Jacob R. Brown

Jacob R. Brown

Postdoctoral Fellow, Princeton University (2022-2023)

To be Assistant Professor of Political Science, Boston University (2023-)

Jacob R. Brown

I am a political scientist studying political behavior in American politics, with particular interest in how geography and group identity structure political behavior. My work investigates the behavioral consequences of geographic partisan polarization: how living in increasingly homogeneous partisan environments influences voters’ political affiliations, attitudes, and civic engagement. To this end, I develop data on the partisan residential exposure of every voter in the United States over the past decade, leveraging precise information on each voter's residential location, partisan affiliation, and political behavior. With these data I present new evidence on the extent and causes of partisan sorting in the United States and test new theories of how where Democrats and Republicans live in relation to one another influences political behavior.

Selected Working Papers

Partisan Conversion Through Neighborhood Influence: How Voters Adopt the Partisanship of their Neighbors and Reinforce Geographic Polarization. (Supporting Information). Revise and Resubmit, American Political Science Review. [Covered by the New York Times].
Abstract Recent studies show that American neighborhoods have become politically homogeneous, raising concerns about how geographic polarization divides parties and influences voters. I argue that voters are influenced by the politics of the people they live near when determining their own partisan registration, adopting the partisanship of their neighbors. Panel data on over 41 million voters from 2008-2020 and an original survey of 24,623 respondents demonstrate that exposure to partisan neighbors increases the likelihood of switching registration to match local partisanship. Neighbor effects represent large increases over baseline probabilities of switching parties and are a small contributing factor to increasing geographic polarization. Survey data support mechanisms of social influence: voters accurately perceive local partisanship, interact more with partisans they live near, are more comfortable when their partisanship matches neighbors' political affiliations. Partisanship is thus shaped by where voters live, and this conversion reinforces ongoing political segregation.

The Obama Effect? Race, First-time Voting, and Future Participation. (Supporting Information). Under Review.
Abstract Did the 2008 United States election produce stronger future mobilization for Blacks than non-Blacks? First-time voting influences long-term political behavior, but do minority voters see the most powerful effects when the formative election is tied to their group’s political empowerment? I test this hypothesis in the context of the election of the first Black president in United States history, using voting eligibility discontinuities to identify the effect of voting in 2008 on future voting for Blacks, Hispanics, and Whites. Voting in 2008 caused a greater increase in the likelihood of voting in 2010 for Blacks than for other new voters, but there is no evidence of a sustained mobilizing advantage in subsequent elections. Furthermore, 2008 was not a unique formative voting experience for new Black voters, but rather produced similar effects on future voting as other presidential elections. These results signal that group political empowerment does not influence the effect of first-time voting experiences on future political participation.

Measuring and Modeling Neighborhoods. (with Cory McCartan and Kosuke Imai). (Survey tool). Under Review.
Abstract The availability of granular geographic data presents new opportunities to understand how neighborhoods are formed and how they influence attitudes and behavior. To facilitate such studies, we develop an online survey instrument for respondents to draw their neighborhoods on a map. We then propose a statistical model to analyze how the characteristics of respondents and geography, and their interactions, predict subjective neighborhoods. We illustrate the proposed methodology using a survey of 2,572 voters in Miami, New York City, and Phoenix. Holding other factors constant, White respondents tend to include census blocks with more White residents in their neighborhoods. Similarly, Democratic and Republican respondents are more likely to include co-partisan census blocks. Our model also provides more accurate out-of-sample predictions than standard distance-based neighborhood measures. Lastly, we use these methodological tools to test how demographic information shapes neighborhoods, but find limited effects from this experimental manipulation. Open-source software is available for implementing the methodology.

The Increase in Partisan Segregation in the United States and its Causes. (with Enrico Cantoni, Ryan Enos, Vincent Pons, and Emilie Sartre).
Abstract This paper provides novel evidence on trends in geographic partisan segregation. Using two individual-level panel datasets covering the near universe of the U.S. population between 2008 and 2020, we leverage information on individuals’ party affiliation to construct two key indicators: i) the fraction of Democrats among voters affiliated with either major party, which reveals that partisan segregation has increased across geographical units, at the tract, county, and congressional district levels; ii) The dissimilarity index, which measures differences in the partisan mix across distinct sub-units and highlights that partisan segregation has also increased within geographical units. Tracking individuals across election years, we decompose changes in partisan segregation into different sources: voter migration, generational change, older voters entering the electorate, and voters changing their partisanship or their registration status. The rise in partisan segregation is mostly driven by generational change, in Democratic-leaning areas, and by the increasing ideological conformity of stayers, in Republican-leaning areas.

Works in Progress

  • Partisan Segregation and Partisan Activation: How Geographic Polarization Increases Political Engagement.
  • How Neighborhoods Shape Political Identity and Voting Behavior: Evidence from Young Movers. (with Enrico Cantoni, Sahil Chinoy, Martin Koenen, and Vincent Pons).
  • Norms of Intolerance: How Partisan Animosity Spreads in Social Relations. (with Sun Young Park).
  • Using Public Camera Feeds to Study Social Distancing and Pro-Health Behaviors in a Pandemic. (with Soubhik Barari, Bryce Dietrich, Ryan Enos, and Melissa Sands).
  • Modeling Turnout. (with Stephen Ansolabehere, Kabir Khanna, and Charles Stewart).
  • Priming Bias Versus Post-Treatment Bias in Experimental Designs. (with Matthew Blackwell, Sophie Hill, Kosuke Imai, and Teppei Yamamoto).

Ongoing Data Collection

  • Started in 2020, the Political Geography Panel Survey is a nationwide annual survey collecting repeated measures of political attitudes that can be connected to changes in geographic context. A feature of this survey is that responses are linked to voterfile data with exact residential address information, allowing for precise tests of the relationship between geography and public opinion. Survey questions cover voters' perceptions of their neighborhoods and residential areas, partisan and racial attitudes, political engagement, and opinions about national and local issues. The survey is run in collaboration with Ryan Enos.

  • The Senior Citizen Survey and Census Linkage Project is a survey targetting voters who were alive in the 1940s and 1950s, collecting contemporary survey data that can be linked to 1940 and 1950 Census data. The central aim of this project is to connect early life experiences to later-in-life political opinions, building off previous work connecting childhood cross-ethnic exposure to downstream partisanship. The survey further collects respondent reflections on over 80 years of American history, offering a unique perspective from a generation of voters that grew up in the wake of World War II and came of age in the 1960s and 1970s. This project is run in collaboration with Ryan Enos, James Feigenbaum, Shom Mazumder, and Dominic Valentino.
  • Other Writing