Switchback experimental design, wherein a single unit (e.g., a whole system) is exposed to a single random treatment for interspersed blocks of time, tackles both cross-unit and temporal interference. Hu and Wager (2022) recently proposed a treatment-effect estimator that truncates the beginnings of blocks and established a $T^{-1/3}$ rate for estimating the global average treatment effect (GATE) in a Markov setting with rapid mixing. They claim this rate is optimal and suggest focusing instead on a different (and design-dependent) estimand so as to enjoy a faster rate. For the same design we propose an alternative estimator that uses the whole block and surprisingly show that it in fact achieves an estimation rate of $\sqrt{\log T/T}$ for the original design-independent GATE estimand under the same assumptions.

翻译：回返实验设计（Switchback experimental design）指单个实验单元（如整个系统）在交替时间块内接受单一随机处理，可同时解决跨单元和时间干扰问题。Hu与Wager（2022）近期提出了一种截断块首的治疗效应估计量，并证明在快速混合的马尔可夫设定下，该估计量对全局平均处理效应（GATE）的估计速率可达$T^{-1/3}$。他们声称该速率为最优，并建议转而关注另一种（依赖实验设计的）估计目标以获得更快速率。针对同一实验设计，我们提出了一种利用完整时间块的替代估计量，并意外证明：在相同假设条件下，该估计量对原始独立于设计的GATE估计目标实际可实现$\sqrt{\log T/T}$的估计速率。