One lecture session per week. Problem sets are due one week after the sessions they cover; see Assignments and Exams.
| Ses # | Topic | Main deliverable |
|---|
| Part I · Linear regression and inference |
| 1 | From Probability to the Linear Regression Model | OLS derivation and projection geometry |
| 2 | OLS Inference: Sampling Distributions, Hypothesis Tests, and Confidence Intervals | t/F/Wald inference exercise |
| 3 | Functional Form, Partial Effects, and Omitted-Variable Bias | Marginal-effect and bias analysis |
| 4 | Heteroskedasticity, Dependence, and Robust Inference | Covariance estimator comparison |
| Part II · Endogeneity and identification |
| 5 | Endogeneity, Instrumental Variables, and Two-Stage Least Squares | Instrument validity memo |
| 6 | Simultaneous Equations and Structural Identification | Identification conditions exercise |
| Part III · Panel data |
| 7 | Panel Data: Fixed Effects, Random Effects, and Correlated Effects | FE/RE comparison |
| 8 | Dynamic Panels, Difference GMM, and System GMM | GMM moment-condition defense |
| Part IV · Time-series econometrics |
| 9 | Time-Series Foundations: Stationarity, ARMA, and Forecasting | Stationarity and ARMA lab |
| 10 | Unit Roots, Structural Breaks, and Persistence | Deterministic specification report |
| 11 | VAR and Structural VAR: Dynamic Interactions and Shock Identification | IRF and identification report |
| 12 | Cointegration, VECM, and ARDL Models | VECM/ARDL comparison |
| Part V · Causal inference and research practice |
| 13 | Causal Inference: Potential Outcomes, DiD, and Regression Discontinuity | DiD/RD design memo |
| 14 | Research Design, Monte Carlo, Replication, and Reporting | Reproducible empirical presentation |