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

Incorporating Spatial Structures in Ecological Inference: An Information Theory Approach

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Received: 30 August 2010; in revised form: 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.
Keywords: generalized cross entropy estimation; ecological inference; spatial heterogeneity
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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MDPI and ACS Style

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

AMA Style

Bernardini Papalia R. Incorporating Spatial Structures in Ecological Inference: An Information Theory Approach. Entropy. 2010; 12(10):2171-2185.

Chicago/Turabian Style

Bernardini Papalia, Rosa. 2010. "Incorporating Spatial Structures in Ecological Inference: An Information Theory Approach." Entropy 12, no. 10: 2171-2185.


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