This course surveys quantitative methods to make causal inferences in the absence of randomized experiment including the use of natural and quasi-experiments, instrumental variables, regression discontinuity, fixed effects estimators, and difference-in-differences. We emphasize the proper interpretation of these research designs and critical engagement with their key assumptions for applied researchers. Prerequisites: Prior training in multivariate regression (e.g., ECON 102B or the permission of the instructor).
3-5 units · Letter (ABCD/NP)
This course surveys quantitative methods to make causal inferences in the absence of randomized experiment including the use of natural and quasi-experiments, instrumental variables, regression discontinuity, fixed effects estimators, and difference-in-differences. We emphasize the proper interpretation of these research designs and critical engagement with their key assumptions for applied researchers. Prerequisites: Prior training in multivariate regression (e.g., ECON 102B or the permission of the instructor).
Offered in Spring 2027 at Stanford University.