A Comment on: Fisher-Schultz Lecture: Generic Machine Learning Inference on Heterogeneous Treatment Effects in Randomized Experiments, With an Application to Immunization in India by Victor Chernozhukov, Mert Demirer, Esther Duflo, and Iván Fernández-Val
成果类型：
Article
署名作者：
Wager, Stefan
署名单位：
Stanford University
刊物名称：
ECONOMETRICA
ISSN/ISSBN：
0012-9682
DOI：
10.3982/ECTA23293
发表日期：
2025
页码：
1171-1176
关键词：
摘要：
We use the martingale construction of Luedtke and van der Laan (2016) to develop tests for the presence of treatment heterogeneity. The resulting sequential validation approach can be instantiated using various validation metrics, such as BLPs, GATES, QINI curves, etc., and provides an alternative to cross-validation-like cross-fold application of these metrics. This note was prepared as a comment on the Fisher-Schultz paper by Chernozhukov, Demirer, Duflo, and Fern & aacute;ndez-Val, forthcoming in Econometrica.
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