Introduction to the Potential Outcomes Framework. Input Talk, Mannheim Centre for European Social Research, September 10, 2019.
This talk introduces participants to the potential outcomes framework, one of the primary approaches to causality in the social sciences and beyond. The talk covers the basic intuition of counterfactual causality as well as the fundamental problem of causal inference and relates core assumptions of frequently used identification strategies to the potential outcomes framework. A hands-on simulation exercise allows participants to apply the framework to artificial data and to further their understanding of biases in causal quantities of interest when core assumptions are violated.
Denis Cohen is a postdoctoral fellow in the Data and Methods Unit at the Mannheim Centre for European Social Research (MZES), University of Mannheim. His research focus lies at the intersection of political preference formation, electoral behavior and political competition. His methodological interests include quantitative approaches to the analysis of clustered data, measurement models, data visualization, strategies for causal identification, and Bayesian statistics.