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

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

Open Access
|Jul 2016

Abstract

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.

DOI: https://doi.org/10.1515/mgr-2016-0008 | Journal eISSN: 2199-6202 | Journal ISSN: 1210-8812
Language: English
Page range: 26 - 36
Submitted on: Sep 30, 2015
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Accepted on: Dec 10, 2015
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Published on: Jul 8, 2016
In partnership with: Paradigm Publishing Services
Publication frequency: 4 issues per year

© 2016 Lucas Martínez-Bernabeu, José Manuel Casado-Díaz, published by Czech Academy of Sciences, Institute of Geonics
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.