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Research questions in political behaviour are often causal. Does voter outreach increase turnout? Can political campaigns persuade voters? Does political performance increase incumbent voting? The course will introduce students to tools to answer these questions and apply them to empirical data from the field of political behaviour. We will begin by introducing statistical theory and practice of causal inference. As theoretical frameworks, we will discuss potential outcomes and randomization. We will also cover various methodological tools including randomized experiments, regression discontinuity designs, regression, instrumental variables, difference-in-differences. Lastly, we apply machine learning techniques for causal inference using regression trees, Lasso, and causal forests. Empirical topics will include political persuasion, credit claiming, and the effect of "Get out the vote" campaigns. |
