Frictions in a Competitive, Regulated Market

竞争激烈、受监管的市场中的摩擦

• 批准号: 1558857
• 负责人: Guillaume Frechette
• 金额: $ 34.4万
• 依托单位: New York University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2016
• 资助国家: 美国
• 起止时间: 2016-06-01 至 2021-05-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1558857&HistoricalAwards=false
• 关键词: Frictions; Competitive; Regulated; Market

Title: Frictions in a Competitive, Regulated Market.This is a time of great transformation in taxi markets everywhere, with the rise of new technology entrants such as Uber and Lyft. Taxi markets in places like New York City resemble a competitive market in some important ways; particularly the presence of a large number of independent participants who do not have market power. However, they also feature impediments, or frictions, to the smooth functioning of such competition. Some of these frictions are regulatory, such as the limits to entry, pricing, and ownership. Some are features of the way the products are delivered. For instance, there is an important "matching friction" that derives from the fact that taxi drivers have limited knowledge about the location of potential passengers, leading to wasteful search or waiting. This project develops and estimates a model that attempts to measure these frictions and discusses policies that may reduce these distortions. It also considers the effects of entrants such as Uber. The PIs study New York City because of the availability of extremely detailed data and because of some interesting features of that market. The first part of the project estimates a dynamic general equilibrium model with matching frictions of the New York City taxi-cab market. The second part of the project explores questions that rely more intensively on the detailed spatial information in the data. The PIs discuss how well drivers coordinate their decisions, and how well they use available information. They propose a novel approach to deal with limitations on the potential to directly observe demand. Because the amount of time a taxi searches for passengers is observed, the PIs can recover the number of waiting customers by using the fact that search is a well-defined spatial process. On the supply-side, potential drivers make a daily entry decision and an hourly stopping decision. These must then be aggregated to be consistent with equilibrium earnings. The wait time and the number of taxis are jointly determined endogenously as part of the competitive equilibrium in this market. The PIs use data from New York City with information on every single cab trip from 2010 to 2013. They propose counterfactuals relaxing entry and ownership restrictions. They also propose a counterfactual that changes the matching technology: a centralized dispatcher who sends empty cabs to the closest passenger. They examine gains in efficiency with reductions in wait times for both passengers and taxis as a function of the fraction of the market controlled by the dispatcher. This is relevant for thinking about the effect of firms such as Uber. In the second part of the project the PIs propose to systematically explore how outcomes change under different types of centralized matching procedures to better understand the role and importance of various frictions. They can also obtain information about the (equilibrium) degree of coordination among taxis. There can be multiple Pareto-ranked equilibria with different degrees of market segmentation. The project aims to evaluate the effects of this market segmentation. This project has many potential impacts beyond the obvious policy implications for the NYC taxi market. It can allow researchers to quantify the distortions of some existing regulations, such as the inflexibility of the fare structures. With recent advances in technology, many markets are now faced with the possibility of alternative modes of organization. This structural approach allows the PIs to explore the potential for such alternative organization. These have relevance for other markets with spatial frictions and a need for rapid delivery of service.

标题：竞争激烈、受监管的市场中的摩擦。随着 Uber 和 Lyft 等新技术进入者的崛起，各地出租车市场正经历着巨大变革。纽约市等地的出租车市场在某些重要方面类似于竞争市场。特别是存在大量不具备市场支配力的独立参与者。然而，它们也存在阻碍此类竞争顺利进行的障碍或摩擦。其中一些摩擦是监管方面的，例如进入、定价和所有权的限制。有些是产品交付方式的特征。例如，存在一个重要的“匹配摩擦”，源于出租车司机对潜在乘客位置的了解有限，导致浪费搜索或等待。该项目开发并估计了一个模型，试图衡量这些摩擦并讨论可能减少这些扭曲的政策。它还考虑了 Uber 等进入者的影响。 PI 研究纽约市是因为可以获得极其详细的数据并且因为该市场有一些有趣的特征。该项目的第一部分估计了动态一般均衡模型以及纽约市出租车市场的匹配摩擦。该项目的第二部分探讨了更依赖于数据中详细空间信息的问题。 PI 讨论驾驶员如何协调他们的决策，以及他们如何使用可用信息。他们提出了一种新颖的方法来解决直接观察需求潜力的限制。由于出租车搜索乘客的时间是可以观察到的，PI 可以利用搜索是一个明确定义的空间过程这一事实来恢复等待乘客的数量。在供应方面，潜在司机每天做出进入决定并每小时做出停车决定。然后必须将这些汇总以与均衡收益保持一致。等待时间和出租车数量是由市场竞争均衡的内生因素共同决定的。 PI 使用来自纽约市的数据，其中包含 2010 年至 2013 年每次出租车出行的信息。他们提出了放宽准入和所有权限制的反事实假设。他们还提出了一个改变匹配技术的反事实：一个集中调度员将空出租车发送给最近的乘客。他们研究了乘客和出租车等待时间减少所带来的效率提升与调度员控制的市场份额之间的关系。这与思考 Uber 等公司的影响相关。在该项目的第二部分中，PI 建议系统地探索在不同类型的集中匹配程序下结果如何变化，以更好地理解各种摩擦的作用和重要性。他们还可以获得有关出租车之间协调（平衡）程度的信息。可能存在多个具有不同程度的市场细分的帕累托均衡。该项目旨在评估这种市场细分的影响。除了对纽约市出租车市场的明显政策影响之外，该项目还有许多潜在影响。它可以让研究人员量化一些现有法规的扭曲，例如票价结构的不灵活性。随着技术的最新进步，许多市场现在面临着替代组织模式的可能性。这种结构方法使 PI 能够探索这种替代组织的潜力。这些与具有空间摩擦​​和需要快速提供服务的其他市场相关。