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Marriott Marquis, Point Loma
Hosted By:
American Economic Association
Behavioral Market Design
Paper Session
Sunday, Jan. 5, 2020 1:00 PM - 3:00 PM (PDT)
- Chair: Shengwu Li, Harvard University
Correlation Neglect in Student-To-School Matching
Abstract
A growing body of evidence suggests that decision-makers fail to account for correlation in signals that they receive. We study the consequences of this behavior for application strategies to schools. In a lab experiment presenting subjects with incentivized school-choice scenarios, we find that subjects generally follow optimal application strategies when schools' admissions decisions are determined independently. However, when schools rely on a common priority---inducing correlation in their decisions---decision making suffers, and students often fail to apply to attractive "safety" options. We document that this pattern holds even within-subject, with significant fractions of participants pursuing different strategies in mathematically equivalent situations that differ only by the presence of correlation. We provide a battery of tests supporting the possibility that this phenomenon is at least partially driven by correlation neglect, and we discuss implications that arise for the design and deployment of student-to-school matching mechanisms.School Choice Under Imperfect Information
Abstract
As in many school districts around the world, prospective high-school students in Ghana are assigned to schools through a centralized system. Using administrative data on applications, we report that virtually all students adopt a weakly dominated strategy, and matching outcomes show that approximately 15\% of students end up unassigned, while almost half of schools have at least 1 vacancy. In order to rationalize choices in this setting, we build and estimate a model, where students engage in a costly search process to acquire information over school characteristics. The key insight of the model is that schooling decisions are exerted without the full examination of all available options, which may lead to sub-optimal choices. Our empirical application documents a substantial welfare loss: distance traveled to schools could be divided by 4. Counterfactual simulations show that if a planner were to restrict choices and assign the highest test score student to the most selective school, welfare would increase by 72\%.Obvious Manipulations
Abstract
A mechanism is strategy-proof if agents can never profitably manipulate, in any state of the world; however, not all non-strategy-proof mechanisms are equally easy to manipulate - some are more ``obviously'' manipulable than others. We propose a formal definition of an obvious manipulation and argue that it may be advantageous for designers to tolerate some manipulations, so long as they are non-obvious. By doing so, improvements can be achieved on other key dimensions, such as efficiency and fairness, without significantly compromising incentives. We classify common non-strategy-proof mechanisms as either obviously manipulable (OM) or not obviously manipulable (NOM), and show that this distinction is both tractable and in-line with empirical realities regarding the success of manipulable mechanisms in practical market design settings.JEL Classifications
- D9 - Micro-Based Behavioral Economics
- D4 - Market Structure, Pricing, and Design