Causal Inference

To establish causal relations between variables, rather than mere correlations is the goal of many empirical studies in almost every scientific domains. Labor economists want to know whether job training programs successfully increase participants’ wages. Epidemiologists want to know whether a particular medical treatment improves quality of life. Advertisers want to know whether a marketing campaign is effective at boosting sales.  This course will provide the fundamentals of how to reason about causality and make causal determinations using empirical data. It will introduce the counterfactual framework of causal inference and then discuss a variety of approaches, starting with the most basic experimental designs to more complex observational methods, for making inferences about causal relationships from the data.