ECON 410: Data Analytics for Economic Policy Evaluation

Course Description

This course aims to equip students with a comprehensive set of statistical tools and research designs pivotal for high-quality research in applied microeconomics and related fields. The curriculum prioritizes research design over statistical technique, focusing on real-world applications rather than theoretical proofs. Key topics include cutting-edge empirical methods for causal inference, such as matching methods, causal machine learning, differences-in-differences design, synthetic controls design, regression discontinuity design, and instrumental variables. The course also integrates recent advances in data science and machine learning, bridging across disciplines such as economics, philosophy, statistics, and computer science to enrich policy debates and research design. (W).