Spatial Disaggregation of Social Indicators: An Info-Metrics Approach
Esteban Fernandez-Vazquez (),
Alberto Diaz Dapena,
Fernando Rubiera-Morollon and
Ana Viñuela
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Esteban Fernandez-Vazquez: REGIOlab: Regional Economics Laboratory at the University of Oviedo
Alberto Diaz Dapena: REGIOlab: Regional Economics Laboratory at the University of Oviedo
Fernando Rubiera-Morollon: REGIOlab: Regional Economics Laboratory at the University of Oviedo
Ana Viñuela: REGIOlab: Regional Economics Laboratory at the University of Oviedo
Authors registered in the RePEc Author Service: Fernando Rubiera Morollón
Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, 2020, vol. 152, issue 2, No 15, 809-821
Abstract:
Abstract In this paper we propose a methodology to obtain social indicators at a detailed spatial scale by combining the information contained in census and sample surveys. Similarly to previous proposals, the method proposed here estimates a model at the sample level to later project it to the census scale. The main novelties of the technique presented are that (i) the small-scale mapping produced is perfectly consistent with the aggregates -regional or national- observed in the sample, and (ii) it does not require imposing strong distributional assumptions. The methodology suggested here follows the basics presented on Golan (2018) by adapting a cross-moment constrained Generalized Maximum Entropy (GME) estimator to the spatial disaggregation problem. This procedure is compared with the equivalent methodology of Tarozzi and Deaton (2009) by means of numerical experiments, providing a comparatively better performance. Additionally, the practical implementation of the methodology proposed is illustrated by estimating poverty rates for small areas for the region of Andalusia (Spain).
Keywords: Small area estimation; Poverty mapping; Spatial disaggregation; Info-metrics and entropy (search for similar items in EconPapers)
Date: 2020
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Persistent link: https://EconPapers.repec.org/RePEc:spr:soinre:v:152:y:2020:i:2:d:10.1007_s11205-020-02455-z
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DOI: 10.1007/s11205-020-02455-z
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