857-0102-00L Methods IV: Causal Inference
|Semester||Spring Semester 2019|
|Lecturers||D. Hangartner, D. Ward|
|Periodicity||yearly recurring course|
|Language of instruction||English|
|Comment||Number of participants limited to 15.|
MA Comparative and International Studies are given priority.
|Abstract||This course provides an introduction to statistical methods used for causal inference in the social sciences, covering both experimental and observational studies.|
|Objective||Familiarity with the key research designs and statistical methods used for causal inference from randomised and observational data.|
|Content||This course provides an introduction to statistical methods used for causal inference in the social sciences. Using the potential outcomes framework of causality, we discuss designs and methods for data from randomized experiments and observational studies. In particular, designs and methods covered include randomization, matching, instrumental variables, difference-in-difference, synthetic control, regression discontinuity, and quantile regression. Examples are drawn from the social sciences.|
|Literature||Angrist, Joshua D., and Jörn-Steffen Pischke. Mostly harmless econometrics: An empiricist's companion. Princeton university press, 2008.|
Rosenbaum, Paul R. Design of Observational Studies. Springer. 2010.
|Prerequisites / Notice||Methods III or equivalent|