CFDP 2049R

The Design and Price of Information


Publication Date: July 2016

Revision Date: June 2017

Pages: 62


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.


Information design, Price of information, Statistical experiments, Mechanism design, Price discrimination, Hypothesis testing.

JEL Classification Codes: D42, D82, D83

JEL Classification Codes: D42D82D83