Thomas Leavitt

Thomas Leavitt

Asst Professor

Marxe School of Public and International Affairs

Department: Public Affairs

Areas of expertise:

Email Address: thomas.leavitt@baruch.cuny.edu

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Dr. Leavitt is currently a postdoctoral research fellow at Harvard University, where he works on Difference-in-Differences and related statistical methods. He received his Ph.D. in Political Science from Columbia University, where he specialized in methodology and comparative politics. Dr. Leavitt’s research develops methods in causal inference, with a specific emphasis on randomized experiments, design-based inference, and their integration with Bayesian methodology. He applies these methodological developments to studies of racial and ethnic politics in a comparative perspective using original data from the US and South Africa.

Education

Ph.D., Political Science, Columbia University New York United States

M.Phil., Political Science, Columbia University New York United States

M.A., Political Science, Columbia University New York United States

M.A., Committee on International Relations, University of Chicago Chicago United States

B.A., Political Science, DePauw University Greencastle United States

SemesterCourse PrefixCourse NumberCourse Name
Fall 2023PAF9271Data Analysis for Public Servi
Fall 2023PAF9271Data Analysis for Public Servi

Journal Articles

(2023). An empirical Bayes' alternative to design-based identification and inference for Difference-in- Differences. Observational Studies,

(2023). Randomization-based, Bayesian Inference of Causal Effects. Journal of Causal Inference, 11(1).

Audit experiments of racial discrimination and the importance of symmetry in exposure to cues . Political Analysis,

Audit Experiments of Racial Discrimination and the Importance of Symmetry in Exposure to Cues.

Book Chapters

Leavitt, T., & Bowers, J. (2020). Causality and Design-Based Inference . The SAGE Handbook of Research Methods in Political Science and International Relations (p. 769–804). SAGE Publications.

Challenges that proprietary research poses for meta-analysis. The Oxford Handbook of Methodological Pluralism

Presentations

Rivera-Burgos, V., & Leavitt, T. (2024, May 21). Parsing Taste-Based from Statistical Discrimination in Audit Experiments. American Causal Inference Conference. Austin, Texas: The Society for Causal Inference.

Leavitt, T. Parsing Taste-Based from Statistical Discrimination in Audit Experiments . Data Science Lunch Seminar Series. : The Center for Data Science, New York University.

Leavitt, T. Planning observational studies with unobserved confounding in mind . Joint Statistical Meetings. Toronto, CA: American Statistical Association.

Leavitt, T. Model selection for Decreasing Dependence on Counterfactual, Identification Assumptions in Controlled Pre-Post Designs . Applied Statistics Workshop. : The Institute for Quantitative Social Science, Harvard University.

Leavitt, T. Model selection for Decreasing Dependence on Counterfactual, Identification Assumptions in Controlled Pre-Post Designs . Quantitative Methods Workshop. : Wilf Family Department of Politics, New York University.

Leavitt, T. Potential Outcome & Directed Acyclic Graphs (DAGs) . The Miratrix C.A.R.E.S. Lab. : Graduate School of Education and Department of Statistics, Harvard University.

Leavitt, T. Major debates in African politics: Colonial rule, anti-colonial resistance and postindependence colonial legacies. B8772-001 -- Global Immersion in East Africa. : Columbia Business School and Chazen Institute for Global Business, Columbia University.

Leavitt, T. Randomization-based, Bayesian inference of causal effects . Quantitative Methods Workshop. : Wilf Family Department of Politics, New York University.