Constrained School Choice



up to qs1 seats to its proposers one at a time following the priority order fs . Remaining
students are rejected. Let q
s2 denote the number of available seats at school s. If qs2 = 0
then school s is removed.

Step l, l 2: Each student i that is rejected in Step l - 1 proposes to the next school
in the ordered list Q
i (if there is no such school then i remains unassigned). School s
assigns up to q
sl seats to its (new) proposers one at a time following the priority order fs.
Remaining students are rejected. Let q
sl+1 denote the number of available seats at school
s. If q
sl+1 = 0 then school s is removed.

The algorithm stops when no student is rejected or all schools have been removed. Any
remaining student remains unassigned. Let β(Q) denote the matching. The mechanism
β is the Boston mechanism, or BOS for short. It is well known that BOS is individually
rational, non wasteful, and Pareto-efficient. It is, however, neither stable nor strategy-
proof.

3.2 The Gale-Shapley Deferred Acceptance Algorithm

The deferred acceptance (DA) algorithm was introduced by Gale and Shapley (1962).
Let Q be a profile of ordered lists submitted by the students. The DA algorithm finds a
matching through the following steps.

Step 1: Each student i proposes to the school that is ranked first in Qi (if there is no
such school then i remains unassigned). Each school s tentatively assigns up to q
s seats
to its proposers one at a time following the priority order f
s . Remaining students are
rejected.

Step l, l 2: Each student i that is rejected in Step l - 1 proposes to the next school
in the ordered list Q
i (if there is no such school then i remains unassigned). Each school
s considers the new proposers and the students that have a (tentative) seat at s. School
s tentatively assigns up to q
s seats to these students one at a time following the priority
order f
s . Remaining students are rejected.

The algorithm stops when no student is rejected. Each student is assigned to his final
tentative school. Let γ(Q) denote the matching. The mechanism γ is the Student-Optimal
Stable mechanism, or SOSM for short. SOSM is a stable mechanism that is Pareto
superior to any other stable matching mechanism (Gale and Shapley, 1962). An additional
important property of SOSM is that it is strategy-proof (Dubins and Freedman, 1981;
Roth, 1982b). However, it is not Pareto-efficient.

10



More intriguing information

1. Behaviour-based Knowledge Systems: An Epigenetic Path from Behaviour to Knowledge
2. EXECUTIVE SUMMARIES
3. La mobilité de la main-d'œuvre en Europe : le rôle des caractéristiques individuelles et de l'hétérogénéité entre pays
4. Exchange Rate Uncertainty and Trade Growth - A Comparison of Linear and Nonlinear (Forecasting) Models
5. LABOR POLICY AND THE OVER-ALL ECONOMY
6. AN EXPLORATION OF THE NEED FOR AND COST OF SELECTED TRADE FACILITATION MEASURES IN ASIA AND THE PACIFIC IN THE CONTEXT OF THE WTO NEGOTIATIONS
7. Initial Public Offerings and Venture Capital in Germany
8. Behavior-Based Early Language Development on a Humanoid Robot
9. Elicited bid functions in (a)symmetric first-price auctions
10. Credit Market Competition and Capital Regulation
11. Mean Variance Optimization of Non-Linear Systems and Worst-case Analysis
12. The name is absent
13. The name is absent
14. Trade Liberalization, Firm Performance and Labour Market Outcomes in the Developing World: What Can We Learn from Micro-LevelData?
15. Weather Forecasting for Weather Derivatives
16. The name is absent
17. he Effect of Phosphorylation on the Electron Capture Dissociation of Peptide Ions
18. The name is absent
19. Financial Markets and International Risk Sharing
20. On the Relation between Robust and Bayesian Decision Making