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
Dr. Esarey is currently the editor of
and the Principal Investigator of the
Methods Colloquium project.
- Esarey, Justin. 2018. "What Makes Someone
a Political Methodologist?" Conditionally accepted at PS: Political Science and Politics. [pdf]
- 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]
- Esarey, Justin and Andrew Menger.
2016. "Practical and Effective Approaches to Dealing with
Clustered Data." Political Science
Research and Methods, forthcoming. [pdf] [replication file]
Justin, and Jane Lawrence Sumner. 2017. "Marginal Effects in
Models: Determining and Controlling the False Positive Rate." Comparative Political Studies (available on First View). [journal] [pdf] [replication
- 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]
- 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]
- 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]
- Esarey, Justin, and Ahra Wu. 2016.
"Measuring the Effects of Publication Bias in Political Science."
Research and Politics 3(3): 1-9.
- Esarey, Justin. 2016. "Fractionally
Integrated Data and the Autodistributed Lag Model: Results from a
Simulation Study." Political Analysis 24(1):
42-49. [pdf] [journal]
- Berry, William, Jacqueline H. R.
and Justin Esarey. 2016. "Bias and Overconfidence in Parametric Models
of Interactive Processes." American
Journal of Political Science
60(2): 521-539. [pdf] [journal]
- Esarey, Justin and Nathan Danneman.
2015. "A Quantitative Method for Substantive Robustness
Science Research and Methods 3(1): 95-111. [pdf] [journal]
- Esarey, Justin, and Jacqueline H.
R. Demeritt. 2014. "Defining and Modeling State-Dependent Systems." Political Analysis
- Esarey, Justin, and Gina Chirillo.
2013. "'Fairer Sex' or Purity Myth? Corruption, Gender, and
Politics and Gender
9(4): 390-413. [pdf] [journal]
- 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]
Justin, Timothy C. Salmon, and Charles Barrilleaux. 2012. "Social
and Income Redistribution in a Laboratory Experiment." Political
Research Quarterly 65(3): 685-698. [journal]
[supplement] [errata and alternative analysis]
Justin, Timothy C. Salmon, and Charles Barrilleaux. 2012. "What
Political Preferences? Self-Interest, Ideology, and Fairness in a
Laboratory Democracy." Economic
Inquiry 50(3): 604-624. [journal]
- Berry, William, Jacqueline
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]
TK, Justin Esarey, and John Scholz. 2009. "Reputation and Cooperation
Voluntary Exchanges: Comparing Local and Central Institutions.” Journal of Politics
71(2): 398-413. [journal] [replication file]
- Ahn, TK, and Justin Esarey. 2008.
Dynamic Model of Generalized Social Trust." Journal of
Theoretical Politics 20: 151-180. [journal]
- Esarey, Justin, Bumba Mukherjee,
Will H. Moore. 2008. "Strategic Interaction and Interstate Crises: A
Bayesian Quantal Response Estimator for Incomplete Information Games." Political
Analysis 16: 250-273. [journal]
- 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
- 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]
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
- Justin Esarey (PI). National
Science Foundation Grant #1423825: "An Online Methods Colloquium for
Quantitative Methodology in Political Science." 2014-2017. $252,384.
- Justin Esarey (PI). Emory
Research Committee Grant: “A Formal Test of Substantive Significance.”
- Charles Barrilleaux (PI), Tim
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.
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:
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: https://goo.gl/8DGTjb.
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.
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 https://shiny.justinesarey.com (note: this tracks all hits to the server, but the Workload Estimator and the usage tracker are the only hosted sites).
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:
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:
- Esarey, Justin, and Jacob Jaffe. "A
Direct Test for Consistency of Random Effects Models that Outperforms
the Hausman Test." [pdf]
Justin, and Vera Liu. "A Prospective Test for Replicability and a
Retrospective Analysis of Theoretical Prediction Strength in the Social