Seminar 217, Risk Management: Better Lee Bounds (Online)

Seminar 217, Risk Management: Better Lee Bounds (Online)

Apr 13, 2021, 11:00 AM - 12:30 PM | Online | Happening As Scheduled
Vira Semenova, UC Berkeley (Speaker)

ABSTRACT: This paper develops methods for tightening Lee's (2009) bounds on average causal effects when the number of pre-randomization covariates is large, potentially exceeding the sample size. These Better Lee Bounds are guaranteed to be sharp when few of the covariates affect the selection and the outcome. If this sparsity assumption fails, the bounds remain valid. I propose inference methods...