Double regression figures prominently in the analysis of racially polarized voting. Grofman and Migalski attempt three extensions of this technique: the application to multimember districts, the calculation of standard errors for the parameters of interest, and validation through comparisons with seemingly unrelated regression (SUR). All three extensions fail. The first is based on an arithmetical error. The second is based on an incomplete specification of the underlying statistical model. The third is based on a mistaken application of SUR in a context in which it is guaranteed to yield the same results as the ordinary least squares estimates of double regression.
Get full access to this article
View all access options for this article.
References
1.
Grofman, Bernard
. 1993. “The Use of Ecological Regression to Estimate Racial Bloc Voting.”University of San Francisco Law Review27:593-626.
2.
Grofman, Bernard
and Michael Migalski. 1988. “Estimating the Extent of Racially Polarized Voting in Multicandidate Contests.”Sociological Methods & Research16:427-453.
3.
King, Gary
. 1997. A Solution to the Ecological Inference Problem: Reconstructing Individual Behavior From Aggregate Data. Princeton, NJ: Princeton University Press.
4.
Lichtman, Allan J.1991. “Passing the Test: Ecological Regression Analysis in the Los Angeles County Case and Beyond.”Evaluation Review15:770-799.
5.
McCullough, B. D.
and H. D. Vinod. 1999. “The Numerical Reliability of Econometric Software.”Journal of Economic Literature37:633-665.
6.
Theil, Henri
. 1971. Principles of Econometrics. Santa Barbara, CA: Wiley.
