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Frictions in a Competitive, Regulated Market

$343,978FY2016SBENSF

New York University, New York NY

Investigators

Abstract

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.

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