This course covers modern econometric methods of causal estimation and inference. The course will focus on identification strategies and may cover instrumental variables, the potential outcome framework, difference-in-difference and high-dimensional fixed effects, dynamic fixed effects (event studies), regression discontinuity designs, matching methods, and synthetic cohort methods. Additional topics may include clustered standard errors, spatial econometrics, GMM, and structural estimation. Prerequisites: Registration in the Business PhD Program, Department of Economics PhD Program, or permission of instructor. Approval of the Associate Dean for the Business PhD Program also required for non-PhD students.