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：切换实验设计通过让单一单元（如整个系统）在穿插的时间块内暴露于单一随机处理，同时解决了跨单元干扰和时间干扰问题。Hu与Wager（2022）近期提出了一种截断时间块起始部分的处理效应估计量，并在快速混合的马尔可夫设定下，建立了全局平均处理效应（GATE）估计的$T^{-1/3}$收敛速率。他们声称该速率具有最优性，并建议转而关注另一种依赖实验设计的估计目标，以获得更快的收敛速率。针对同一实验设计，我们提出了一种利用整个时间块的替代估计量，并令人惊讶地证明：在相同假设条件下，该估计量对于原始不依赖于实验设计的全局平均处理效应（GATE）目标，实际上能达到$\sqrt{\log T/T}$的估计收敛速率。