A Computational Approach to Measuring Vote Elasticity and Competitiveness

Abstract

The recent wave of attention to partisan gerrymandering has come with a push to refine or replace the laws that govern political redistricting around the country. A common element in several states' reform efforts has been the inclusion of competitiveness metrics, or scores that evaluate a districting plan based on the extent to which district-level outcomes are in play or are likely to be closely contested.In this paper, we examine several classes of competitiveness metrics motivated by recent reform proposals and then evaluate their potential outcomes across large ensembles of districting plans at the Congressional and state Senate levels. This is part of a growing literature using MCMC techniques from applied statistics to situate plans and criteria in the context of valid redistricting alternatives. Our empirical analysis focuses on five states-Utah, Georgia, Wisconsin, Virginia, and Massachusetts-chosen to represent a range of partisan attributes. We highlight situation-specific difficulties in creating good competitiveness metrics and show that optimizing competitiveness can produce unintended consequences on other partisan metrics. These results demonstrate the importance of (1) avoiding writing detailed metric constraints into long-lasting constitutional reform and (2) carrying out careful mathematical modeling on real geo-electoral data in each redistricting cycle.

Colorado in Context: Congressional Redistricting and Competing Fairness Criteria in Colorado

“…Recall that for purposes of our analysis, we have defined a district to be competitive with respect to a particular election if the Democratic vote share for that district (ignoring votes for minor parties) is between 45% and 55%. These margins are certainly somewhat arbitrary, and in light of the results of [13], we advise caution in the interpretation of these results. In particular, as we shall see below, a significant change in the overall partisan outcome (for instance, a "wave year" for one party or the other) can completely change the characterization of a district as competitive or not by this measure.…”

“…We note that[13] also examines Colorado's current legal definition of competitiveness, that is, "having a reasonable potential for the party affiliation of the district's representative to change at least once between federal decennial censuses"[5] using probability, and finds that a literal reading of this law might be that "any district in which both parties have at least a 13% projected chance of winning might match the Colorado law, since (1 − 0.13) 5 ≈ 0.5"[13].…”

“…• Competitiveness We adopt the "vote-band" method of measuring competitiveness [13], in which a district is considered competitive if Democrats and Republicans both receive 45% to 55% of the combined Democratic and Republican votes (votes for candidates of other parties are not considered). This was the definition of competitiveness adopted by Carerra in 2011 [24], though other definitions based on voter registration (not historical voting data) were considered by Commissioner Loevy and by the Colorado State Supreme Court in their 2012 ruling on the Colorado Congressional redistricting [24,21].…”

“…Competitiveness of districts is widely regarded as desirable, but the notion of "competitiveness" is not so easy to quantify. A variety of competitiveness metrics were explored in [13], and the analysis given there shows that there may be situation-specific difficulties with creating good competitiveness metrics, and that optimizing competitiveness metrics may produce unintended consequences. Recall that for purposes of our analysis, we have defined a district to be competitive with respect to a particular election if the Democratic vote share for that district (ignoring votes for minor parties) is between 45% and 55%.…”