Panos Toulis
Causal Inference under Network Interference: The Case of Cupid Effects
Hillel Bavli
Aggregating for Accuracy: A Closer Look at Sampling and Accuracy in Class Action Litigation
Title: Treatment Effect Heterogeneity
Abstract: Applied researchers are increasingly interested in whether and how treatment effects vary in randomized evaluations, especially variation not explained by observed covariates. We propose a model-free approach for testing for the presence of such unexplained variation. To use this randomization-based approach, we must address the fact that the average treatment effect, generally the object of interest in randomized experiments, actually acts as a nuisance parameter in this setting. We explore potential solutions and advocate for a method that... Read more about ResearchStats: Peng Ding