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
Econometrica · 2025 · Stefan Wager
中文摘要
我们利用 Luedtke 和 van der Laan（2016）的鞅构造，构建用于检验处理效应异质性是否存在的检验方法。由此得到的序贯验证方法可借助多种验证指标（如 BLP、GATES、QINI 曲线等）进行实例化，并为这些指标的类似交叉验证的跨折应用提供了一种替代方案。本说明是作为对 Chernozhukov、Demirer、Duflo 和 Fernández-Val 即将发表于《Econometrica》的 Fisher–Schultz 论文的评论而撰写的。
Abstract
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 Fernández‐Val, forthcoming in Econometrica.