Fractional Top Trading Cycle on the Full Preference Domain

Jingsheng Yu and Jun Zhang

Papers from arXiv.org

Abstract: Efficiency and fairness are two desiderata in market design. Fairness requires randomization in many environments. Observing the inadequacy of Top Trading Cycle (TTC) to incorporate randomization, Yu and Zhang (2020) propose the class of Fractional TTC mechanisms to solve random allocation problems efficiently and fairly. The assumption of strict preferences in the paper restricts the application scope. This paper extends Fractional TTC to the full preference domain in which agents can be indifferent between objects. Efficiency and fairness of Fractional TTC are preserved. As a corollary, we obtain an extension of the probabilistic serial mechanism in the house allocation model to the full preference domain. Our extension does not require any knowledge beyond elementary computation.

Date: 2020-05
New Economics Papers: this item is included in nep-des
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
http://arxiv.org/pdf/2005.09340 Latest version (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:arx:papers:2005.09340

Access Statistics for this paper

More papers in Papers from arXiv.org
Bibliographic data for series maintained by arXiv administrators ().