Approximate Competitive Equilibrium from Equal Incomes

Approximate Competitive Equilibrium from Equal Incomes (A-CEEI) is a procedure for fair item assignment. It was developed by Eric Budish.[1]

Background

CEEI (Competitive Equilibrium from Equal Incomes) is a fundamental mechanism for fair division of divisible resources. It works in two steps:

The equilibrium allocation is provably envy free and Pareto efficient.

Unfortunately, when there are indivisibilities, a CEEI does not always exist, so it cannot be used directly for fair item assignment. However, it can be approximated, and the approximation has good fairness, efficiency and strategic properties.

Assumptions

A-CEEI only assumes that the agents know how to rank bundles of items. The ranking need not be weakly additive nor even monotone.

Procedure

Guarantees

The allocation satisfies the following properties:

Moreover, the A-CEEI mechanism is strategyproof "in the large": when there are many agents, each agent has only a small influence on the price, so the agents act as price takers. Then, it is optimal for each agent to report his true valuations, since it allows the mechanism to give him an optimal bundle given the prices.

Computation

The A-CEEI allocation is hard to compute: it is PPAD complete.[2]

However, in realistic-size problems, A-CEEI can be computed using a two-level search process:

  1. Master level: the center uses tabu search to suggest prices;
  2. Agent level: mixed integer programs are solved to find agent demands at the current prices.

The agent-level program can be done in parallel for all agents, so this method scales near-optimally in the number of processors.[3]

The mechanism has been considered for the task of assigning students to courses at the Wharton School of the University of Pennsylvania. [4]

Comparison to maximum-Nash welfare

The Maximum-Nash-Welfare (MNW) algorithm finds an allocation that maximizes the product of the agents' utilities. It is similar to A-CEEI in several respects:[5]

However, A-CEEI has several advantages:

On the flip side, the disadvantage of A-CEEI is that the returned allocation is not Pareto-efficient, since some items remain unallocated (it is Pareto-efficient only with respect to the allocated items).

In practice, A-CEEI is better when there are many agents, each of whom may get only a small number of items. A typical application is when the agents are students and the items are positions in courses. MNW is better when there are few agents and many items, such as in inheritance division.

Comparison to competitive equilibrium

A-CEEI (and CEEI in general) is related, but not identical, to the concept of competitive equilibrium.

See also

References

  1. Budish, Eric (2011). "The Combinatorial Assignment Problem: Approximate Competitive Equilibrium from Equal Incomes". Journal of Political Economy. 119 (6): 1061. doi:10.1086/664613.
  2. Othman, Abraham; Papadimitriou, Christos; Rubinstein, Aviad (2016). "The Complexity of Fairness Through Equilibrium". ACM Transactions on Economics and Computation. 4 (4): 1. doi:10.1145/2956583.
  3. Abraham Othman and Tuomas Sandholm and Eric Budish (2010). Finding approximate competitive equilibria: efficient and fair course allocation (PDF). AAMAS '10. acm.org
  4. Budish, Eric; Kessler, Judd B. (2016). "Bringing Real Market Participants' Real Preferences into the Lab: An Experiment that Changed the Course Allocation Mechanism at Wharton" (PDF).
  5. Caragiannis, Ioannis; Kurokawa, David; Moulin, Hervé; Procaccia, Ariel D.; Shah, Nisarg; Wang, Junxing (2016). The Unreasonable Fairness of Maximum Nash Welfare. Proceedings of the 2016 ACM Conference on Economics and Computation - EC '16. p. 305. ISBN 9781450339360. doi:10.1145/2940716.2940726.
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