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.
| 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) |
Past Recipients
| 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 |