Delineating zones to increase geographical detail in individual response data files: An application to the Spanish 2011 Census of population

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Título: Delineating zones to increase geographical detail in individual response data files: An application to the Spanish 2011 Census of population
Autor/es: Martínez Bernabeu, Lucas | Casado-Díaz, José M.
Grupo/s de investigación o GITE: Territorio y Movilidad. Mercados de Trabajo y Vivienda
Centro, Departamento o Servicio: Universidad de Alicante. Departamento de Análisis Económico Aplicado | Universidad de Alicante. Instituto Interuniversitario de Economía Internacional
Palabras clave: Labour market areas | Census | Microdata | Regionalisation | Clustering | Evolutionary computation | Spain | Regional science | Regional economics
Área/s de conocimiento: Economía Aplicada
Fecha de publicación: 8-jul-2016
Editor: De Gruyter
Cita bibliográfica: Moravian Geographical Reports. 2016, 24(2): 26-36. doi:10.1515/mgr-2016-0008
Resumen: Due to confidentiality considerations, the microdata available from the 2011 Spanish Census have been codified at a provincial (NUTS 3) level except when the municipal (LAU 2) population exceeds 20,000 inhabitants (a requirement that is met by less than 5% of all municipalities). For the remainder of the municipalities within a given province, information is only provided for their classification in wide population intervals. These limitations, hampering territorially-focused socio-economic analyses, and more specifically, those related to the labour market, are observed in many other countries. This article proposes and demonstrates an automatic procedure aimed at delineating a set of areas that meet such population requirements and that may be used to re-codify the geographic reference in these cases, thereby increasing the territorial detail at which individual information is available. The method aggregates municipalities into clusters based on the optimisation of a relevant objective function subject to a number of statistical constraints, and is implemented using evolutionary computation techniques. Clusters are defined to fit outer boundaries at the level of labour market areas.
Patrocinador/es: This work was supported by the Spanish Ministry of Economy and Competitiveness (grant number CSO2014-55780-C3-2-P, National R&D&i Plan 2013-2016).
URI: http://hdl.handle.net/10045/56685
ISSN: 1210-8812 | 2199-6202 (Online)
DOI: 10.1515/mgr-2016-0008
Idioma: eng
Tipo: info:eu-repo/semantics/article
Derechos: This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License
Revisión científica: si
Versión del editor: http://dx.doi.org/10.1515/mgr-2016-0008
Aparece en las colecciones:INV - TEYMO - Artículos de Revistas / Journal Articles

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