Optimal truncation in matching markets

- We explore strategic behavior in 1-1 matching markets with incomplete information.
- In large, uniform markets, women optimally truncate most of their preference list.
- This qualifies large market results suggesting truth-telling is “close” to optimal.
- Reduced risk aversion and correlation across preferences lead to more truncation.

Although no stable matching mechanism can induce truth-telling as a dominant strategy for all participants (Roth, 1982), recent studies have presented conditions under which truthful reporting by all agents is close to optimal (Immorlica and Mahdian, 2005; Kojima and Pathak, 2009; Lee, 2011). Our results demonstrate that in large, uniform markets using the Men-Proposing Deferred Acceptance Algorithm, each woman's best response to truthful behavior by all other agents is to truncate her list substantially. In fact, the optimal degree of truncation for such a woman goes to 100% of her list as the market size grows large. In general one-to-one markets we provide comparative statics for optimal truncation strategies: reduction in risk aversion and reduced correlation across preferences each lead agents to truncate more. So while several recent papers focused on the limits of strategic manipulation, our results serve as a reminder that without pre-conditions ensuring truthful reporting, there exists a potential for significant manipulation even in settings where agents have little information.