Course List

The goal of this course is to give students a comprehensive toolbox for reading and producing cutting-edge applied empirical research, with focus on the theory and practice behind causal inference in social sciences. We will cover treatment effects, experiments, panel data, differences-in-differences, instrumental variables, nonparametric regression, regression discontinuity, matching, synthetic control, and more. Students will read applied papers from both political science and economics, and write review reports examining research designs, identification strategies, and causal claims. They will also produce research proposals that will be presented in class. Applications will be taught with R.

The goal of this course is to give students a comprehensive toolbox for reading and producing cutting-edge applied empirical research, with focus on the theory and practice behind causal inference in social sciences. We will cover treatment effects, experiments, panel data, differences-in-differences, instrumental variables, nonparametric regression, regression discontinuity, matching, synthetic control, and more. Students will read applied papers from both political science and economics, and write review reports examining research designs, identification strategies, and causal claims. They will also produce research proposals that will be presented in class. Applications will be taught with R.

The goal of this course is to give students a comprehensive toolbox for reading and producing cutting-edge applied empirical research, with focus on the theory and practice behind causal inference in social sciences. We will cover treatment effects, experiments, panel data, differences-in-differences, instrumental variables, nonparametric regression, regression discontinuity, matching, synthetic control, and more. Students will read applied papers from both political science and economics, and write review reports examining research designs, identification strategies, and causal claims. They will also produce research proposals that will be presented in class. Applications will be taught with R.

W 1400-1515 & F 1030-1200. The goal of this course is to give students a comprehensive toolbox for reading and producing cutting-edge applied empirical research, with focus on the theory and practice behind causal inference in social sciences. We will cover treatment effects, experiments, panel data, differences-in-differences, instrumental variables, nonparametric regression, regression discontinuity, matching, synthetic control, and more. Students will read applied papers from both political science and economics, and write review reports examining research designs, identification strategies, and causal claims. They will also produce research proposals that will be presented in class. Applications will be taught with R.

Substantive questions in empirical social science research are often causal. Does voter outreach increase turnout? Do political institutions affect economic development? Are job training programs effective? This class will introduce students to both the theory and the practice behind making these kinds of causal inferences. We will cover causal identification, potential outcomes, experiments, matching, regression, difference-in-differences, instrumental variables estimation, regression discontinuity designs, sensitivity analysis, dynamic causal inference, and more. The course will draw upon examples from political science, economics, sociology, public health, and public policy.

Substantive questions in empirical social science research are often causal. Does voter outreach increase turnout? Do political institutions affect economic development? Are job training programs effective? This class will introduce students to both the theory and the practice behind making these kinds of causal inferences. We will cover causal identification, potential outcomes, experiments, matching, regression, difference-in-differences, instrumental variables estimation, regression discontinuity designs, sensitivity analysis, dynamic causal inference, and more. The course will draw upon examples from political science, economics, sociology, public health, and public policy.