4 papers
Cross-Fitting Under Nonregularity: Normality and Inference via Locality
Bruno Fava
Cross-fitting is routine in much of applied research. While conventional confidence intervals that ignore cross-fold dependence are asymptotically valid in several settings, they u…
Training and Testing with Multiple Splits: A Central Limit Theorem for Split-Sample Estimators
Bruno Fava
As predictive algorithms grow in popularity, using the same dataset to both train and test a new model has become routine across research, policy, and industry. Sample-splitting at…
Predicting the Distribution of Treatment Effects: A Covariate-Adjustment Approach
Bruno Fava
Important questions for impact evaluation require knowledge not only of average effects, but of the distribution of treatment effects. The inability to observe individual counterfa…
The Illusion of the Illusion of Sparsity: An exercise in prior sensitivity
Bruno Fava, Hedibert F. Lopes
The emergence of Big Data raises the question of how to model economic relations when there is a large number of possible explanatory variables. We revisit the issue by comparing t…