On March 22, 2020, the State of New York issued a “stay-at-home” policy, wherein all non-essential businesses were on pause until June 8, 2020. The bike-sharing system (BSS) and yellow taxi system (YTS) in Manhattan were substantially affected. This sudden drop in demand can impact not only short and long-term mobility but also the sustainability of transport network. Given that few empirical studies are focusing on the impacts of the “stay-at-home” policy on the BSS and YTS, this further substantiates the importance of analyzing how the policy affects the overall transportation system in New York City (NYC). This paper aims to fill this gap by quantifying the impacts of the “stay-at-home” policy on the two aforementioned transportation systems. Specifically, the following three research gaps are summarized in this study: I) The hidden biases in current “stay-at-home” policy estimation methods were not properly addressed; II) The policy impacts on BSS and YTS during different periods of the effective day were unclear; III) The sensitivity of uncontrolled confounders in long-term policy impact estimations was poorly discussed. We addressed these important research gaps by introducing robust statistical approaches like regression discontinuity design (RDD) and propensity score matching (PSM) methods, which can overcome methodological challenges such as counterfactual restoration, spatiotemporal heterogeneities, and unmeasured confounders. The BSS and YTS were studied at the aggregated neighborhood levels. Results demonstrate that the impacts on BSS have higher variations than YTS usage. The monthly average treatment effects on the treated (ATT) for BSS ranged from −72% to −28% respectively in March and June, while YTS ranged from −96% to −94%. Evidence suggests that demand for BSS surged on weekends in May and June. Understanding the impact of this short-term yet significant policy change on travel behavior will help optimize supply and demand management strategies, thereby improving the long-term sustainability should similar situations arise in the future.

2020 年 3 月 22 日，纽约州发布“居家”政策，所有非必要业务暂停至 2020 年 6 月 8 日。 共享单车系统（BSS）和黄色出租车系统（ YTS）在曼哈顿受到重大影响。需求的突然下降不仅会影响短期和长期的流动性，还会影响交通网络的可持续性。鉴于很少有实证研究关注“居家”政策对 BSS 和 YTS 的影响，这进一步证实了分析该政策如何影响纽约市 (NYC) 整体交通系统的重要性。本文旨在通过量化“居家”政策对上述两个交通系统的影响来填补这一空白。具体而言，本研究总结了以下三个研究空白：I) 当前“宅在家里”政策估计方法中隐藏的偏见没有得到妥善解决；二) 生效日不同时段政策对BSS和YTS的影响不明确；III) 长期政策影响估计中不受控制的混杂因素的敏感性没有得到很好的讨论。我们通过引入稳健的统计方法（如回归不连续性设计 (RDD) 和倾向评分匹配 (PSM) 方法）解决了这些重要的研究空白，这些方法可以克服反事实恢复、时空异质性和未测量的混杂因素等方法论挑战。BSS 和 YTS 在聚合邻域水平上进行了研究。结果表明，对 BSS 的影响比 YTS 使用具有更大的变化。3 月和 6 月，BSS 对治疗 (ATT) 的月平均治疗效果范围分别为 -72% 至 -28%，而 YTS 的范围为 -96% 至 -94%。有证据表明，5 月和 6 月的周末对 BSS 的需求激增。了解这种短期但重大的政策变化对旅行行为的影响将有助于优化供需管理策略，从而在未来出现类似情况时提高长期可持续性。