Econometric Data Science
Introduces regression and other tools for causal inference and descriptive analysis in empirical economics. Topics include analysis of randomized experiments, instrumental variables methods and regression discontinuity designs, differences-in-differences estimation, and regress with time series data. Develops the skills needed to conduct — and critique — empirical studies in economics and related fields. Empirical applications are drawn from published examples and frontier research. Familiarity with statistical programming languages is helpful. Students taking graduate version complete an empirical project leading to a short paper. No listeners. Limited to 70 total for versions meeting together.
Prerequisites & course information
Subject meets with 14.32 Prereq: 14.300 , 15.069 , or 18.650[J] G (Fall, Spring) 4-4-4 units
Sources
- Course catalogue ↗2026–2027