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.

Publications

The Obama Effect? Race, First-time Voting, and Future Participation. Accepted. Political Science Research and Methods. (Supporting Information; Replication Data).
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.

How Local Partisan Context Conditions Pro-social Behaviors: Mask-Wearing During COVID-19. 2022. (with Ryan Baxter-King, Ryan Enos, Arash Naeim, and Lynn Vavreck). Proceedings of the National Academy of Sciences.(Supporting Information; Replication Data; Cite).
Abstract Does local partisan context influence compliance with public health recommendations? Using a nationwide survey of 60,000 adults and geographic data on over 180 million registered voters, we investigate whether neighborhood partisan composition affects a publicly observable and politicized behavior: wearing a mask. We find that Republicans are less likely to comply with mask-wearing as the share of Republicans in their Zip Codes increases. Democratic mask-wearing, however, is unaffected by local partisan context. Consequentially, the partisan gap in mask-wearing is largest in Republican neighborhoods, and less apparent in Democratic areas. These effects are distinct from other contextual effects such as variations in neighborhood race, income, or education. Additionally, partisan context does not influence unobservable public health recommendations like COVID-19 vaccination, or non-politicized behaviors like flu vaccination, suggesting that mask-wearing reflects the publicly observable and politicized nature of the behavior instead of underlying differences in dispositions toward medical care.

Locked Out of College: When Admissions Bureaucrats Do and Do Not Discriminate. 2022. (with Hanno Hilbig). British Journal of Political Science. (Supporting Information; Replication Data; Cite).
Abstract How does an individual's criminal record shape interactions with the state and society? This article presents evidence from a nationwide field experiment in the United States, which shows that prospective applicants with criminal records are about 5 percentage points less likely to receive information from college admission offices. However, this bias does not extend to race: there is no difference in response rates to Black and White applicants. The authors further show that bias is all but absent in public bureaucracies, as discrimination against formerly incarcerated applicants is driven by private schools. Examining why bias is stronger for private colleges, the study demonstrates that the private–public difference persists even after accounting for college selectivity, socio-economic composition and school finances. Moving beyond the measurement of bias, an intervention designed to reduce discrimination is evaluated: whether an email from an advocate mitigates bias associated with a criminal record. No evidence is found that advocate endorsements decrease bureaucratic bias.

Resisting Broken Windows: The Effect of Neighborhood Disorder on Political Behavior. 2022. (with Michael Zoorob). Political Behavior. (Ungated; Supporting Information; Replication Data; Cite).
Abstract Concurrent housing and opioid crises have increased exposure to street-crime, homelessness and addiction in American cities. What are the political consequences of this increased neighborhood disorder? We examine a change in social context following the relocation of homelessness and drug treatment services in Boston. In 2014, an unexpected bridge closing forced nearly 1000 people receiving emergency shelter or addiction treatment to relocate from an island in the Boston Harbor to mainland Boston, causing sustained increases in drug-use, loitering, and other features of neighborhood disorder. Residents near the relocation facilities mobilized to maintain order in their community. In the subsequent Mayoral election, their turnout grew 9% points while participation in state and national elections was unchanged. However, increased turnout favored the incumbent Mayor, consistent with voter learning about candidate quality following local shocks. Voters responded to neighborhood changes at the relevant electoral scale and rewarded responsive politicians.

Childhood Cross-ethnic Exposure Predicts Political Behavior Seven Decades Later: Evidence from Linked Administrative Data. 2021. (with Ryan Enos, James Feigenbaum, and Shom Mazumder). Science Advances. (Supporting Information; Replication Data; Cite). [Covered by the Los Angeles Times, CNN, the Daily Mail, and the Harvard Gazette].
Abstract Does contact across social groups influence sociopolitical behavior? This question is among the most studied in the social sciences with deep implications for the harmony of diverse societies. Yet, despite a voluminous body of scholarship, evidence around this question is limited to cross-sectional surveys that only measure short-term consequences of contact or to panel surveys with small samples covering short time periods. Using advances in machine learning that enable large-scale linkages across datasets, we examine the long-term determinants of sociopolitical behavior through an unprecedented individual-level analysis linking contemporary political records to the 1940 U.S. Census. These linked data allow us to measure the exact residential context of nearly every person in the United States in 1940 and, for men, connect this with the political behavior of those still alive over 70 years later. We find that, among white Americans, early-life exposure to black neighbors predicts Democratic partisanship over 70 years later.

The Measurement of Partisan Sorting for 180 Million Voters. 2021. (with Ryan Enos). Nature Human Behaviour. (Supporting Information; Replication Data; Cite). [Covered by the New York Times, The Atlantic, Fast Company, The Harvard Gazette, The Harvard Crimson , The Academic Times, and the Raw Story We've Got Issues podcast].
Abstract Segregation across social groups is an enduring feature of nearly all human societies and is associated with numerous social maladies. In many countries, reports of growing geographic political polarization raise concerns about the stability of democratic governance. Here, using advances in spatial data computation, we measure individual partisan segregation by calculating the local residential segregation of every registered voter in the United States, creating a spatially weighted measure for more than 180 million individuals. With these data, we present evidence of extensive partisan segregation in the country. A large proportion of voters live with virtually no exposure to voters from the other party in their residential environment. Such high levels of partisan isolation can be found across a range of places and densities and are distinct from racial and ethnic segregation. Moreover, Democrats and Republicans living in the same city, or even the same neighbourhood, are segregated by party.

Weakening Strong Black Political Empowerment: Implications from Atlanta’s 2009 Mayoral Election. 2014. (with Michael Leo Owens). Journal of Urban Affairs, 36:4, 663-681. (Cite).
Abstract Atlanta is perhaps the city with the greatest degree of black political empowerment (BPE) in the United States. Yet in 2009 a relatively weak white mayoral candidate nearly won the general and runoff elections over a field of stronger black candidates. Why? Treating Atlanta as a prototypical case, the article examines factors that undermine the capacity of blacks to retain control of mayoralties in strong BPE cities, with an emphasis on disruptions to black electorates, discontent among black citizens, and reinvestment in electoral politics by whites at the local level.

Selected Working Papers

Partisan Conversion Through Neighborhood Influence: How Voters Adopt the Partisanship of their Neighbors. (Supporting Information). [Covered by the New York Times]. Under Review.
Abstract Recent studies show that American neighborhoods have become politically homogeneous, raising concerns about how geographic polarization divides parties and influences voters. But it remains unclear how voters are influenced by the politics of their neighbors. I argue that voters are influenced by local norms when defining their own partisan affiliations, adopting local partisanship. Panel data on 41 million voters from 2008-2020 and an original survey of 24,623 respondents demonstrate that exposure to partisan neighbors increases party switching. These effects are largest for older voters, voters in single-family communities, and voters with more same-race neighbors. Survey data support mechanisms of social influence: voters accurately perceive local partisanship, interact more with partisans they live near, and are more comfortable when their partisanship matches neighbors' political affiliations. Partisanship is thus shaped by where voters live and who they live close to, demonstrating the behavioral consequences of geographic polarization.

Partisan Segregation and Partisan Activation: How Geographic Polarization Increases Political Engagement.
Abstract Do voters participate more in politics when they live around neighbors who share their party? I argue that voters are more likely to be socialized into politics when they live near more co-partisans. Using administrative data on every registered voter across 30 U.S. states from 2012-2021 and an original survey of 45,139 voters, I measure the effect of partisan neighborhoods on voting and other political engagement. Focusing on voters who do not change residences between elections, I find that increased exposure to co-partisan neighbors makes voters more likely to turnout, volunteer for campaigns, attend protests, participate in local political meetings, and to publicly express their partisanship through lawn signs, clothing, or bumper stickers. Survey data further show that voters respond to in-group exposure by becoming more comfortable in their neighborhood and more likely to politically engage with neighbors, consistent with social influence driving participatory effects.

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). [Covered by the New York Times].
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

  • Where You Grow Up Shapes Your Political Behavior: Evidence from Childhood Moves. (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).
  • Forecasting Turnout. (with Stephen Ansolabehere, Kabir Khanna, Connor Phillips, and Charles Stewart).
  • Priming Bias Versus Post-Treatment Bias in Experimental Designs. (with Matthew Blackwell, Sophie Hill, Kosuke Imai, and Teppei Yamamoto).
  • Financial Stress, Social Networks, and Political Participation: Evidence from Social Security Benefit Cycles. (with Hunter Rendleman).
  • Strategic Party Registration in Primary Elections: Evidence from Voterfile Panel Data. (with Samuel Mitchell and Connor Phillips).

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.

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