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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.

Information

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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