Wu, Haoyang (2019): Profitable Bayesian implementation.
PDF
MPRA_paper_91304.pdf Download (95kB) |
Abstract
In mechanism design theory, a designer would like to implement a desired social choice function which specifies her favorite outcome for each possible profile of all agents' types. Since agents' types are modelled as their private information, what the designer can do is to construct a mechanism and choose an outcome after observing a specific profile of agents' strategies. Traditionally, the designer has no way to adjust agents' types and hence may be in a dilemma in the sense that even if she is not satisfied with some outcome with low profit, she has to announce it because she must obey the mechanism designed by herself. In this paper, we generalize the mechanism design theory to a case where the designer can adjust the type distribution of agents, and propose a novel notion, \emph{i.e.}, profitable Bayesian implementation. After defining a series of notions such as adjusted types, optimal adjustment cost and profitable Bayesian implementability, we propose that the revelation principle does not hold in this generalized case. Finally, we construct an auction example to show that the designer can obtain an expected profit greater than the maximum profit that she can obtain in the traditional optimal auction, at the same time each agent's \emph{ex ante} expected profit is also increased.
Item Type: | MPRA Paper |
---|---|
Original Title: | Profitable Bayesian implementation |
Language: | English |
Keywords: | Mechanism design; Optimal auction; Bayesian Nash implementation. |
Subjects: | D - Microeconomics > D7 - Analysis of Collective Decision-Making > D71 - Social Choice ; Clubs ; Committees ; Associations |
Item ID: | 91304 |
Depositing User: | Haoyang Wu |
Date Deposited: | 07 Jan 2019 18:27 |
Last Modified: | 21 Oct 2019 13:13 |
References: | 1. A. Mas-Colell, M.D. Whinston and J.R. Green, Microeconomic Theory, Oxford University Press, 1995. 2. Y. Narahari et al, Game Theoretic Problems in Network Economics and Mechanism Design Solutions, Springer, 2009. 3. R. Serrano, The Theory of Implementation of Social Choice Function, SIAM Review, vol.46, No.3, 377-414, 2004. 4. R. Myerson, Optimal Auction Design, Mathematics of Operations Research, vol.6, No.1, 58-73, 1981. 5. M. Engers and B. McManus, Charity Auctions, International Economic Review, vol.48, No.3, 953-994, 2007. 6. V. Krishna, Auction Theory (Second Edition), Academic Press, 2010. |
URI: | https://mpra.ub.uni-muenchen.de/id/eprint/91304 |
Available Versions of this Item
-
Generalizing mechanism design theory to a case where agents' types are adjustable. (deposited 24 Dec 2018 06:55)
-
Generalizing mechanism design theory to a case where agents' types are adjustable. (deposited 28 Dec 2018 02:44)
-
Profitable Bayesian implementation. (deposited 29 Dec 2018 17:23)
- Profitable Bayesian implementation. (deposited 07 Jan 2019 18:27) [Currently Displayed]
-
Profitable Bayesian implementation. (deposited 29 Dec 2018 17:23)
-
Generalizing mechanism design theory to a case where agents' types are adjustable. (deposited 28 Dec 2018 02:44)