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Ecological Inference And Spatial Heterogeneity - A New Approach Based On Entropy Econometrics

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Author Info
Ludo Peeters ()
Coro Chasco-Yrigoyen ()

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Abstract

In this paper, we compare the results obtained by the application of three alternative methods of ecological inference. The data is on per capita household disposable income in the 50 provinces and 78 municipalities of Asturias, Spain. The first method is based on Ordinary Least Squares regression model, which assumes constancy or homogeneity. The second method is based on a spatial autocorrelation model, which assumes heterogeneity in two spatial regimes. The third method is based on a varying-coefficients model, which assumes total heterogeneity. The second model is estimated by Maximum Likelihood, whereas the latter is estimated by using Generalized Maximum or Cross Entropy.

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Paper provided by European Regional Science Association in its series ERSA conference papers with number ersa05p705.

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Date of creation: Aug 2005
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Handle: RePEc:wiw:wiwrsa:ersa05p705

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  1. George Judge & Douglas Miller & Wendy Cho, 2003. "An Information Theoretic Approach to Ecological Estimation and Inference," Department of Agricultural & Resource Economics, UC Berkeley, Working Paper Series 946, Department of Agricultural & Resource Economics, UC Berkeley. [Downloadable!]
  2. Bidani, Benu & Ravallion, Martin, 1997. "Decomposing social indicators using distributional data," Journal of Econometrics, Elsevier, vol. 77(1), pages 125-139, March. [Downloadable!] (restricted)
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  3. Swamy, P A V B & Tavlas, George S, 1995. " Random Coefficient Models: Theory and Applications," Journal of Economic Surveys, Blackwell Publishing, vol. 9(2), pages 165-96, June.
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