We host market design seminars for researchers.
*All times are Japan Standard Time (JST).
*Unless otherwise mentioned, the seminars will be held online using Zoom (pre-registration system).
*Presentations are in ENGLISH.
*Please refrain from taking pictures, recording audio and video.
*Please do not reproduce the contents or share the Zoom joining URL with a third party.
Please use the following link for registration.
*Registration is required only for the first time. The same meeting URL can be used for this UTMD seminar series.
[Dec. 9, 2021] Jeremy Fox (Rice University)
Date & Time: 2021/12/9(Thu) 9:00-10:30am
Title: Measuring the Welfare Gains from Cardinal-Preference Pseudomarkets in School Choice
Abstract: We compare cardinal-preference and ordinal-preference mechanisms for assignment problems such as school choice, with a focus on a variant of the pseudomarket mechanism of Hylland and Zeckhauser (1979). We introduce and theoretically analyze a variant of the pseudomarket mechanism that has an equilibrium selection rule. We also introduce a computer algorithm to compute the implied stochastic assignment. We estimate cardinal preferences over schools using data on student submissions of rank ordered lists of schools in Seattle. Using these estimated preferences, we measure the welfare gains from using the pseudomarket mechanism instead of the ordinally-efficient probabilistic serial mechanism.
[Dec. 23, 2021] Zhen Lian (Cornell University)
Date & Time: 2021/12/23(Thu) 9:00-10:30am
Title: Autonomous Vehicle Market Design
Abstract: We develop an economic model of autonomous vehicle (AV) ride-hailing markets in which uncertain aggregate demand is served with a combination of a fixed fleet of AVs and an unlimited potential supply of human drivers (HVs). We analyze market outcomes under two dispatch platform designs (common platform vs. independent platforms) and two levels of AV competition (monopoly AV vs. competitive AV). A key result of our analysis is that the lower cost of AVs does not necessarily translate into lower prices; the price impact of AVs is ambiguous and depends critically on both the dispatch platform design and the level of competition. In the extreme case, we show if AVs and HVs operate on independent dispatch platforms and there is a monopoly AVs supplier, then prices are even higher than they are in a pure HV market. When AVs are introduced on a common dispatch platform, we show that whether the equilibrium price is reduced depends on the level of AV competition. If AVs are owned by a monopoly firm, then the equilibrium price is the same as in a pure HV market. In fact, the only market design that leads to unambiguously lower prices in all demand scenarios is when AVs and HVs operate on a common dispatch platform and the AV supply is competitive. Our results illustrate the critical role market design and competition plays in realizing potential welfare gains from AVs.
[Jan. 13, 2022] Wolfgang Pesendorfer (Princeton University)
Date & Time: 2022/1/13(Thu) 9:00-10:30am
[Feb. 17, 2022] Rakesh Vohra (University of Pennsylvania)
Date & Time: 2022/2/17(Thu) 9:00-10:45am
[Feb. 21, 2022] Ayumi Igarashi (National Institute of Informatics)
Date & Time: 2022/2/21(Mon) 10:25am-12:10
[Mar. 3, 2022] Morimitsu Kurino (Keio University)
Date & Time: 2022/03/03(Thu) 15:30-17:00
(There is a possibility to be held in-person depending on COVID-19 situation.)
[Dec. 2, 2021] Aytek Erdil (University of Cambridge)
Date & Time: 2021/12/2(Thu) 17:00-18:30
Title: Widening Access with Smart Targets
Abstract: In the UK, universities advertise the degree majors (courses) they offer, and over 700,000 students apply directly to their chosen courses out of over 30,000 courses available. For each of their courses, universities have a target number of students to admit. Some universities also have a target number of disadvantaged students to admit in each course. Depending on student demand, each university adjusts these course-level targets over a long admissions calendar, and makes offers with the aim of fulfilling its aggregate (i.e., university-level) targets.
We show that it is possible to reorganise this market with a centralised system which maintains universities’ flexibility to optimally adjust their targets. We design a strategy-proof mechanism that finds a stable matching in a market where students pursue their most preferred courses and universities aim to meet their targets with the best applicants possible.