Olle Folke is a researcher at the department of government at Uppsala University. He has previously been an assistant professor at SIPA, Columbia University. He has held visiting appointments at Harvard, MIT and Berkeley. He has published in, for example, the American Political Science Review, American Journal of Political Science, Journal of Politics, and the American Economic Review.

Johanna Rickne is an associate professor at SOFI, Stockholm University. She has previously been a lecturer in quantitative methods at SIPA, Columbia University and a researcher at Research Institute for Industrial Economics. She has held visiting appointments at Harvard and Berkeley. Her research has been published in the American Political Science Review, American Economic Review, Comparative Political Studies, and the Economic Journal.

Course Content
Policy evaluation is important across academic fields. In economics, policies may address levels and distributions of taxes and subsidies. In political science, policies may address the design of the electoral system, for example by the introduction of gender quotas. This course teaches common econometric tools for evaluating policy impacts. A strong emphasis is placed on the logic of causal inference: How can we design our evaluation so that we can estimate actual causal effect of the policy?
Half the time will be devoted to lectures and the other half to practical work in STATA. Replicating and discussing previous research will be an important tool for highlighting and reinforcing learning of the lecture content.

Course Objectives
1. Students will be able to design advanced policy evaluations with quantitative methods. In particular, they will be able to correctly apply i) regression discontinuity designs, ii) instrumental variable designs, and iii) difference-in-difference designs.
2. Students should be able to critically evaluate the empirical soundness of existing policy evaluations.

Course Prerequisites
Students should be familiar with the basic principles of policy evaluation. This includes concepts such as randomization, treatment and control groups, and exogeneity. The course will devote considerable time to practical applications of advanced econometric methods. Familiarity with application of basic quantitative methods in STATA is therefore an important pre-requisite.

Representative Background Reading
Specify one or two articles a participant should be able to read (& understand) before beginning the course.

Required texts
Angrist, Joshua D., and Jörn-Steffen Pischke. Mastering Metrics: The path from cause to effect. Princeton University Press, 2014.
Dunning, Thad. Natural experiments in the social sciences: A design-based approach. Cambridge University Press, 2012.

Day 1: Course Introduction, Basic Regression Principles, Panel Data and Interaction Models
Day 2: The Challenge of Causal Inference, Control Variables, the Experimental Ideal, Conditional Independence Assumption
Day 3: Basic Principles Natural Experiments
Day 4: Difference in Difference Design
Day 5: Regression Discontinuity Design
Day 6: Advanced Topics in Regression Discontinuity Designs
Day 7: Instrumental Variables
Day 8: Evaluating Research Designs Part 1: Validating Identifying Assumptions
Day 9: Evaluating Research Designs Part 2. Multiple Testing, Standard Errors and Mechanisms.
Day 10: Course Conclusion. Extended discussion of empirical applications.