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The Primacy of Race in the Geography of Income-Based Voting

The forthcoming article “The Primacy of Race in the Geography of Income-Based Voting” by Eitan Hersh and  Clayton Nall is summarized by the authors here:

For decades, researchers have studied the relationship between income and voting, investigating where, why, and how much the rich and poor diverge from each other in their political preferences. In American politics, scholars such as Gelman et al (2008) and Alesina and Glaser (2004) have paid particular attention to how geography, and geographic context, shapes the relationship between income and mass politics. They have asked whether rich and poor voters have more divergent preferences in rich states or poor states, racially diverse states or racially homogenous states. Due to the limitations of survey samples, most research on income, voting, and geography has focused on variation across large-scale boundaries like states. However, at the scale of a state, it is difficult to disentangle explanations for the geographic variation in income-based voting. For instance, if the rich and poor have divergent preferences in a state that is both poor and racially diverse, is it more likely the economic context or racial context that contributes to the income-based stratification?

This question brought us into a partnership that connects Nall’s research agenda of political geography with Hersh’s research agenda of using granular public records to study politics.  In our article, we study sources of geographic variation at a much lower-level of geographic aggregation than previous studies. We employ 72 million individual-level party registration records and 185,000 precinct-level election returns. With these data sets, we assess factors that predict stronger or weaker income-based voting.  With an abundance of data, we estimate the relationship between income and partisanship in small geographies, like state house districts, mostly non-parametrically and with few modeling assumptions.

We discover several descriptive facts that have been obscured in prior research based either on county-level data alone, or on individual-level data analyzed at the state level:

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