Comment on “Estimating the Extent of Racially Polarized Voting in Multicandidate Contests†by Bernard Grofman and Michael Migalski

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.