Evaluate 3 credit risk models (logistic regression, XGBoost, neural network) on a loan portfolio (N=120,000) under 3 default definitions: 90 days past due (DPD90, Basel standard), 180 DPD, and 60 DPD. Model rankings change: at DPD90, XGBoost leads (AUC=0.
Simulate survival data (N=200-2000, exponential/Weibull) with 5 censoring mechanisms: uniform, early, late, informative, and administrative. Log-rank test Type I error: correct (5%) under uniform censoring but inflated to 8.
Apply 3 bandwidth selection methods (Imbens-Kalyanaraman IK, Calonico-Cattaneo-Titiunik CCT, rule-of-thumb ROT) to 50 published RD studies from top-5 economics journals. Bandwidth estimates: median IK/CCT ratio = 1.
Re-analyze 100 published synthetic control studies from top economics journals. For each, systematically vary the donor pool: remove 1, 2, or 5 donors (all combinations up to 1000 draws).