ECON 8899 - Causal Inference and Evidence-based Policy

3 Credit Hours
Prerequisites: A graduate-level statistics course that covers probability theory, hypothesis testing and linear regression.
Description
If unsure about , contact the professor. To answer cause-and-effect questions, a counterfactual model of causality and a unified methodological framework has been developed over the last three decades. This class aims to teach students to apply and interpret the counterfactual model and associated designs for answering policy-relevant empirical questions. Students will gain a deeper understanding of, and connections among, approaches to answering causal questions and of the nature of evidence itself. The topics comprise experimental designs and a suite of observational designs, including conditioning designs, partial identification designs, multiple control group designs, instrumental variable designs, regression discontinuity designs, synthetic control designs and tests of known effects and sensitivity tests to hidden bias. These topics are examined in a broad range of policy domains (poverty, planning, economic development, politics, crime, social work, health, public finance, environment, and others).