Research Article
Can “Complex” Market Designs Make it from Theory to Practice? Changing the Course Allocation Mechanism at Wharton
@ARTICLE{10.4108/eai.8-8-2015.2261075, author={Eric Budish}, title={Can “Complex” Market Designs Make it from Theory to Practice? Changing the Course Allocation Mechanism at Wharton}, journal={EAI Endorsed Transactions on Serious Games}, volume={3}, number={11}, publisher={ACM}, journal_a={SG}, year={2015}, month={8}, keywords={market design, matching, combinatorial allocation, course allocation, scheduling, tabu search, competitive equilibrium, experiments, preference elicitation, user interface design}, doi={10.4108/eai.8-8-2015.2261075} }
- Eric Budish
Year: 2015
Can “Complex” Market Designs Make it from Theory to Practice? Changing the Course Allocation Mechanism at Wharton
SG
EAI
DOI: 10.4108/eai.8-8-2015.2261075
Abstract
Budish (2011) proposes a new mechanism for the problem of combinatorial assignment -- e.g., assigning students to schedules of courses -- called approximate competitive equilibrium from equal incomes (CEEI). While the CEEI mechanism satisfies attractive properties of efficiency, fairness, and incentives, it is “complicated” in several ways that one might reasonably wonder whether the theory could actually be implemented in the real world.
This talk reports on two papers (Budish and Kessler, 2015; Budish et al., 2015) that helped bring this complex market design theory to successful implementation in practice, at the Wharton School at the University of Pennsylvania. The first paper reports on experiments conducted at Wharton to test the CEEI mechanism. In addition to showing that the CEEI mechanism improved the efficiency and fairness of the allocation, the experiment also serves as a roadmap for other market design researchers seeking to test complex mechanisms in practice. The second paper reports on the computational and economic engineering work involved in actually implementing the mechanism in practice. This involved modifications of the CEEI mechanism to deal with some of the issues caused by approximations in the theory, and a computational procedure that performs a massive parallel heuristic search, solving billions of mixed-integer programs along the way, to output an approximate competitive equilibrium in the fake-money economy for courses.
Copyright © 2015 E. Budish, licensed to EAI. This is an open access article distributed under the terms of the Creative Commons Attribution licence (http://creativecommons.org/licenses/by/3.0/), which permits unlimited use, distribution and reproduction in any medium so long as the original work is properly cited.