A National Measure of School District Partisanship for the 2016 to 2024 Presidential Elections

Scholars increasingly interested in the governance of local school districts, which invites curiosity about the partisanship of their voting constituencies. Presently, researchers have to translate precinct-level or county-level votes to school district geographies using imprecise imputation strategies as the geographies are not coterminous. We review the recent methods researchers use to allocate votes to school districts for partisan proxy measurements and then propose a nationwide measure using ancillary land cover data. We provide a novel, nationwide database of vote counts and partisanship for the roughly 13,000 school districts for the 2016, 2020, and 2024 presidential elections via dasymetric interpolation, which allocates precinct votes to districts in proportion to developed land rather than geometric area. We illustrate common trends of interest to data users: within-state variation, partisanship change over time, and disaggregation on district locale. We then use our measure to replicate Hartney and Finger’s (2022) study exploring the relationship between district partisanship and pandemic school reopening, which assigns each district the vote share of its parent county. We compare our measure of votes against the county-level Ohio measure they assembled, finding closely similar distributions of school district partisanship. We improve both the sample size and interpretability of their study, finding that their headline Ohio result also holds nationally while illustrating that a national measure allows for broader generalizability and more precise estimates.