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Political Analysis, 10:3
© 2002 by the Society for Political Methodology

Spatial Effects and Ecological Inference

Luc Anselin and Wendy K. Tam Cho

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{at}uiuc.edu
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{at}cho.pol.uiuc.edu

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.


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