By: |
Dipjyoti Majumdar (Department of Economics, Concordia University) |
Abstract: |
We study incentive issues related to two-sided one-to-one stable matching
problem after weakening the notion of strategy-proofness to Ordinal Bayesian
Incentive Compatibility (OBIC). Under OBIC, truthtelling is required to
maximize the expected utility of every agent, expected utility being computed
with respect to the agent’s prior beliefs and under the assumption that
everybody else is also telling the truth. We show that when preferences are
unrestricted there exists no matching procedure that is both stable and OBIC.
Next preferences are restricted to the case where remaining single is the
worst alternative for every agent. We show that in this case, if agents have
uniform priors then the stable matchings generated by “deferred acceptance
algorithms” are OBIC. However, for generic priors there are no matching
procedures that are both stable and OBIC even with restricted preferences. |
Keywords: |
stable matching, incentives, strategy-proofness |
JEL: |
C72 D72 |
Date: |
2003–08 |
URL: |
http://d.repec.org/n?u=RePEc:crd:wpaper:05001&r=gth |