Journal of Political Economy · 2026 · Victor Chernozhukov、Kaspar Wüthrich、Yinchu Zhu
中文摘要
我们提出一种实用且稳健的方法, 用于对合成控制法估计的平均处理效应进行统计推断。我们构建了用于偏误修正的 K 折交叉拟合程序。为避免长期方差估计这一难题, 推断基于自归一化（self-normalized）t 统计量, 该统计量的渐近分布是具有枢轴性质的 t 分布。我们的 t 检验易于实施, 在模型设定偏误下具有可证明的稳健性, 且对平稳与非平稳数据均有效。在基于实际应用的模拟中, 该检验展现出优异的小样本表现, 并相对于其他方法表现良好。我们通过重新考察碳税对排放的影响来说明该 t 检验的实用价值。
Abstract
We propose a practical and robust method for making inference on average treatment effects estimated by synthetic controls. We develop a K-fold cross-fitting procedure for bias correction. To avoid the difficult estimation of the long-run variance, inference is based on a self-normalized t-statistic, which has an asymptotically pivotal t-distribution. Our t-test is easy to implement, provably robust against misspecification, and valid with stationary and nonstationary data. It demonstrates an excellent small-sample performance in application-based simulations and performs well relative to other methods. We illustrate the usefulness of the t-test by revisiting the effect of carbon taxes on emissions.