The Obama Effect? Race, First-time Voting, and Future Participation.
). Revise and Resubmit, Political Behavior
How Local Partisan Context Conditions Pro-social Behaviors: Mask-Wearing During COVID-19.
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.
(with Ryan Baxter-King, Ryan Enos, Arash Naeim, and Lynn Vavreck).
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 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.
Measuring and Modeling Neighborhoods. (with Cory McCartan and Kosuke Imai). (PolMeth Poster
With the availability of granular geographical data, social scientists are increasingly interested in examining how residential neighborhoods influence attitudes, behavior, politics, socio-economic outcomes, and psychological processes. To facilitate such studies, we develop an easy-to-use online survey instrument that allows respondents to draw their neighborhoods on a map. We then propose a statistical model that can be used to analyze how the characteristics of respondents, those of relevant local areas, and their interactions determine the formation of their neighborhoods. The model also can generate out-of-sample predictions of one's subjective neighborhood given these observed characteristics. We illustrate the proposed methodology by conducting a survey among registered voters in Miami, New York City, and Phoenix. We find that across these cities, voters are more likely to include same-race and co-partisan census blocks into their neighborhoods. We also show that our model provides more accurate out-of-sample predictions than the standard distance-based measures of neighborhoods. Open-source software is available for implementing the proposed methodology.
The Increase in Partisan Segregation in the United States and its Causes. (with Enrico Cantoni, Ryan Enos, Vincent Pons, and Emilie Sartre).
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 in 30 U.S states to construct two key indicators: i) The ratio of Democrats to Democrats and Republicans D/(D+R), which reveals that partisan segregation has increased across geographical units, at 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 further decompose the sources of changes in partisan segregation, calculating the extent to which changes are driven by voter mobility, new voters entering the electorate, and by voters changing their partisanship. The rise in partisan segregation appears mostly driven by generational change in Democrat areas and by the increasing ideological conformity of stayers in Republican areas.