Tamar Zeilberger
Postdoctoral Fellow in Political Science and Public Policy, London School of Economics and Political Science (LSE)
Houghton Street, London WC2A 2AE, United Kingdom
About
I am a postdoctoral fellow in political science and public policy at the London School of Economics and Political Science (LSE). My research focuses on comparative authoritarian politics, political economy, and the case of contemporary China; and primarily uses some combination of formal modeling and inference from observational data with statistics and machine learning. My recent work centers on uncertainty and domestic instability, respectively, and devises new methodological approaches for studying the former. My substantive and methodological interests are mutually reinforcing, and motivated by policy-relevant questions in authoritarian settings that cannot be examined with traditional randomized experiments.
I received my PhD in political science from the University of California, Los Angeles in 2023. Previously, I obtained an MA from the University of Chicago. For more information, keep scrolling and see my CV!
CV
Research
Book Project
Investing with "Known Unknowns" in Low-Information Environments: How Firms, Political Uncertainty, and Autocracy Interact and Influence Contemporary China
My book project examines political uncertainty in autocracies, and its effects on investment, using evidence from contemporary China. I develop a theory that posits that political uncertainty in autocracies produces heterogeneous effects on investment, and identifies how institutions and other government interventions that transmit information moderate those effects. I model the theory to derive predictions for their signs and magnitudes. I test the predictions with evidence from contemporary China. To that end, I develop a measure of political uncertainty. Measuring political uncertainty in autocracies is an open problem. Without competitive elections, exogenous sources of variation are rare. I first locate an exogenous source of variation in political uncertainty in autocracies, namely China's institutionalized and routinized leadership transitions. I then exploit the Communist Party's tight control over the news media to reveal necessary and otherwise obscured internal dynamics of their leadership transitions, such as when leadership selections are actually made and how widely the identities of future leadership are shared prior to their official announcement. This entails identifying informative patterns in Chinese archival news coverage of the top candidates for "future" leadership positions using statistical and machine learning-based analyses, including anomaly detection with epidemic change-point estimation via a penalized cost approach that I extend for negative binomial and Poisson models and Bayesian detection methods; and text classification using unsupervised natural language processing. With that measure, I leverage variation across China in investment and interventions by the Communist Party, as well as detailed accounting data on domestic firms coupled with convenient restrictions on foreign investment, with panel analyses.
Working Papers
"Destabilizing to Stabilize: Interstate Dispute Escalation & Leadership Transitions in China" [preprint on OSF]
During the tumultuous waning weeks of the Trump administration, the chairman of the Joint Chiefs of Staff called his counterpart in China twice to reassure him that the president would not initiate sudden conflict as a tactic to remain in power. When news of the calls surfaced, critics decried those actions as heavy handed. In this paper, I present evidence that suggests such calls were actually a prudent measure, and provide an explanation for China’s leaders reported wariness and lingering skepticism. Namely, I find that China’s leaders have a history of militarily escalating disputes with other states in the time directly preceding and succeeding their leadership transitions. In fact, over 60 percent of incidents of escalation by China that occurred between 1989 and 2013 transpired around leadership transitions. I theorize that this previously unidentified pattern of escalation is motivated by concerns over domestic instability, and that it represents concessions to China’s hawkish issue publics to shore up stability at critical junctures. I illustrate the logic of that strategy with a simple formal model. Using maximum likelihood estimation, I find that there is a significant positive relationship between interstate dispute escalation and leadership transition. Of note, it is generally accepted that China has favored win-win diplomatic solutions to its disputes with other states. Instances of escalation have thus largely been categorized as aberrant behavior. My identification of this pattern of escalation challenges this logic and suggests that the militarization of disputes has at times been a routine and strategic undertaking by the leaders of China’s Communist Party.
"The Logic of Political Survival Revisited: Consequences of Elite Uncertainty Under Authoritarian Rule" [preprint on arXiv]
Existing research has established that autocrats offer concessions to prevent ouster by their inner circle. This paper examines how those concessions are influenced by the relative uncertainty of an autocrat's inner circle about remaining in that favored body. I take as my starting point the formal model of political survival presented in Bueno de Mesquita et. al.'s The Logic of Political Survival. I extend the model to account for variation in the relative uncertainty of an autocrat's inner circle. To make the math tractable, I dispense with convention and introduce comparative statics across two models with different formulations of uncertainty. This exercise reveals a set of conditions under which to expect an increase in the concessions offered by an autocrat with implications for development and democracy. Those findings yield a corresponding set of logical corollaries with potential to further our understanding of authoritarian politics, including an unexamined facet of the "dictator’s dilemma" and related incentives for members of an inner circle to permit purges or act to destabilize their ranks. The models also identify a source of policy volatility not found outside of autocracies. Taken together, the findings suggest a need for more research on elite uncertainty in autocracies.
"Measuring Political Uncertainty in Autocracies with Evidence from China" [Paper available upon request] [Poster presentation of findings - PolMeth 2024]
Political uncertainty—the lack of confidence with which government and policy outcomes can be predicted—has recently surged to unprecedented levels across the globe. Nonetheless, research on the subject is constrained by the absence of an objective measure. Existing solutions to the open problem of measuring political uncertainty, necessarily measure it indirectly; including by proxy via plausibly exogenous competitive elections or via newspaper indices that count explicit mentions and related terms. Those approaches exclude autocracies where competition is suppressed, ballot boxes are scarce or stuffed, and newspapers are censored. Toward a solution for autocracies, I develop a measure of political uncertainty with evidence from China. I first locate a plausibly exogenous source of variation in political uncertainty, namely China’s formerly institutionalized and routinized leadership transitions. I then exploit the Communist Party’s tight control over the news media to reveal the internal dynamics of those leadership transitions. This entails identifying informative patterns in Chinese archival news on the top candidates for "future" leadership positions, using statistical and machine-based anomaly detection methods; including anomaly detection with epidemic change-point estimation via a penalized cost approach and Bayesian detection methods. I find that prior to leadership selection, China's local officials campaign for candidates who share ties; and that the Communist Party appears to signal its leadership selection in the press before their identities are officially announced. With that information, I estimate the period when China's leadership transitions most closely approximate competitive elections to develop a measure of political uncertainty in autocracies.
Work in Progress
"Garbage In, Garbage Out? Systematic Error and Data-Driven Policy Making in China"
Resting Papers
"The "Benefits" of Clientelism: Electoral Support as an Insurance Premium with Evidence from Brazilian Municipalities"
Teaching
Graduate Courses (LSE)
Co-Instructor for PP478: Political Science for Public Policy; Academic Year 2023-2024 with Lloyd Gruber
Graduate Courses (UCLA)
Instructor for Math Camp (Introduction to Mathematics in the Social Sciences for incoming PhD students in Political Science, Psychology, Sociology, Geography, Anthropology, Urban Planning, & Environmental Studies); Summer 2020
TA for PS204A: Game Theory in Politics I; Winter 2021 with Barry O'Neill, Winter 2020 with Michael Chwe
Math Maven (Quantitative Methods & Formal Theory Consultant for PhD Students in Political Science); Academic Year 2018-2019, 2019-2020
Undergraduate Courses (UCLA)
Instructor for PS6: Introduction to Data Analysis; Summer 2021
TA for PS30: Politics & Strategy (Introduction to Formal Theory); Fall 2016, 2018, Winter 2022 with Michael Chwe, Spring 2017, 2019 with Kathleen Bawn, Winter 2019 with Barry O'Neill
TA for PS156: Government & Politics in Latin America; Winter 2017 with Barbara Geddes
For Fun
A Powerball simulator in R to teach lessons on rare events, probability, and lotteries or for risk and reward free fun