Essays on robust mechanism design

Long, Yan (2016) Essays on robust mechanism design. PhD thesis, University of Glasgow.

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Abstract

Chapter 1: Under the average common value function, we select almost uniquely the mechanism that gives the seller the largest portion of the true value in the worst situation among all the direct mechanisms that are feasible, ex-post implementable and individually rational.
Chapter 2: Strategy-proof, budget balanced, anonymous, envy-free linear mechanisms assign p identical objects to n agents. The efficiency loss is the largest ratio of surplus loss to efficient surplus, over all profiles of non-negative valuations. The smallest efficiency loss is uniquely achieved by the following simple allocation rule: assigns one object to each of the p−1 agents with the highest valuation, a large probability to the agent with the pth highest valuation, and the remaining probability to the agent with the (p+1)th highest valuation. When “envy freeness” is replaced by the weaker condition “voluntary participation”, the optimal mechanism differs only when p is much less than n.
Chapter 3: One group is to be selected among a set of agents. Agents have preferences over the size of the group if they are selected; and preferences over size as well as the “stand-outside” option are single-peaked. We take a mechanism design approach and search for group selection mechanisms that are efficient, strategy-proof and individually rational. Two classes of such mechanisms are presented. The proposing mechanism allows agents to either maintain or shrink the group size following a fixed priority, and is characterized by group strategy-proofness. The voting mechanism enlarges the group size in each voting round, and achieves at least half of the maximum group size compatible with individual rationality.

Item Type: Thesis (PhD)
Qualification Level: Doctoral
Subjects: H Social Sciences > HB Economic Theory
Colleges/Schools: College of Social Sciences > Adam Smith Business School > Economics
Supervisor's Name: Moulin, Professor Herve
Date of Award: 2016
Depositing User: Ms Yan Long
Unique ID: glathesis:2016-7472
Copyright: Copyright of this thesis is held by the author.
Date Deposited: 25 Aug 2016 15:32
Last Modified: 23 Sep 2016 08:05
URI: http://theses.gla.ac.uk/id/eprint/7472

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