From Predictive Algorithms to the Automatic Generation of Anomalies. The draft can be found here.

Two-way Fixed Effects and Differences-in-Differences Estimators in Heterogeneous Adoption Designs

Production Function Estimation Using Subjective Expectations Data

Learning the Effect of Persuasion via Difference-in-Differences

Causal Inference under Interference through Designed Markets

Moment Restrictions in Nonlinear Panel Data Models with Feedback

Empirical Bayes When Estimation Precision Predicts Parameters

Inference for an Algorithmic Fairness-Accuracy Frontier

Robust Treatment Choice: A View From Partial Identification