I study the impact of transportation network companies (TNC) on traffic delays using a natural experiment created by the abrupt departure of Uber and Lyft from Austin, Texas. Applying difference in differences and regression discontinuity specifications to high-frequency traffic data, I estimate that Uber and Lyft together decreased daytime traffic speeds in Austin by roughly 2.3%. Using Austin-specific measures of the value of travel time, I translate these slowdowns to estimates of citywide congestion costs that range from $33 to $52 million annually. Back of the envelope calculations imply that these costs are similar in magnitude to the consumer surplus provided by TNCs in Austin. Together these results suggest that while TNCs may impose modest travel time externalities, restricting or taxing TNC activity is unlikely to generate large net welfare gains through reduced congestion.

我使用Uber和Lyft突然从德克萨斯州奥斯汀出发创建的自然实验，研究了运输网络公司（TNC）对交通延误的影响。将差异和回归不连续性规范应用于高频交通数据，我估计Uber和Lyft共同使奥斯丁的日间交通速度降低了约2.3％。通过使用奥斯汀特定的出行时间价值衡量标准，我将这些放缓情况转化为对城市范围内交通拥堵成本的估计，每年的交通拥堵成本在33到5200万美元之间。粗略计算表明，这些成本在数量上与跨国公司在奥斯丁提供的消费者剩余相似。这些结果共同表明，尽管跨国公司可能会施加适度的旅行时间外部性，