区域は、通勤の相関性を描出するが、他の経済的機能区域よりも空間的均質化を捉える性能が低い。

Suggested Citation

  • Alexandra Wicht & Per Kropp & Barbara Schwengler, 2020. "Are functional regions more homogeneous than administrative regions? A test using hierarchical linear models," Papers in Regional Science, Wiley Blackwell, vol. 99(1), pages 135-164, February.
  • Handle: RePEc:bla:presci:v:99:y:2020:i:1:p:135-164
    DOI: 10.1111/pirs.12471
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    Cited by:

    1. Ulrike Unterhofer & Conny Wunsch, 2022. "Macroeconomic Effects of Active Labour Market Policies: A Novel Instrumental Variables Approach," Papers 2211.12437, arXiv.org.
    2. Lucas Martínez‐Bernabéu & José Manuel Casado‐Díaz, 2021. "Standard modularity is unsuitable for functional regionalization of spatial interaction data," Papers in Regional Science, Wiley Blackwell, vol. 100(5), pages 1323-1330, October.
    3. Yuanting Ma & Yong Sun & Futian Weng & Yan Xu, 2023. "An Identification of Industrial Functional Zones Based on NLP: Evidence From Online Commercial Registration Data," SAGE Open, , vol. 13(1), pages 21582440231, February.
    4. Stephan Brunow & Ramona Jost, 2023. "Being a long distance out-commuter or home employee in a rather peripheral region evidence of a German federal state," Review of Regional Research: Jahrbuch für Regionalwissenschaft, Springer;Gesellschaft für Regionalforschung (GfR), vol. 43(2), pages 317-342, August.
    5. Lucas Martínez-Bernabéu & José Manuel Casado-Díaz, 2022. "Automatic delimitation of labour market areas based on multi-criteria optimisation: The case of Spain 2011," Environment and Planning B, , vol. 49(2), pages 654-670, February.
    6. Viviana Carriel & Marcelo Lufin & Manuel Pérez-Trujillo, 2022. "Do workers negative self-select when they commute? Evidence for the Chilean case of long-distance commuting," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 69(1), pages 255-279, August.

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