Doubly robust nearest neighbors in factor models

Name: Doubly robust nearest neighbors in factor models
Uploaded: 2026-08-19T05:03:13.326330+00:00
Duration: 553 s
Description: The episode discusses the paper "Doubly robust nearest neighbors in factor models" by researchers from Harvard, MIT, and the University of Michigan. The hosts examine the DR-NN estimate, which addresses missing data by combining unit and time neighbors. This method provides improved accuracy and tighter confidence intervals compared to traditional approaches.

The episode discusses the paper "Doubly robust nearest neighbors in factor models" by researchers from Harvard, MIT, and the University of Michigan. The hosts examine the DR-NN estimate, which addresses missing data by combining unit and time neighbors. This method provides improved accuracy and tighter confidence intervals compared to traditional approaches.

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