Essays in Market Design

In this dissertation, I study three problems in market design: the allocation of resources to schools using deferred acceptance algorithms, the demand reduction of employees on centralized labor markets, and the alleviation of traffic congestion. I show how institutional and behavioral considerations specific to each problem can alleviate several practical limitations faced by current solutions. For the case of traffic congestion, I show experimentally that the proposed solution is effective. In Chapter 1, I investigate how school districts could assign resources to schools when it is desirable to provide stable assignments. An assignment is stable if there is no student currently assigned to a school that would prefer to be assigned to a different school that would admit him if it had the resources. Current assignment algorithms assume resources are fixed. I show how simple modifications to these algorithms produce stable allocations of resources and students to schools. In Chapter 2, I show how the negotiation of salaries within centralized labor markets using deferred acceptance algorithms eliminates the incentives of the hiring firms to strategically reduce their demand. It is well-known that it is impossible to eliminate these incentives for the hiring firms in markets without negotiation of salaries. Chapter 3 investigates how to achieve an efficient distribution of traffic congestion on a road network. Traffic congestion is the product of an externality: drivers do not consider the cost they impose on other drivers by entering a road. In theory, Pigouvian prices would solve the problem. In practice, however, these prices face two important limitations: i) the information required to calculate these prices is unavailable to policy makers and ii) these prices would effectively be new taxes that would transfer resources from the public to the government. I show how to construct congestion prices that retrieve the required information from the drivers and do not transfer resources to the government. I circumvent the limitations of Pigouvian prices by assuming that individuals make some mistakes when selecting routes and have a tendency towards truth-telling. Both assumptions are very robust observations in experimental economics.

A Ride-Sharing System with High Capacity Vehicles and Flexible Meeting Points

In many major cities, fixed route transit systems such as bus and rail serve millions of trips per day. These systems have people collect at common locations (the station or stop), and board at common times (for example according to a predetermined schedule or headway). By using common service locations and times, these modes can consolidate many trips that have similar origins and destinations or overlapping routes. However, the routes are not sensitive to changing travel patterns, and have no way of identifying which trips are going unserved, or are poorly served, by the existing routes. On the opposite end of the spectrum, personal modes of transportation, such as a private vehicle or taxi, offer service to and from the exact origin and destination of a rider, at close to exactly the time they desire to travel. Despite the apparent increased convenience to users, the presence of a large number of small vehicles results in a disorganized, and potentially congested road network during high demand periods. The focus of the research presented in this paper is to develop a system that possesses both the on-demand nature of a personal mode, with the efficiency of shared modes. In this system, users submit their request for travel, but are asked to make small compromises in their origin and destination location by walking to a nearby meeting point, as well as slightly modifying their time of travel, in order to accommodate other passengers. Because the origin and destination location of the request can be adjusted, this is a more general case of the Dial-a-Ride problem with time windows. The solution methodology uses a graph clustering algorithm coupled with a greedy insertion technique. A case study is presented using actual requests for taxi trips in Washington DC, and shows a significant decrease in the number of vehicles required to serve the demand.

Network Development with Bicycle Lanes

Bicycling as an active mode of transport can offer great individual and societal benefits. Allocating space for bicycle facilities is the key to promoting cycling as bicyclists perceive better safety and convenience in separate bikeways. In this thesis, a method is proposed for optimizing the selection and scheduling of capacity enhancements in road networks while also optimizing the allocation of road space to bicycle lanes. The goal is to determine what fraction of the available space should be allocated to bicycles, as the network evolves, in order to minimize the present value of the total cost of the system cost. The allocation method is combined with a genetic algorithm to select and schedule road expansion projects under certain budget constraints.