Teppei Yamamoto is an Associate Professor of Political Science at the Massachusetts Institute of Technology and a Faculty Affiliate of the Center for Statistics at the Institute for Data, Systems, and Society. Professor Yamamoto has a B.A. in Liberal Arts from the University of Tokyo and M.A. and Ph.D. in Politics from Princeton University.
His research focuses on various methods of causal inference, including causal moderation and causal attribution. Additionally, he has written on Bayesian statistics with a focus on electoral studies and comparative political behavior using discrete choice models and empirical applications.
“Validating Vignette and Conjoint Survey Experiments against Real-World Behavior” (2015), Proceedings of the National Academy of Sciences of the United States of America, 112(8), 2395-2400
“Identification and Sensitivity Analysis for Multiple Causal Mechanisms: Revisiting Evidence from Framing Experiments” (2013), Political Analysis, 21(2), 141-171
“Causal Inference with Differential Measurement Error: Nonparametric Identification and Sensitivity Analysis” (2010), American Journal of Political Science, 54(2), 543-560