Jonathan Mummolo

3.9k total citations · 4 hit papers
32 papers, 2.2k citations indexed

About

Jonathan Mummolo is a scholar working on Sociology and Political Science, Political Science and International Relations and Statistics and Probability. According to data from OpenAlex, Jonathan Mummolo has authored 32 papers receiving a total of 2.2k indexed citations (citations by other indexed papers that have themselves been cited), including 27 papers in Sociology and Political Science, 26 papers in Political Science and International Relations and 7 papers in Statistics and Probability. Recurrent topics in Jonathan Mummolo's work include Electoral Systems and Political Participation (18 papers), Crime Patterns and Interventions (10 papers) and Policing Practices and Perceptions (8 papers). Jonathan Mummolo is often cited by papers focused on Electoral Systems and Political Participation (18 papers), Crime Patterns and Interventions (10 papers) and Policing Practices and Perceptions (8 papers). Jonathan Mummolo collaborates with scholars based in United States, Canada and United Kingdom. Jonathan Mummolo's co-authors include Erik Peterson, Jens Hainmueller, Yiqing Xu, Dean Knox, Clayton Nall, Will Lowe, Bocar Ba, Roman Rivera, Marc Meredith and Eitan Hersh and has published in prestigious journals such as Science, Proceedings of the National Academy of Sciences and Journal of the American Statistical Association.

In The Last Decade

Jonathan Mummolo

32 papers receiving 2.1k citations

Hit Papers

How Much Should We Trust ... 2018 2026 2020 2023 2018 2018 2021 2020 200 400 600

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author Last Decade Papers Cites
Jonathan Mummolo 1.3k 1.1k 415 226 214 32 2.2k
Thomas B. Pepinsky 1.8k 1.4× 1.3k 1.2× 720 1.7× 147 0.7× 307 1.4× 109 3.4k
Yotam Margalit 1.4k 1.1× 1.6k 1.5× 481 1.2× 144 0.6× 256 1.2× 61 2.7k
Tom van der Meer 2.0k 1.6× 1.4k 1.3× 180 0.4× 138 0.6× 143 0.7× 78 2.9k
Tom W. Rice 887 0.7× 1.3k 1.2× 503 1.2× 216 1.0× 279 1.3× 72 2.3k
Bernadette C. Hayes 1.7k 1.3× 724 0.7× 524 1.3× 445 2.0× 153 0.7× 91 3.0k
Dominik Hangartner 2.8k 2.2× 1.2k 1.1× 610 1.5× 261 1.2× 105 0.5× 78 4.1k
Andrew C. Eggers 623 0.5× 817 0.8× 486 1.2× 251 1.1× 237 1.1× 42 1.7k
Suzanne Mettler 999 0.8× 1.8k 1.6× 505 1.2× 412 1.8× 208 1.0× 52 2.8k
Guy Grossman 1.1k 0.9× 656 0.6× 417 1.0× 139 0.6× 66 0.3× 56 1.9k
Thomas J. Leeper 1.9k 1.5× 1.4k 1.3× 284 0.7× 312 1.4× 154 0.7× 42 3.1k

Countries citing papers authored by Jonathan Mummolo

Since Specialization
Citations

This map shows the geographic impact of Jonathan Mummolo's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Jonathan Mummolo with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jonathan Mummolo more than expected).

Fields of papers citing papers by Jonathan Mummolo

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Jonathan Mummolo. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Jonathan Mummolo. The network helps show where Jonathan Mummolo may publish in the future.

Co-authorship network of co-authors of Jonathan Mummolo

This figure shows the co-authorship network connecting the top 25 collaborators of Jonathan Mummolo. A scholar is included among the top collaborators of Jonathan Mummolo based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Jonathan Mummolo. Jonathan Mummolo is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Ba, Bocar, Jacob Kaplan, Dean Knox, et al.. (2025). Political diversity in U.S. police agencies. American Journal of Political Science. 69(4). 1617–1635. 1 indexed citations
2.
Wright, Lauren, Jonathan Mummolo, & M. Jackson Marr. (2024). How Framing Gender Diversity in Government Affects Perceptions of Substantive Representation. The Journal of Politics. 88(1). 221–233. 1 indexed citations
3.
Knox, Dean, et al.. (2023). An Automated Approach to Causal Inference in Discrete Settings. Journal of the American Statistical Association. 119(547). 1–16. 8 indexed citations
4.
Mummolo, Jonathan, et al.. (2022). Which Police Departments Want Reform? Barriers to Evidence-Based Policymaking. Journal of Experimental Political Science. 10(3). 403–412. 2 indexed citations
5.
Ba, Bocar, Dean Knox, Jonathan Mummolo, & Roman Rivera. (2021). The role of officer race and gender in police-civilian interactions in Chicago. Science. 371(6530). 696–702. 165 indexed citations breakdown →
6.
Knox, Dean & Jonathan Mummolo. (2020). Toward a General Causal Framework for the Study of Racial Bias in Policing. 1(3). 341–378. 14 indexed citations
7.
Knox, Dean, Will Lowe, & Jonathan Mummolo. (2020). Can Racial Bias in Policing Be Credibly Estimated Using Data Contaminated by Post-Treatment Selection?. SSRN Electronic Journal. 2 indexed citations
8.
Knox, Dean, Will Lowe, & Jonathan Mummolo. (2020). Administrative Records Mask Racially Biased Policing. American Political Science Review. 114(3). 619–637. 157 indexed citations breakdown →
9.
Mummolo, Jonathan, et al.. (2019). Which Police Departments Want Reform? Bureaucratic Reputation and Aversion to Research Collaborations. SSRN Electronic Journal. 1 indexed citations
10.
Mummolo, Jonathan. (2018). Militarization fails to enhance police safety or reduce crime but may harm police reputation. Proceedings of the National Academy of Sciences. 115(37). 9181–9186. 120 indexed citations
11.
Mummolo, Jonathan & Erik Peterson. (2018). Improving the Interpretation of Fixed Effects Regression Results. Political Science Research and Methods. 6(4). 829–835. 209 indexed citations
12.
Mummolo, Jonathan & Erik Peterson. (2018). Demand Effects in Survey Experiments: An Empirical Assessment. American Political Science Review. 113(2). 517–529. 322 indexed citations breakdown →
13.
Grimmer, Justin, Eitan Hersh, Marc Meredith, Jonathan Mummolo, & Clayton Nall. (2018). Obstacles to Estimating Voter ID Laws’ Effect on Turnout. The Journal of Politics. 80(3). 1045–1051. 80 indexed citations
14.
Hopkins, Daniel J. & Jonathan Mummolo. (2017). Assessing the Breadth of Framing Effects. Quarterly Journal of Political Science. 12(1). 37–57. 22 indexed citations
15.
Mummolo, Jonathan. (2017). Modern Police Tactics, Police-Citizen Interactions, and the Prospects for Reform. The Journal of Politics. 80(1). 1–15. 105 indexed citations
16.
Hopkins, Daniel J. & Jonathan Mummolo. (2016). Assessing the Breadth of Framing Effects. SSRN Electronic Journal. 1 indexed citations
17.
Mummolo, Jonathan & Clayton Nall. (2016). Why Partisans Do Not Sort: The Constraints on Political Segregation. The Journal of Politics. 79(1). 45–59. 113 indexed citations
18.
Mummolo, Jonathan & Erik Peterson. (2016). How Content Preferences Limit the Reach of Voting Aids. American Politics Research. 45(2). 159–185. 15 indexed citations
19.
Bailey, Michael, Jonathan Mummolo, & Hans Noel. (2012). Tea Party Influence: A Story of Activists and Elites. SSRN Electronic Journal. 4 indexed citations
20.
Bailey, Michael, Jonathan Mummolo, & Hans Noel. (2012). Tea Party Influence. American Politics Research. 40(5). 769–804. 36 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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