NSF/BSF: Strategic Information Disclosure

This award funds research in the economic theory of information disclosure. The goal is to develop and analyze three separate models of how people interact in employment and market situations. The first considers whether a manager of a publicly traded firm who seeks to maximize share prices should disclose everything she knows today, or whether she should delay disclosure until she has more information.

The second project examines whether a manager is more likely to disclose when she is more confident that the information is accurate. The third project considers how an entrepreneur might reveal information to investors and regulators. The results of this project will advance the national prosperity because it will help us better understand the effects of different regulations on publicly traded firms.

Voluntary information disclosure by agents is a common feature of markets, ranging from public information disclosure by managers of public firms that affects stock prices, to entrepreneurs disclosing information to influence investors and customers, to politicians trying to influence voters. While most previous models have studied relatively simple, mostly static disclosure problems, this proposal explores more realistic and complex environments.

The first project analyzes models of agents facing a dynamic problem: disclose information now or later. In the model, a public firm's value follows a random walk. At each point in time, a manager of the firm learns with some probability the current value and can disclose it credibly.

The manager maximizes a weighted average of stock prices, and the market sets prices rationally. The project explores how dynamic considerations affect equilibrium disclosure, how regulation requiring timely disclosure affects information dissemination, and incentives to acquire information in the first place. The second project captures another realistic aspect of disclosure: that when an agent reveals information, it is often just a noisy estimate of the true value.

Moreover, the market may be worried that the agent is hiding more accurate information. It answers which types of signals (more or less accurate) the manager is more likely to disclose. It describes the correlation between prices and residual uncertainty about the true value conditional on disclosed information.

The third project studies a model of an agent trying to influence multiple decisions by receivers. For example, an entrepreneur may reveal information to investors and to regulators to influence decisions by both. It aims to discover under what conditions sequential information disclosure can strictly improve upon single-shot disclosure and the optimal order of communication.

This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.