Gov 2002: Causal Inference

With Michael Peress (Fall 2016)
Graduate course on the theory and implementation of causal inference methods for social science research. Topics include randomized experiments, matching, diff-in-diff, instrumental variables, regression discontinuity designs, sensitivity analysis, and causal mediation.

Section Syllabus

Section 1

Section 2 , Data and Code

Section 3

Section 4, Paper

Section 5

Section 6

Section 7

Section 8

Section 9

Section 10 , Code

Section 11 , Code

Math Prefresher: A Short Course in Quantitative Methods (Link)

(Summer 2016, Summer 2017)
A two-week graduate course on mathematics and computer programming for social scientists. The course introduces the mathematics and computer skills needed for quantitative and formal modeling courses offered at Harvard.