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econ.EM2026

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…

econ.EM2026

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…

econ.EM2026

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…

econ.EM2024

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…

econ.EM2024

Inference for parameters identified by conditional moment restrictions using a generalized Bierens maximum statistic

Xiaohong Chen, Sokbae Lee, Myung Hwan Seo +1

Many economic panel and dynamic models, such as rational behavior and Euler equations, imply that the parameters of interest are identified by conditional moment restrictions. We i…

econ.EM2024

Treatment Choice with Nonlinear Regret

Toru Kitagawa, Sokbae Lee, Chen Qiu

The literature focuses on the mean of welfare regret, which can lead to undesirable treatment choice due to sensitivity to sampling uncertainty. We propose to minimize the mean of…