Automatic delimitation of labour market areas based on multi-criteria optimisation: The case of Spain 2011

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Title: Automatic delimitation of labour market areas based on multi-criteria optimisation: The case of Spain 2011
Authors: Martínez Bernabeu, Lucas | Casado-Díaz, José M.
Research Group/s: Territorio y Movilidad. Mercados de Trabajo y Vivienda
Center, Department or Service: Universidad de Alicante. Departamento de Análisis Económico Aplicado | Universidad de Alicante. Instituto Interuniversitario de Economía Internacional
Keywords: Functional region | Commuting region | Labour market areas | Local optimisation | Constrained optimisation
Knowledge Area: Economía Aplicada
Issue Date: 4-Jun-2021
Publisher: SAGE Publications
Citation: Environment and Planning B: Urban Analytics and City Science. 2022, 49(2): 654-670. https://doi.org/10.1177/23998083211021104
Abstract: Labour market areas (LMAs) are a type of functional region (FR) defined on commuting flows and used in many countries to serve as the territorial reference for regional studies and policy making at local levels. Existing methods rely on manual adjustments of the results to ensure high quality, making them difficult to be monitored, hard to apply to different territories, and onerous to produce in terms of required work-hours. We propose an approach to automatise all stages of the delineation procedure and improve the final results, building upon a state-of-the-art stochastic search procedure that ensures optimal allocation of municipalities/counties to LMAs while keeping good global indicators: a pre-processing layer clusters adjoining municipalities with strong commuting flows to constrain the initial search space of the stochastic search, and a multi-criteria heuristic corrects common deficiencies that derive from global maximisation approaches or simple greedy heuristics. It produces high quality LMAs with optimal local characteristics. To demonstrate this methodology and assess the improvement achieved, we apply it to define LMAs in Spain based on the latest commuting data.
Sponsor: This work was funded by the Spanish Ministry of Science, Innovation and Universities / Agencia Estatal de Investigación (AEI), and the EU ERDF, grant number CSO2017-86474-R.
URI: http://hdl.handle.net/10045/115558
ISSN: 2399-8083 (Print) | 2399-8091 (Online)
DOI: 10.1177/23998083211021104
Language: eng
Type: info:eu-repo/semantics/article
Rights: © The Author(s) 2021
Peer Review: si
Publisher version: https://doi.org/10.1177/23998083211021104
Appears in Collections:INV - TEYMO - Artículos de Revistas / Journal Articles

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