Estimating Candidate Support in Voting Rights Act Cases: Comparing Iterative EI and EI-R×C Methods

Abstract

Scholars and legal practitioners of voting rights are concerned with estimating individual-level voting behavior from aggregate-level data. The most commonly used technique, King’s ecological inference (EI), has been questioned for inflexibility in multiethnic settings or with multiple candidates. One method for estimating vote support for multiple candidates in the same election is called ecological inference: row by columns (R×C). While some simulations suggest that R×C may produce more precise estimates than the iterative EI technique, there has not been a comprehensive side-by-side comparison of the two methods using real election data that analysts and legal practitioners often rely upon in courts. We fill this void by comparing iterative EI and R×C models with a new statistical package—eiCompare—in a variety of R×C combinations including 2 candidates and 2 groups, 3 candidates and 3 groups, and up to 12 candidates and three groups and multiple candidates and four groups. Additionally, we examine the two methods with 500 simulated data sets that differ in combinations of heterogeneity, polarization, and correlation. Finally, we introduce a new model congruence score to aid scholars and voting rights analysts in the substantive interpretation of the estimates. Across all of our analyses, we find that both methods produce substantively similar results. This suggests that iterative EI and R×C can be used interchangeably when assessing precinct-level voting patterns in Voting Rights Act cases and that neither method produces bias in favor or against finding racially polarized voting patterns.

The use of differential privacy for census data and its impact on redistricting: The case of the 2020 U.S. Census

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Asian American Candidate Preferences: Evidence from California

“…The main method of analysis for this project is using ecological inference (Barreto et al 2019;King 1997) to estimate national-origin voting among Asian Americans. Ecological inference is a method of inferring discrete individual behavior from aggregate group-level (ecological) data.…”

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Can States Promote Minority Representation? Assessing the Effects of the California Voting Rights Act

“…California is one of the most diverse states in the nation, and while Whites are relatively Democratic in cities like Los Angeles, San Francisco, San Jose, and Santa Cruz, Whites in many areas of the state (i.e., Orange County, Inland Empire, Central Valley, interior North) reflect similar outlooks and voting patterns as Whites in other states across the United States. In local elections though, even in cities like Los Angeles, racially polarized voting is apparent (Barreto et al 2019; Collingwood et al 2016). In assessing racially polarized voting in Los Angeles, for instance, Abosch, Barreto, and Woods (2007) show that percentage Hispanic at the precinct level correlates at over 0.7 with Latino/non-Latino support for Latino candidates.…”