谁从动态定价中受益？

中文摘要

新技术近来推动了实时定价的繁荣。我研究了其中最突出的例子——网约车中的动态加价。利用Uber的数据，我构建了一个空间均衡的实证模型，用以衡量动态加价的福利效应。该模型由需求、供给和匹配技术构成，允许存在时间和空间上的异质性，以及供给与需求中的随机性。我发现，相对于Uber统一设定整体价格水平的统一定价反事实情形，动态加价使总福利增加了总收入的2.15%。福利效应在市场各方之间存在显著差异：乘客剩余增加了总收入的3.57%，而司机剩余和平台当前利润分别减少了总收入的0.98%和0.50%。所有收入水平的乘客均从中受益。在司机中，工作时间长的司机受损最严重，女性尤其如此。

Abstract

New technologies have recently led to a boom in real‐time pricing. I study the most salient example, surge pricing in ride hailing. Using data from Uber, I develop an empirical model of spatial equilibrium to measure the welfare effects of surge pricing. The model is composed of demand, supply, and a matching technology. It allows for temporal and spatial heterogeneity as well as randomness in supply and demand. I find that, relative to a uniform pricing counterfactual in which Uber sets the overall price level, surge pricing increases total welfare by 2.15% of gross revenue. Welfare effects differ substantially across sides of the market: rider surplus increases by 3.57% of gross revenue, whereas driver surplus and the platform's current profits decrease by 0.98% and 0.50% of gross revenue, respectively. Riders at all income levels benefit. Among drivers, those who work long hours are hurt the most, especially women.