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An Information Theoretic Approach to Ecological Inference in Presence of Spatial Dependence

In: Defining the Spatial Scale in Modern Regional Analysis

Author

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  • Rosa Bernardini-Papalia

    (University of Bologna, Italy)

Abstract

This chapter introduces an Information Theory (IT)-based method for modeling economic aggregates and for obtaining estimates for small area (sub-group) or subpopulations when no sample units or limited data are available. The proposed approach offers a tractable framework for modeling the underlying variation in small area indicators, in particular when data set contains outliers and in presence of collinearity among regressors since the maximum entropy estimates are robust with respect to the outliers and also less sensitive to a high condition number of the design matrix. A basic ecological inference problem which allows for spatial heterogeneity and dependence is presented with the aim of estimating small area/sub-group indicators by combining all available information at both macro and micro data level.

Suggested Citation

  • Rosa Bernardini-Papalia, 2012. "An Information Theoretic Approach to Ecological Inference in Presence of Spatial Dependence," Advances in Spatial Science, in: Esteban Fernández Vázquez & Fernando Rubiera Morollón (ed.), Defining the Spatial Scale in Modern Regional Analysis, edition 127, chapter 0, pages 157-171, Springer.
    • Handle: RePEc:spr:adspcp:978-3-642-31994-5_8
    DOI: 10.1007/978-3-642-31994-5_8
    as

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