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：竞争性，受监管的市场中的摩擦。这是各地出租车市场发生巨大转型的时期，Uber和Lyft等新技术参与者的兴起。纽约市等地方的出租车市场在某些重要方面类似于竞争市场。特别是没有市场力量的大量独立参与者的存在。但是，它们还具有障碍或摩擦，以使这种竞争的平稳运作。其中一些摩擦是监管的，例如进入，定价和所有权的限制。有些是产品交付方式的功能。例如，有一个重要的“匹配摩擦”源于这样一个事实，即出租车司机对潜在乘客的位置的了解有限，从而导致浪费搜索或等待。该项目开发并估算了一个试图测量这些摩擦并讨论可能减少这些扭曲的政策的模型。它还考虑了Uber等参赛者的影响。 PIS研究纽约市是由于该市场的一些有趣的数据以及一些有趣的特征，因此研究了纽约市。该项目的第一部分估计了一个动态的一般平衡模型，并与纽约市出租车市场的摩擦相匹配。该项目的第二部分探讨了更加依赖数据中详细的空间信息的问题。 PI讨论了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应对直接观察需求的潜力的局限性。由于观察到出租车搜索乘客的时间，因此PI可以使用搜索是一个定义明确的空间过程来恢复等待客户的数量。在供应方面，潜在的驾驶员每天做出每日决策和每小时停止决定。然后必须将这些汇总为与均衡收入一致。等待时间和出租车的数量是内源性确定的，这是该市场竞争均衡的一部分。 PI使用纽约市的数据提供有关从2010年到2013年的每一次出租车旅行的信息。他们提出反事实的放松入境和所有权限制。他们还提出了一种改变匹配技术的反事实：将空出租车送往最近的乘客的集中调度员。他们研究了乘客和出租车的等待时间的效率提高，这是调度员控制的市场比例的函数。这与思考Uber等公司的影响有关。在项目的第二部分中，PIS建议系统地探讨在不同类型的集中匹配程序下结果如何变化，以更好地了解各种摩擦的作用和重要性。他们还可以获取有关出租车之间（平衡）协调程度的信息。可以有多个具有不同市场细分程度的帕累托级平衡。该项目旨在评估该市场细分的影响。该项目对纽约市出租车市场的明显政策影响有许多潜在的影响。它可以允许研究人员量化某些现有法规的扭曲，例如票价结构的僵化性。随着技术的最新进展，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可以探索这种替代组织的潜力。这些与其他具有空间摩擦​​的市场相关，需要快速提供服务。