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Moravian Geographical Reports

The Journal of Institute of Geonics AS CR, v.v.i.

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

Lucas Martínez-Bernabeu / José Manuel Casado-Díaz
  • International Economics Institute and Department of Applied Economic Analysis, University of Alicante, Spain
  • Other articles by this author:
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Published Online: 2016-07-08 | DOI: https://doi.org/10.1515/mgr-2016-0008


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.

Keywords: labour market areas; census; microdata; regionalisation; clustering; evolutionary computation; Spain


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About the article

Received: 2015-09-30

Accepted: 2015-12-10

Published Online: 2016-07-08

Published in Print: 2016-06-01

Citation Information: Moravian Geographical Reports, Volume 24, Issue 2, Pages 26–36, ISSN (Online) 1210-8812, DOI: https://doi.org/10.1515/mgr-2016-0008.

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© 2016. This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License. BY-NC-ND 4.0

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