Dr. Justin Esarey is an Associate Professor of Political Science at Rice University who specializes in political methodology. His areas of expertise include detecting and presenting context-specific relationships, model specification and sensitivity, the analysis of binary data, laboratory social experimentation, and promoting thoughtful inference (and thinking about inference) by using technology to make methodological resources available to the scholarly public. His substantive projects study the relationship between corruption and female participation in government, the effect of "naming and shaming" on human rights abuse, and the behavioral implications of political ideology.

Dr. Esarey is currently the editor of The Political Methodologist and the Principal Investigator of the International Methods Colloquium project.

Journal Articles

  1. Esarey, Justin. 2018. "What Makes Someone a Political Methodologist?" Conditionally accepted at PS: Political Science and Politics. [pdf] [replication file]
  2. Esarey, Justin, and Andrew R. Wood. 2017. "Blogs, Online Seminars, and Social Media as Tools of Scholarship in Political Science." PS: Political Science and Politics, forthcoming. [pdf] [replication file]

  3. Esarey, Justin and Andrew Menger. 2016. "Practical and Effective Approaches to Dealing with
    Clustered Data." Political Science Research and Methods, forthcoming. [pdf] [replication file]
  4. Esarey, Justin, and Jane Lawrence Sumner. 2017. "Marginal Effects in Interaction Models: Determining and Controlling the False Positive Rate." Comparative Political Studies (available on First View). [journal] [pdf] [replication file]

  5. Esarey, Justin, and Leslie Schwindt-Bayer. 2017. "Women’s Representation, Accountability, and Corruption in Democracies." British Journal of Political Science (available on first view). [journal] [pdf] [online appendix] [replication file
  6. Esarey, Justin. 2017. "Does Peer Review Identify the Best Papers? A Simulation Study of Editors, Reviewers, and the Scientific Publication Process." PS: Political Science and Politics 50(4): 963-969. [journal] [pdf] [replication file]

    This paper was profiled by Inside Higher Ed.

  7. Esarey, Justin, and Jacqueline H. R. Demeritt. 2017. "Political Context and the Consequences of Naming and Shaming for Human Rights Abuse." International Interactions 43(4): 589-618. [journal] [pdf] [replication file]
  8. Esarey, Justin, and Ahra Wu. 2016. "Measuring the Effects of Publication Bias in Political Science." Research and Politics 3(3): 1-9. [journal] [replication file] [coding sheets]
  9. Esarey, Justin. 2016. "Fractionally Integrated Data and the Autodistributed Lag Model: Results from a Simulation Study." Political Analysis 24(1): 42-49. [pdf] [journal] [replication file]
  10. Berry, William, Jacqueline H. R. Demeritt, and Justin Esarey. 2016. "Bias and Overconfidence in Parametric Models of Interactive Processes." American Journal of Political Science 60(2): 521-539. [pdf] [journal] [replication file]
  11. Esarey, Justin and Nathan Danneman. 2015. "A Quantitative Method for Substantive Robustness Assessment." Political Science Research and Methods 3(1): 95-111. [pdf] [journal] [replication file] [software]
  12. Esarey, Justin, and Jacqueline H. R. Demeritt. 2014. "Defining and Modeling State-Dependent Systems." Political Analysis 22(1): 66-85. [pdf] [journal] [replication file]
  13. Esarey, Justin, and Gina Chirillo. 2013. "'Fairer Sex' or Purity Myth? Corruption, Gender, and Institutional Context." Politics and Gender 9(4): 390-413. [pdf] [journal] [replication file] [unrounded tables]

    This paper was profiled by Reuters, Time, New York Magazine, Slate, The Guardian, WDET Radio, and in the Jezebel blog.

  14. Esarey, Justin, and Andrew Pierce. 2012. "Assessing Fit Quality and Testing for Misspecification in
    Binary Dependent Variable Models." Political Analysis 20(4): 480-500. [pdf] [journal] [software] [replication file]
  15. Esarey, Justin, Timothy C. Salmon, and Charles Barrilleaux. 2012. "Social Insurance and Income Redistribution in a Laboratory Experiment." Political Research Quarterly 65(3): 685-698. [journal] [supplement] [errata and alternative analysis] [replication file]
  16. Esarey, Justin, Timothy C. Salmon, and Charles Barrilleaux. 2012. "What Motivates Political Preferences? Self-Interest, Ideology, and Fairness in a Laboratory Democracy." Economic Inquiry 50(3): 604-624. [journal] [replication file]
  17. Berry, William, Jacqueline H. R. Demeritt, and Justin Esarey. 2010. "Testing for Interaction in Binary Logit and Probit Models: Is a Product Term Essential?" American Journal of Political Science 54(1):248-266. [journal] [replication file]
  18. Ahn, TK, Justin Esarey, and John Scholz. 2009. "Reputation and Cooperation in Voluntary Exchanges: Comparing Local and Central Institutions.” Journal of Politics 71(2): 398-413. [journal] [replication file]
  19. Ahn, TK, and Justin Esarey. 2008. "A Dynamic Model of Generalized Social Trust." Journal of Theoretical Politics 20: 151-180. [journal] [supplement]
  20. Esarey, Justin, Bumba Mukherjee, and Will H. Moore. 2008. "Strategic Interaction and Interstate Crises: A Bayesian Quantal Response Estimator for Incomplete Information Games." Political Analysis 16: 250-273. [journal] [replication file]

Book Chapters

  1. Schwindt-Bayer, Leslie, Justin Esarey, and Erika Schumacher. 2018. "Gender and Citizen Responses to Corruption among Politicians: The U.S. and Brazil.'' In Gender and Corruption: Historical Roots and New Avenues for Research, eds. Helena Stensota and Lena Wagnerud. London: Palgrave Macmillan. [pdf] [replication file]
  2. Esarey, Justin. 2017. "Causal Inference with Observational Data." Chapter 4 in Analytics, Policy, and Governance, eds. Jennifer Bachner, Kathryn Wagner Hill, and Benjamin Ginsberg. New Haven: Yale University Press. [pdf] [replication file] [amazon link]

Revise and Resubmit

  1. Esarey, Justin, and Leslie Schwindt-Bayer. "Estimating Causal Relationships Between Women's Representation in Government and Corruption." Invited to revise and resubmit to Comparative Political Studies. [pdf] [replication file]


  1. Justin Esarey (PI). National Science Foundation Grant #1423825: "An Online Methods Colloquium for Quantitative Methodology in Political Science." 2014-2017. $252,384.
  2. Justin Esarey (PI). Emory University Research Committee Grant: “A Formal Test of Substantive Significance.” $15,400.
  3. Charles Barrilleaux (PI), Tim Salmon and Justin Esarey (Co-PIs.) National Science Foundation Grant #0720055: "Explaining Preferences for Social Insurance and Redistribution in a Laboratory Democracy," 2007-2009. $108,000.


  1. clusterSEs package for R. Calculate p-values and confidence intervals using cluster-adjusted t-statistics (based on Ibragimov and Muller 2010, Journal of Business and Economic Statistics 28(4)), pairs cluster bootstrapped t-statistics, and wild cluster bootstrapped t-statistics (the latter two techniques based on Cameron, Gelbach, and Miller 2008, Review of Economics and Statistics 90(3)). Procedures are included for use with GLM, ivreg, plm (fixed effects), and mlogit models. URL:

  2. interactionTest package for R. Allows researchers to calculate t-statistics that properly control the false discovery rate or familywise error rate when constructing marginal effects plots for models with interaction terms (Esarey and Sumner 2017). Co-authored with Jane Lawrence Sumner. URL:

  3. Course Workload Estimator app in RShiny. Allows instructors and students to assess how many out-of-class hours of work per week that a syllabus requires based on research that studies reading and writing speeds. Co-authored with Elizabeth Barre. URL:

    This software won the 2017 POD innovation award of the Professional and Organizational Development Network in Higher Education.

    Usage statistics for the last month are available at (note: this tracks all hits to the server, but the Workload Estimator and the usage tracker are the only hosted sites).

  4. heatmapFit package for R. Generates a fit plot for diagnosing misspecification in models of binary dependent variables, and calculates the related heatmap fit statistic (Esarey and Pierce, 2012). Co-authored with Andrew Pierce and Jericho Du. URL:

  5. cstar package for R. Functions that allow a researcher to examine the robustness of the substantive significance of their findings. Implements ideas set out in Esarey and Danneman (2015). Co-authored with Nathan Danneman. URL:

Working Papers

  1. Esarey, Justin, and Jacob Jaffe. "A Direct Test for Consistency of Random Effects Models that Outperforms the Hausman Test." [pdf]
  2. Esarey, Justin, and Vera Liu. "A Prospective Test for Replicability and a Retrospective Analysis of Theoretical Prediction Strength in the Social Sciences." [poster] [replication file]   

[Back to Top]
(c) Justin Esarey and Elizabeth Barre