Course Content
Each session combines conceptual reasoning, empirical design, and a short base-R exercise. Use the links under each session to access slides, homework, theory practice, and code.
Identification Strategy and Independence Refresher
Required RefresherQuestion: What is causal inference?
Concepts: causal effect, counterfactual, potential outcomes, identification, independence.
Recommended reading:
- Angrist, J. D., & Pischke, J.-S. (2010). The credibility revolution in empirical economics: How better research design is taking the con out of econometrics. Journal of Economic Perspectives, 24(2), 3–30.
Foundations of Policy Evaluation
Session 1Question: What exactly are we trying to learn when evaluating a policy?
Concepts: causal question, treatment, outcome, population, time horizon, potential outcomes, estimand, selection bias, internal and external validity.
Recommended paper:
- LaLonde, R. J. (1986). Evaluating the econometric evaluations of training programs with experimental data. American Economic Review, 76(4), 604–620.
Selection Bias, Regression, Matching, and Inference
Session 2Question: Can conditioning on observables reconstruct the missing counterfactual?
Concepts: naive comparisons, conditional independence, bad controls, propensity score, common support, balance diagnostics, clustered inference.
Recommended paper:
- Dehejia, R. H., & Wahba, S. (2002). Propensity score-matching methods for nonexperimental causal studies. Review of Economics and Statistics, 84(1), 151–161.
Randomised Experiments: Design and Power
Session 3Question: What does randomisation solve, and what problems remain?
Concepts: assignment mechanism, balance, implementation threats, minimum detectable effect, cluster design effect, experimental protocol.
Recommended paper:
- Miguel, E., & Kremer, M. (2004). Worms: Identifying impacts on education and health in the presence of treatment externalities. Econometrica, 72(1), 159–217.
Compliance, IV, LATE, and External Validity
Session 4Question: Can exogenous variation in treatment identify effects when treatment is endogenous?
Concepts: encouragement design, compliers, always-takers, never-takers, defiers, relevance, independence, exclusion, monotonicity, weak instruments, external validity.
Recommended paper:
- Angrist, J. D. (1990). Lifetime earnings and the Vietnam era draft lottery: Evidence from Social Security administrative records. American Economic Review, 80(3), 313–336.
Difference-in-Differences: 2x2 and TWFE
Session 5Question: Can untreated trends reveal the missing counterfactual trend?
Concepts: before-after comparison, treated-control comparison, ATT in the post period, parallel trends, TWFE, serial correlation, clustering.
Recommended paper:
- Card, D., & Krueger, A. B. (1994). Minimum wages and employment: A case study of the fast-food industry in New Jersey and Pennsylvania. American Economic Review, 84(4), 772–793.
Event Studies and Staggered DiD
Session 6Question: What changes when treatment timing and treatment effects are heterogeneous?
Concepts: omitted period, dynamic effects, anticipation, weak support, never-treated and not-yet-treated controls, ATT(g,t), aggregation.
Recommended paper:
- Autor, D. H. (2003). Outsourcing at will: The contribution of unjust dismissal doctrine to the growth of employment outsourcing. Journal of Labor Economics, 21(1), 1–42.
Regression Discontinuity
Session 7Question: Can an institutional threshold create a locally credible comparison?
Concepts: running variable, cutoff, bandwidth, local linear regression, density checks, covariate continuity, placebo cutoffs, fuzzy RDD, local IV estimand.
Recommended paper:
- Lee, D. S. (2008). Randomized experiments from non-random selection in U.S. House elections. Journal of Econometrics, 142(2), 675–697.
Synthetic Control, Heterogeneity, and Replication
Session 8Question: How do we synthesise, interpret, and challenge causal evidence?
Concepts: donor pool, predictors, weights, pre-treatment fit, treatment gap, placebo tests, heterogeneity, transport, robustness, replication audit.
Recommended paper:
- Abadie, A., Diamond, A., & Hainmueller, J. (2010). Synthetic control methods for comparative case studies: Estimating the effect of California's tobacco control program. Journal of the American Statistical Association, 105(490), 493–505.