Résumé
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.
Codes JEL
- D42: Monopoly
- D81: Criteria for Decision-Making under Risk and Uncertainty
- D82: Asymmetric and Private Information • Mechanism Design
Référence
Dirk Bergemann, Alex Smolin et Alessandro Bonatti, « The Design and Price of Information », American Economic Review, vol. 108, n° 1, 2018, p. 1–48.
Publié dans
American Economic Review, vol. 108, n° 1, 2018, p. 1–48