(iPoster) Disaggregating Diversity: School Board Race-Gender Effects on Teacher Salaries

• In Event: Poster Sessions: Political Science Education & Race, Ethnicity, and Politics
  In Poster Session: Poster Session: Race, Ethnicity, and Politics

Abstract

A growing literature in political science and public policy examines whether descriptive representation among decision-makers influences policy outcomes. In the context of education governance, prior research links school board composition to spending priorities, labor relations, and student outcomes, but most studies rely on coarse measures such as female or minority representation. These aggregated measures may obscure important heterogeneity across demographic subgroups. In particular, the intersection of gender and ethnicity among governing board members remains underexplored, despite theoretical arguments that distinct lived experiences may shape preferences and decision-making. This study investigates whether differences in the race-gender composition of newly elected school board members are associated with later changes in teacher compensation.

Using data from the California Elections Data Archive and Ed-Data covering all California school board elections, we construct a district-year panel of California school districts from 2010 to 2024. Individual-level records of newly elected school board members were supplemented with probabilistic estimates of gender and ethnicity derived from name-based inference methods. Gender probabilities were generated for each individual, while ethnicity probabilities were estimated using a composite approach that integrated outputs from the wru_county, predictrace, and rethnicity packages, which leverage surname information and geographic context. These probabilities were aggregated to the district-year level to construct expected counts of board members by race-gender category (e.g., White male, Hispanic female, Asian female). To estimate the relationship between race-gender composition of newly elected school board members and teacher pay, we fit linear mixed-effects models with district random intercepts and year fixed effects, regressing next-year and following-year average teacher salaries on joint race-gender board composition. All specifications included an indicator for even-numbered years to account for election-cycle dynamics, which exhibited a strong and statistically significant association with salary outcomes. Alternative models using aggregated demographic measures and gender-ethnicity interaction terms were estimated as robustness checks.

We find a robust positive association between Hispanic female board representation and teacher salaries. A newly elected Hispanic female board member is associated with an approximately $913 increase in average teacher salaries two years following the election (p = 0.0003), relative to a newly elected white male board member. This relationship persists across alternative specifications, and interestingly, is not explained by overall female representation or Hispanic representation alone. However, lead-lag analyses indicate that similar associations appear prior to election years. This suggests the relationship is unlikely to be causal and may instead reflect pre-existing district-level trends correlated with the race-gender composition of newly elected school board members and compensation outcomes. Most other race-gender categories exhibit coefficients that are statistically indistinguishable from zero, suggesting either null effects or limited within-district variation.

These findings suggest that the relationship between descriptive representation and education policy outcomes is highly heterogeneous and driven by specific race-gender subgroups rather than by aggregate diversity measures. By combining election data with probabilistic demographic inference and modeling joint race-gender representation, this study provides a more nuanced account of how descriptive representation influences policy outcomes.

Authors

• Anya Dalal, Castilleja School

• Jacob Harris, The University of Alabama