The John T. Williams Dissertation Prize

In recognition of John T. Williams’ contribution to graduate training, the John T. Williams Award has been established for the best dissertation proposal in the area of political methodology.

Past Recipients

2022 Winner
Recipient Melody Huang (Berkeley)
Work “Three Essays on Causal Inference under Interference and Hypothesis Testing in Random Experiments”
Citation This year's Williams Dissertation Prize is awarded to Melody Huang, Ph.d. candidate at the University of California, Berkeley, for her work on the credibility and generalizability of causal inference, more specifically, for her development of a new sensitivity analysis framework for weighted estimators in the generalizability setting. Unlike other frameworks, in Huang's set up the weights account for the confounding effect of sampling, not treatment. In addition, in her framework the parameters are guaranteed to be bounded across finite ranges. Hence there is no need to impose parametric assumptions on the outcome and selection models. Huang produces three sensitivity tools for generalizing experimental results: bias contour plots, a robustness value, and a benchmark that allows researchers to use observed covariates to estimate parameter values for the confounder. Her work potentially will strengthen our inferences about the effects of voter mobilization efforts and of other important public policies.
Selection committee John Freeman (chair, Minnesota), Yamil Velez (Columbia), Erin Hartman (Berkeley), Walter Mebane (Michigan), and In Song Kim  (MIT)
2020 Winner
Recipient Ye Wang (NYU)
Work “Three Essays on Causal Inference under Interference and Hypothesis Testing in Random Experiments”
Citation The William Prize Committee is delighted to announce that the John T. Williams Dissertation Prize, 2020 was awarded to Ye Wang's dissertation proposal “Three Essays on Causal Inference under Interference and Hypothesis Testing in Random Experiments.” Wang makes two major methodological innovations. First, he develops a methodological framework to identify causal relationships in time-series cross-sectional data under arbitrary within-unit (temporal) and between-unit (spatial) interference. Wang shows, under the sequential ignorability assumption, how one can obtain unbiased/consistent estimates of cumulative causal effects via inverse probability of treatment weighting (IPTW) estimators. More specifically, the proposed estimator identifies the expected average treatment effect generated by any particular treatment history of a representative unit on itself or on its neighbors. He demonstrates the usefulness of his innovation in a simulation and in a re-analysis of a published study of the impacts of a political reform in New York, accounting for temporal and spatial interference. He then applies this methodology to gauge the effect of protests in a handful of constituencies during the Umbrella Movement on electoral support for the opposition in Hong Kong. The second methodological contribution of Wang’s dissertation is to develop tools for testing nonlinear moderating effects in experiments. He adapts the evolutionary tree algorithm and sample splitting design to experimental analysis; the algorithm enables researchers to find the optimal partition of the moderator’s support on the training set for any loss function. He conducts a simulation study as well as a pilot study of the effects of a get-out-the-vote (GOTV) experiment, providing a promising direction for applying machine learning algorithms to experimental settings.
Selection committee John Freeman (chair, Minnesota), Walter Mebane (Michigan), and In Song Kim  (MIT)
Year Recipient Work
2019 Naijia Liu (Princeton) "Essays on Model Selection and Honest Inference"
2018 Kevin McAlister (University of Michigan) "Roll Call Scaling in the U.S. Congress: Addressing the Deficiencies"
2017 Naoki Egami (Princeton)  
2016 Dean Knox (MIT) "Essays on Modeling and Causal Inference in Network Data"
2015 Drew Dimmery (NYU) "Essays on Machine Learning and Causal Inference with Application to Nonprofits"
2014 Yiqing Xu (MIT) "Causal Inference with Time-Series Cross-Section Data with Applications to Chinese Political Economy"
2013 Scott Cook (University of Pittsburgh) The Contagion of Crises: Estimating Models of Endogenous and Interdependent Rare Events
2012 Adriana Crespo-Tenorio (Washington University in St. Louis) Three Papers on the Political Consequences of Oil Price Volatility
2011 Matthew Blackwell (Harvard) Essays in Political Methodology and American Politics
2010 Teppei Yamamoto (Princeton) Essays on Quantitative Methodology for Political Science
2009 Xun Pang (Washington University in St. Louis) A Bayesian Probit Hierarchical Model with AR(p) Errors and Non-nested Clustering: Studying Sovereign Creditworthiness and Political Institutions
2008 Justin Grimmer (Harvard) A Bayesian Hierarchical Topic Model for Political Texts: Measuring and Explaining Legislator's Express Agenda
2007 Arthur Spirling (University of Rochester) Bringing Intuition to Fruition: 'Turning Points' and 'Power' in Political Methodology
2006 Roman Ivanchenko (Ohio State) Interactions Between the Supreme-Court and Congress: A Different Look at the Decision-Making Process

Past Selection Committees

Year Committee
2019 Xun Pang (Tsinghua University), Dean Knox (Princeton, recused) and Yiqing Xu (University of California, San Diego)
2018 Xun Pang (Tsinghua, chair), Arthur Spirling (NYU), and Yiqing Xu (UCSD)
2017 Xun Pang (Tsinghua, chair), Arthur Spirling (NYU), and Yiqing Xu (UCSD)
2016 Justin Grimmer (Chicago, chair), Matt Blackwell (Harvard) and Teppi Yamamoto (MIT)
2015 Curt Signorino (Chair), John Ahlquist, Jennifer Jerit
2014 Curt Signorino (Chair), John Ahlquist, Jennifer Jerit
2013 Michael Colaresi (Chair), Guy Whitten, Irfan Nooruddin
2012 Michael Colaresi (Chair), Guy Whitten, Irfan Nooruddin
2011 Guy Whitten (Chair), Michael Colaresi, Jonathan Nagler
2010 Guy Whitten (Chair), Michael Colaresi, Jonathan Nagler
2009 Guy Whitten (Chair), Michael Colaresi, Betsy Sinclair
2007 John Aldrich (Chair), Michael Colaresi, Tse-Min Lin
2006 John Aldrich (Co-Chair), Virginia Gray (Co-Chair), Patrick Brandt, Burt Monroe