Delegated Information Provision

TL;DR

This paper models a delegation framework where a designer restricts an experimenter's ability to manipulate information, balancing persuasion incentives with truthful information transmission, with applications to privacy in recommender systems.

Contribution

It characterizes optimal experiment delegation under incentives, introducing double censorship and demonstrating benefits of constrained persuasion in information design.

Findings

Double censorship involves an intermediate pooling region.

Imposing delegation constraints benefits the designer.

Privacy constraints can naturally emerge to prevent persuasion.

Abstract

A designer relies on an experimenter to provide information to a decision maker, but the experimenter has incentives to persuade rather than merely transmit information. Anticipating this motive, the designer can restrict the set of admissible experiments, but cannot prevent the experimenter from garbling any admissible experiment. We model this situation as delegation over experiments. The optimal delegation set is obtained by comparing maximally informative experiments among those the experimenter has no incentive to garble. When the experimenter's preferences are $S$-shaped, we characterize these experiments as double censorship. Relative to the full-delegation benchmark, double censorship features an intermediate pooling region, inducing a smaller pooling region for the highest states. We show that the designer strictly benefits from imposing a nontrivial delegation set that constrains persuasion while retaining information provision. Applying our results to recommender systems, we show that privacy constraints can arise endogenously to protect consumers against persuasion.