ESTIMATING THE PARTISAN CONSEQUENCES OF REDISTRICTING PLANS - SIMPLY

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 p air of OLS equations that regress voting percentages on major party re gistration percentages. I test this model on data for all California A ssembly and congressional elections from 1970 through 1994, and compar e it to more complicated equations that contain incumbency and socioec onomic 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, a nd Texas can also predict outcomes with considerable accuracy. Using t hese equations, I show that the so-called ''Burton Gerrymander'' of 19 80 had minimal partisan consequences, while the nonpartisan plan insti tuted by the California Supreme Court's Special Masters in 1992 was ne arly as biased in favor of the Republicans as the proposal of the Repu blican party. I also introduce a new graphic representation of redistr icting plans and conclude with a discussion of some seemingly methodol ogical choices that have important substantive implications for assess ing the fairness of redistricting plans.