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Spatial Effects and Ecological Inference

Published online by Cambridge University Press:  04 January 2017

Luc Anselin  and
Wendy K. Tam Cho
Luc Anselin
Affiliation:
Regional Economics Applications Laboratory and Departments of Agricultural and Consumer Economics, Economics, and Geography, University of Illinois at Urbana-Champaign, 1301 Gregory Drive, Urbana, IL 61801. e-mail: anselin@uiuc.edu
Wendy K. Tam Cho
Affiliation:
Departments of Political Science and Statistics, University of Illinois at Urbana—Champaign, 361 Lincoln Hall, 702 South Wright Street, Urbana, IL 61801. e-mail: wendy@cho.pol.uiuc.edu
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Abstract

This paper examines the role of spatial effects in ecological inference. Both formally and through simulation experiments, we consider the problems associated with ecological inference and cross-level inference methods in the presence of increasing degrees of spatial autocorrelation. Past assessments of spatial autocorrelation in aggregate data analysis focused on unidimensional, one-directional processes that are not representative of the full complexities caused by spatial autocorrelation. Our analysis is more complete and representative of true forms of spatial autocorrelation and pays particular attention to the specification of spatial autocorrelation in models with random coefficient variation. Our assessment focuses on the effects of this specification on the bias and precision of parameter estimates.

Type
Research Article
Information
Political Analysis , Volume 10 , Issue 3: Special Issue on Spatial Methods in Political Science , Summer 2002 , pp. 276 - 297
Copyright
Copyright © Political Methodology Section of the American Political Science Association 2002 

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References

Achen, Christopher H., and Phillips Shively, W. 1995. Cross-Level Inference. Chicago: University of Chicago Press.Google Scholar
Anselin, Luc. 1988. Spatial Econometrics: Methods and Models. Boston: Kluwer Academic.Google Scholar
Anselin, Luc. 1990. “Spatial Dependence and Spatial Structural Instability in Applied Regression Analysis.” Journal of Regional Science 30:185–207.Google Scholar
Anselin, Luc. 1992. “Spatial Dependence and Spatial Heterogeneity: Model Specification Issues in the Spatial Expansion Paradigm.” In Applications of the Expansion Method, eds. Jones, J. P. and Casetti, E. London: Routledge, pp. 334–354.Google Scholar
Anselin, Luc. 1995. “Local Indicators of Spatial Association—LISA.” Geographical Analysis 27:93–115.Google Scholar
Anselin, Luc. 2000. “The Alchemy of Statistics, or Creating Data Where No Data Exist.” Annals of the Association of American Geographers 90:93–115.Google Scholar
Anselin, Luc, and Bera, A. 1998. “Spatial Dependence in Linear Regression Models with an Introduction to Spatial Econometrics.” In Handbook of Applied Economic Statistics, eds. Ullah, A. and Giles, D. New York: Marcel Dekker, pp. 237–289.Google Scholar
Ansolabehere, Stephen, and Rivers, Douglas. 1997. “Bias in Ecological Regression Estimates.” Working paper.Google Scholar
Casetti, Emilio. 1997. “The Expansion Method, Mathematical Modeling, and Spatial Econometrics.” International Regional Science Review 20:9–33.Google Scholar
Cho, Wendy K. Tam. 1998. “Iff the Assumption Fits …: A Comment on the King Ecological Inference Solution.” Political Analysis 7:143–163.Google Scholar
Tam, Cho, Wendy K. 2001. “Latent Groups and Cross-Level Inferences.” Electoral Studies 20:243–263.Google Scholar
Cliff, A., and Ord, K. 1981. Spatial Processes: Models and Applications. London: Pion.Google Scholar
Fotheringham, A. Stewart, Brundson, Chris, and Martin, Charlton. 1998. “Geographically Weighted Regression: A Natural Evolution of the Expansion Method for Spatial Data Analysis.” Environment and Planning A 30:1905–1927.Google Scholar
Freedman, D.A., Klein, S. P., Ostland, M., and Roberts, M. R. 1998. Book review of “A Solution to the Ecological Inference Problem.” Journal of the American Statistical Association 93:1518–1522.Google Scholar
Goodman, Leo A. 1953. “Ecological Regressions and Behavior of Individuals.” American Sociological Review 18:663–664.Google Scholar
Goodman, Leo A. 1959. “Some Alternatives to Ecological Correlation.” American Journal of Sociology 64:610–625.Google Scholar
Griffiths, William E. 1972. “Estimation of Actual Response Coefficients in the Hildreth-Houck Random Coefficient Model.” Journal of the American Statistical Association 68:329–335.Google Scholar
Griffiths, William E., Drynan, Ross G., and Prakash, Surekha. 1979. “Bayesian Estimation of a Random Coefficient Model.” Journal of Econometrics 10:201–220.Google Scholar
King, Gary. 1997. A Solution to the Ecological Inference Problem: Reconstructing Individual Behavior from Aggregate Data. Princeton, NJ: Princeton University Press.Google Scholar
King, Gary. 2000. “Geography, Statistics, and Ecological Inference.” Annals of the Association of American Geographers 90:601–606.Google Scholar
Lancaster, Tony. 2000. “The Incidental Parameter Problem Since 1948.” Journal of Econometrics 95:391–413.Google Scholar
Neyman, Jerzy, and Scott, Elizabeth L. 1948. “Consistent Estimation from Partially Consistent Observations.” Econometrica 16:1–32.Google Scholar
O'Loughlin, John. 2000. “Extending King's Ecological Inference Approach to Answer a Social Science Puzzle: Who Voted for the Nazi Party in Weimar Germany?” Annals of the Association of American Geographers 90:592–601.Google Scholar
Openshaw, Stan, and Taylor, Peter. 1979. “A Million or so Correlation Coefficients: Three Experiments on the Modifiable Areal Unit Problem.” In Statistical Applications in the Spatial Sciences, ed. Wrigley, N. London: Pion, pp. 127–144.Google Scholar
Robinson, W. S. 1950. “Ecological Correlations and the Behavior of Individuals.” American Sociological Review 15:351–357.Google Scholar