The Design and Price of Information

Dirk Bergemann, Alessandro Bonatti and Alex Smolin

No 2049R, Cowles Foundation Discussion Papers from Cowles Foundation for Research in Economics, Yale University

Abstract: A data buyer faces a decision problem under uncertainty. He can augment his initial private information with supplemental data from a data seller. His willingness to pay for supplemental data is determined by the quality of his initial private information. The data seller optimally offers a menu of statistical experiments. We establish the properties that any revenue-maximizing menu of experiments must satisfy. Every experiment is a non-dispersed stochastic matrix, and every menu contains a fully informative experiment. In the cases of binary states and actions, or binary types, we provide an explicit construction of the optimal menu of experiments.

Keywords: Information design; Price of information; Statistical experiments; Mechanism design; Price discrimination; Hypothesis testing (search for similar items in EconPapers)
JEL-codes: D42 D82 D83 (search for similar items in EconPapers)
Pages: 62 pages
Date: 2017-06
New Economics Papers: this item is included in nep-com, nep-exp and nep-mic
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

Published in American Economic Review (January 2018)

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Related works:
Journal Article: The Design and Price of Information (2018)
Working Paper: The Design and Price of Information (2016)
Working Paper: The Design and Price of Information (2016)
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