Information acquisition and full surplus extraction |
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Authors: | Sushil Bikhchandani |
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Affiliation: | Anderson School of Management, UCLA, Los Angeles, CA 90095-1481, United States |
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Abstract: | It is well known that when agents' types are correlated, the mechanism designer can extract the entire surplus. This creates an incentive for agents to acquire information about other agents' types. Robust lotteries (are payment schemes that) support full extraction and partially robust lotteries support efficient implementation in the presence of information acquisition opportunities. Necessary and sufficient conditions for existence of robust and partially robust lotteries are derived. If an agent's information signal spans other agents' types then robust lotteries do not exist. However, if all agents report their signal realizations then robust lotteries exist in an extended type space. |
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Keywords: | D44 D82 |
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