Selling supplemental information

TL;DR

This paper analyzes how a data broker can optimally sell information to a decision maker under uncertainty, designing mechanisms that maximize surplus extraction even with correlated signals and private information.

Contribution

It characterizes the optimal selling mechanism for information, including screening over signals and handling correlation and private information, extending to general environments.

Findings

Optimal binary signals for each type in binary action settings

Efficient surplus extraction is possible under certain conditions

Conditions where surplus extraction is not feasible

Abstract

I consider an environment in which a decision maker faces uncertainty and privately holds information in the form of a signal about the true state of the world. The decision maker purchases additional information from a data broker before receiving the signal realization. I characterize the data broker's optimal selling mechanism, which involves screening over all possible signals. I allow the space of all signals the data broker can sell to be arbitrarily correlated with the signal the decision maker owns. This plays a key role in designing the optimal menu. In the binary action setting, the data broker extracts the efficient surplus by offering a distinct binary signal for each type. Moreover, this result holds even when the broker does not know the prior distribution over states. In more general environments, I provide conditions on the payoff structure and the decision maker's type space under which the data broker extracts the efficient surplus. I discuss scenarios in which efficient surplus extraction is not possible.