AI 中文总结
提出非参数集成条件矩检验处理效应异质性，通过重铸原假设降低对干扰参数估计敏感性，推导检验统计量渐近性质，证明其对局部备择假设有功效并开发自助法，还进行了扩展与应用研究。
AI 中文摘要
我们提出了一种非参数集成条件矩（ICM）检验，用于检验由给定协变量子向量定义的亚群之间的处理效应异质性。在无混淆性条件下，原假设被重铸为基于奈曼正交得分的条件矩限制，这降低了经验过程对干扰参数估计的一阶敏感性。检验统计量被构造为标记经验过程的连续泛函。我们建立了一致可行到最优近似，并推导了原假设和固定备择假设下这些检验统计量的渐近性质。我们进一步表明该检验对以\(n^{-1/2}\)速率收敛到原假设的局部备择假设有显著功效，并开发了一种易于实现的乘子自助法用于可行推断。我们还将检验扩展到参数化CATE规范检验以及内生处理和二元工具变量的设置。最后，我们应用所提出的检验方法来研究孕期母亲吸烟对婴儿出生体重的影响是否随母亲年龄而变化。
英文摘要
We propose a nonparametric integrated conditional moment (ICM) test for treatment effect heterogeneity across subpopulations defined by a given covariate subvector. Under unconfoundedness, the null is recast as a conditional moment restriction based on a Neyman-orthogonal score, which reduces the first-order sensitivity of the empirical process to nuisance parameter estimation. The test statistics are constructed as continuous functionals of a marked empirical process. We establish a uniform feasible-to-oracle approximation and derive the asymptotic properties of these test statistics under the null and fixed alternatives. We further show that the test has nontrivial power against local alternatives converging to the null at the $n^{-1/2}$ rate, and develop an easy-to-implement multiplier bootstrap for feasible inference. We also develop extensions to tests of parametric CATE specifications and to settings with endogenous treatment and a binary instrument. Finally, we apply the proposed testing approach to study whether the effect of maternal smoking during pregnancy on infant birth weight varies with maternal age.
Comments102 pages, including an online appendix; 2 figures and 12 tables
