Earlier drafts of this article were presented at the 2000 Annual Meeting of the American Political Science Association and at the 2002 Summer Meeting of the Society for Political Methodology. The authors thank Christopher Adolph, Wendy Tam Cho, Walter Mebane, Jr., Jasjeet Sekhon and four anonymous reviewers for comments and thank Barry Burden and David Kimball for data. In addition, Shotts thanks the Center for the Study of Democratic Politics at Princeton University for generously supporting him as a visiting research scholar.
Logical Inconsistency in EI-Based Second-Stage Regressions
Article first published online: 12 DEC 2003
American Journal of Political Science
Volume 48, Issue 1, pages 172–183, January 2004
How to Cite
Herron, M. C. and Shotts, K. W. (2004), Logical Inconsistency in EI-Based Second-Stage Regressions. American Journal of Political Science, 48: 172–183. doi: 10.1111/j.0092-5853.2004.00063.x
- Issue published online: 12 DEC 2003
- Article first published online: 12 DEC 2003
The statistical procedure EI–R, in which point estimates produced by the King (1997) ecological inference technique are used as dependent variables in a linear regression, can be logically inconsistent insofar as the assumptions necessary to support EI–R's first stage (ecological inference via King's technique) can be incompatible with the assumptions supporting its second stage (linear regression). In light of this problem, we develop a specification test for logical consistency of EI–R and describe options available to a researcher who confronts test rejection. We then apply our test to the implementation of EI–R in Burden and Kimball's (1998) study of ticket splitting and find that this implementation is logically inconsistent. In correcting for this problem we show that Burden and Kimball's substantive results are artifacts of a self-contradictory statistical technique.