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Entropy 2010, 12(10), 2171-2185; doi:10.3390/e12102171

Incorporating Spatial Structures in Ecological Inference: An Information Theory Approach

Department of Statistics, University of Bologna, Via Belle Arti 41, Bologna, Italy
Received: 30 August 2010 / Revised: 12 October 2010 / Accepted: 12 October 2010 / Published: 14 October 2010
(This article belongs to the Special Issue Advances in Information Theory)
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Abstract

This paper introduces an Information Theory-based method for modeling economic aggregates and estimating their sub-group (sub-area) decomposition when no individual or sub-group data are available. This method offers a flexible framework for modeling the underlying variation in sub-group indicators, by addressing the spatial dependency problem. A basic ecological inference problem, which allows for spatial heterogeneity and dependence, is presented with the aim of first estimating the model at the aggregate level, and then of employing the estimated coefficients to obtain the sub-group level indicators. View Full-Text
Keywords: generalized cross entropy estimation; ecological inference; spatial heterogeneity generalized cross entropy estimation; ecological inference; spatial heterogeneity
This is an open access article distributed under the Creative Commons Attribution License (CC BY 3.0).

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Bernardini Papalia, R. Incorporating Spatial Structures in Ecological Inference: An Information Theory Approach. Entropy 2010, 12, 2171-2185.

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