Estimating the Partisan Consequences of Redistricting Plans -- Simply

Abstract

Although some judges and political scientists have recently questioned the idea that it is possible to predict the partisan consequences of redistricting plans, I demonstrate that it is simple to do so with a pair of OLS equations that regress voting percentages on major party registration percentages. I test this model on data for all California Assembly and congressional elections from 1970 through 1994, and compare it to more complicated equations that contain incumbency and socioeconomic variables. The simplest equations correctly predict nearly 90% of the results. I show that analogous equations using registration or votes for minor or even major offices in California, North Carolina, and Texas can also predict outcomes with considerable accuracy. Using these equations, I show that the so-called "Burton Gerrymander" of 1980 had minimal partisan consequences, while the nonpartisan plan instituted by the California Supreme Court's Special Masters in 1992 was nearly as biased in favor of the Republicans as the proposal of the Republican party. I also introduce a new graphic representation of redistricting plans and conclude with a discussion of some seemingly methodological choices that have important substantive implications for assessing the fairness of redistricting plans.