5 papers
Individual Shrinkage for Random Effects
Raffaella Giacomini, Sokbae Lee, Silvia Sarpietro
This paper develops an approach to random effects estimation and individual-level forecasting in micropanels that targets individual accuracy rather than aggregate performance. The…
Bounding Treatment Effects by Pooling Limited Information across Observations
Sokbae Lee, Martin Weidner
We provide novel bounds on average treatment effects (on the treated) that are valid under an unconfoundedness assumption. Our bounds are designed to be robust in challenging situa…
Treatment Effects with Targeting Instruments
Sokbae Lee, Bernard Salanié
Multivalued treatments are commonplace in applications. We explore the use of discrete-valued instruments to control for selection bias in this setting. Our discussion revolves aro…
Statistical inference in two-stage observation models including algorithmic randomness
Zhixiang Zhang, Sokbae Lee, Edgar Dobriban
Randomized algorithms, such as random sampling, random projections, and stochastic optimization, are increasingly used to reduce the computational cost of modern statistical analys…
Individual Welfare Analysis: Random Quasilinear Utility, Independence, and Confidence Bounds
Junlong Feng, Sokbae Lee
We introduce a novel framework for individual-level welfare analysis. It builds on a parametric model for continuous demand with a quasilinear utility function, allowing for hetero…