Why Partisans Do Not Sort: The Constraints on Political Segregation
Abstract
Social divisions between American partisans are growing, with Republicans and Democrats exhibiting homophily in a range of seemingly nonpolitical domains. It has been widely claimed that this partisan social divide extends to Americans’ decisions about where to live. In two original survey experiments, we confirm that Democrats are, in fact, more likely than Republicans to prefer living in more Democratic, dense, and racially diverse places. However, improving on previous studies, we test respondents’ stated preferences against their actual moving behavior. While partisans differ in their residential preferences, on average they are not migrating to more politically distinct communities. Using zip-code-level census and partisanship data on the places where respondents live, we provide one explanation for this contradiction: by prioritizing common concerns when deciding where to live, Americans forgo the opportunity to move to more politically compatible communities.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
People are not moving for political reasons, largely because nonpolitical factors such as the quality of public schools dominate the decisions of Democrats and Republicans alike.
“mobility data suggest that people are not moving for political reasons, largely because nonpolitical factors-such as the quality of the public schools-dominate the decisions of Democrats and Republicans alike.”
From The Origins and Consequences of Affective Polarization in the United States (2019) · cites this paper as Mummolo & Nall (2017)
Revealed preferences concerning place of residence diverge from stated preferences.
“Mummolo & Nall (2017) show that revealed preferences concerning place of residence diverge from stated preferences.”
From The Origins and Consequences of Affective Polarization in the United States (2019) · cites this paper as Mummolo & Nall (2017)
The ideological homogeneity of social networks is enhanced by structural dynamics such as geographic sorting, the growing politicization of the rural-urban divide, and 'lifestyle' differences that are correlated with political orientation.
“The ideological homogeneity of social networks is enhanced by structural dynamics such as geographic sorting209–211, the growing politicization of the rural–urban divide212,213, and ‘lifestyle’ differences that are correlated with political orientation107,214–216”
From Cognitive–motivational mechanisms of political polarization in social-communicative contexts (2022) · cites this paper as [210]
The citation lists haven’t been fetched yet
References 59 · Cited by 269
- Authors
- Mummolo, J., & Nall, C.
- Affiliations
- Stanford University (US)
- Venue
- The Journal of Politics
- Publisher
- University of Chicago Press
- Published
- 2017-01
- Volume
- 79
- Issue
- 1
- Pages
- 45-59
- ISSN
- 0022-3816 (ISSN-L)
- 1468-2508
- OpenAlex
- W2531419399
- Cited by
- 269
- References
- 59
- Citations by year
- 2026: 30 · 2025: 38 · 2024: 19 · 2023: 28 · 2022: 44 · 2021: 21 · 2020: 42 · 2019: 17 · 2018: 26 · 2017: 4
- FWCI
- 79.27
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- The Journal of Politics (publishedVersion)
- Topics
- Social Sciences › Political Science and International Relations › Electoral Systems and Political Participation
- Social Sciences › Sociology and Political Science › Urban, Neighborhood, and Segregation Studies
- Social Sciences › Communication › Social Media and Politics
- Keywords
- partisanship, residential segregation, partisan sorting, housing preferences, political homophily, racial diversity, urban density
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review