Information (Design), Black Markets, and Congestion
Friday, Jan. 3, 2020 2:30 PM - 4:30 PM (PDT)
- Chair: Dorothea Kuebler, WZB Berlin Social Science Center
Information Design in Dynamic Contests: An Experimental Study
AbstractIn many real-world innovation tournaments and R&D races, the feasibility of the end goal is uncertain.
We present a novel real-effort experiment to study the role of information in these dynamic winner-takes-all contests. Information about the partial progress of competitors plays a dual role: it can provide encouragement about the feasibility of the underlying task, but it can also make laggards reduce their efforts or quit the contest altogether because their chances of winning have become slimmer. Our experimental design embeds this task uncertainty into a dynamic environment and examines how several information disclosure policies perform on several dimensions. Our findings detail the tradeoffs involved in using different policies, and provide recommendations for contest designers on which disclosure mechanisms to use. We also study the effect of these mechanisms on the welfare of participants and show that it is generally difficult to use information to simultaneously improve this welfare as well as the objective of the designer. We describe how our results deviate from theoretical predictions and discuss some of the possible drivers of these discrepancies.
How to Avoid Black Markets for Appointments with Online Booking Systems
AbstractAllocating appointment slots is presented as a new application for market design. We consider online booking systems that are commonly used by public authorities to allocate appointments for visa interviews, passport renewals, driver's licenses, etc. We document that black markets for appointments have developed in many parts of the world. Scalpers book the appointments that are offered for free and sell the slots to appointment seekers. We model the existing first-come-first-served booking system and propose an alternative system. The alternative system collects applications for slots for a certain time period and then randomly allocates slots to applicants. We investigate the two systems under conditions of low and high demand for slots. The theory predicts and lab experiments confirm that scalpers profitably book and sell slots under the current system with high demand, but that they are not active in the proposed new system under both demand conditions.
Application Costs and Congestion in Matching Markets
AbstractA matching market often requires recruiting agents, or “programs," to costly screen “applicants," and congestion increases with the number of applicants to be screened. We investigate the role of application costs: Higher costs reduce congestion by discouraging applicants from applying to certain programs; however, they may harm match quality. In a multiple-elicitation experiment conducted in a real-life matching market, we implement variants of the Gale-Shapley Deferred-Acceptance mechanism with different application costs. Our experimental and structural estimates show that a (low) application cost effectively reduces congestion without harming match quality.
- D9 - Micro-Based Behavioral Economics
- C9 - Design of Experiments