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Overlapping labour market areas based on link communities

Author

Listed:
  • Yicheol Han
  • Stephan J. Goetz

Abstract

Many urban areas around the world have expanded from monocentric to polycentric regions forming larger hierarchical structures. These regions represent functional regions or labour market areas (LMAs) that are classified as groups of counties representing mutually exclusive, non‐overlapping geographies. In practice, however, a county may belong to multiple overlapping LMAs. To model this overlapping across urban hierarchies, we extend the link community method from network theory and apply it to US commuting data. Our proposed approach reliably identifies the LMAs that we would expect to find as well as core and periphery areas within them. Muchas áreas urbanas de todo el mundo se han expandido, pasando de regiones monocéntricas a policéntricas y formando estructuras jerárquicas más grandes. Estas regiones representan regiones funcionales o áreas del mercado laboral (AML) que se clasifican como grupos de condados que representan geografías mutuamente excluyentes y no solapadas. En la práctica, sin embargo, un condado puede pertenecer a múltiples AML superpuestas. Para la modelización de esta superposición entre jerarquías urbanas se ha ampliado el método de comunidades de enlace a partir de la teoría de redes y se ha aplicado a datos de desplazamientos en los Estados Unidos. El enfoque propuesto identifica de manera fiable las AML que se esperaría encontrar, así como las áreas centrales y periféricas dentro de ellas. 世界中の多くの都市部の地域が、モノセントリックな地域構造から、より大きな階層構造を成すポリセントリックな構造へと拡大してきている。これらの地域は、相互排他的で重複のない地理構造を象徴する行政区 (county)のグループとして分類される、機能的地域または労働市場地域 (labour market area: LMA)となっている。しかしながら実際には、ひとつの行政区が複数の重複するLMAに属している可能性がある。本稿では、この都市部の階層間の重複をモデル化するため、ネットワーク理論からコミュニティをつなぐ方法を拡張して米国の通勤データに適用した。この我々の提案するアプローチは予想通りLMAを確実に認識し、さらにその内部の中心地域と周辺地域も認識した。

Suggested Citation

  • Yicheol Han & Stephan J. Goetz, 2019. "Overlapping labour market areas based on link communities," Papers in Regional Science, Wiley Blackwell, vol. 98(1), pages 539-553, February.
  • Handle: RePEc:bla:presci:v:98:y:2019:i:1:p:539-553
    DOI: 10.1111/pirs.12326
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    Cited by:

    1. Mark He & Joseph Glasser & Nathaniel Pritchard & Shankar Bhamidi & Nikhil Kaza, 2020. "Demarcating geographic regions using community detection in commuting networks with significant self-loops," PLOS ONE, Public Library of Science, vol. 15(4), pages 1-31, April.
    2. Nikhil Kaza & Katherine Nesse, 2021. "Characterizing the Regional Structure in the United States: A County-based Analysis of Labor Market Centrality," International Regional Science Review, , vol. 44(5), pages 560-581, September.

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