Wu, Haoyang (2019): Profitable Bayesian implementation in one-shot mechanism settings.
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Abstract
In the 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. Traditionally, the designer 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 investigate a case where the designer can induce each agent to adjust his type in a one-shot mechanism. We propose that for a profitable Bayesian implementable social choice function, the designer may escape from the above-mentioned dilemma by spending the optimal adjustment cost and obtain a higher profit. Finally, we construct an example to show that the designer can breakthrough the limit of expected profit which she can obtain at most in the traditional optimal auction model.
Item Type: | MPRA Paper |
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Original Title: | Profitable Bayesian implementation in one-shot mechanism settings |
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: | 94242 |
Depositing User: | Haoyang Wu |
Date Deposited: | 10 Jun 2019 08:57 |
Last Modified: | 02 Oct 2019 10:07 |
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. M. Engers and B. McManus, Charity Auctions, International Economic Review, vol.48, No.3, 953-994, 2007. 5. R. Myerson, Optimal Auction Design, Mathematics of Operations Research, vol.6, No.1, 58-73, 1981. 6. V. Krishna, Auction Theory (Second Edition), Academic Press, 2010. |
URI: | https://mpra.ub.uni-muenchen.de/id/eprint/94242 |
Available Versions of this Item
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Generalizing mechanism design theory to a case where agents' types are adjustable. (deposited 24 Dec 2018 06:55)
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Generalizing mechanism design theory to a case where agents' types are adjustable. (deposited 28 Dec 2018 02:44)
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Profitable Bayesian implementation. (deposited 29 Dec 2018 17:23)
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Profitable Bayesian implementation. (deposited 07 Jan 2019 18:27)
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Profitable Bayesian implementation in one-shot mechanism settings. (deposited 06 Feb 2019 20:49)
- Profitable Bayesian implementation in one-shot mechanism settings. (deposited 10 Jun 2019 08:57) [Currently Displayed]
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Profitable Bayesian implementation in one-shot mechanism settings. (deposited 06 Feb 2019 20:49)
-
Profitable Bayesian implementation. (deposited 07 Jan 2019 18:27)
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Profitable Bayesian implementation. (deposited 29 Dec 2018 17:23)
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Generalizing mechanism design theory to a case where agents' types are adjustable. (deposited 28 Dec 2018 02:44)