Impact Evaluation : Treatment Effects and Causal Analysis (Paperback)

1. Basic definitions, assumptions, and randomized experiments; 2. An introduction to nonparametric identification and estimation; 3. Selection on observables: matching, regression and propensity score estimators; 4. Selection on unobservables: nonparametric IV and structural equation approaches; 5. Difference-in-differences estimation: selection on observables and unobservables; 6. Regression discontinuity design; 7. Distributional policy analysis and quantile treatment effects; 8. Dynamic treatment evaluation.