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

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  • Ludo Peeters
  • Coro Chasco-Yrigoyen

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.

Suggested Citation

  • Ludo Peeters & Coro Chasco-Yrigoyen, 2005. "Ecological Inference And Spatial Heterogeneity - A New Approach Based On Entropy Econometrics," ERSA conference papers ersa05p705, European Regional Science Association.
    • Handle: RePEc:wiw:wiwrsa:ersa05p705
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    References listed on IDEAS

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    2. Judge, George G. & Miller, Douglas J. & Cho, Wendy K. T., 2003. "An Information Theoretic Approach to Ecological Estimation and Inference," Department of Agricultural & Resource Economics, UC Berkeley, Working Paper Series qt7h03r00q, Department of Agricultural & Resource Economics, UC Berkeley.
    3. Golan, Amos & Judge, George G. & Miller, Douglas, 1996. "Maximum Entropy Econometrics," Staff General Research Papers Archive 1488, Iowa State University, Department of Economics.
    4. Bidani, Benu & Ravallion, Martin, 1997. "Decomposing social indicators using distributional data," Journal of Econometrics, Elsevier, vol. 77(1), pages 125-139, March.
    5. Judge, George G. & Miller, Douglas James & Cho, Wendy K, 2003. "An information theoretic approach to ecological estimation and inference," CUDARE Working Paper Series 946, University of California at Berkeley, Department of Agricultural and Resource Economics and Policy.
    6. Ori Rosen & Wenxin Jiang & Gary King & Martin A. Tanner, 2001. "Bayesian and Frequentist Inference for Ecological Inference: The R×C Case," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 55(2), pages 134-156, July.
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