This paper analyzes equlibrium and welfare for a tractable class of economies (games) with externalities, strategic complementarity or substitutability, and heterogenous information. First, we characterize the equilibrium use of information; complementarity heightens the sensitivity of equilibrium actions to public information, raising aggregate volatility, whereas substitutability heightens the sensitivity to private information, cross-sectional dispersion. Next, we define and characterize an efficiency benchmark designed to address whether the equilibrium use of information is optimal from a social perspective; the efficient use of information reflects the social value of aligning choices across agents. Finally, we examine the comparative statics of equilibrium welfare with respect to the information structure; the social value of information is best understood by classifying economies according to the inefficiency, if any, in the equilibrium use of information. We conclude with a few applications, including production externalities, beauty contests, business cycles, and large Cournot and Bertrand games.

Transparency of Information and Coordination in Economies with Investment Complementarities by George-Marios Angeletos and Alessandro Pavan. Published in volume 94, issue 2, pages 91-98 of American Economic Review, May 2004

We develop a dynamic theory of managerial turnover in a world in which the quality of the match between a firm and its managers changes stochastically over time. Shocks to managerial productivity are anticipated at the time of contracting but privately observed by the managers. Our key positive result shows that the firm’s optimal retention decisions become more permissive with time. Our key normative result shows that, compared to what is efficient, the firm’s contract induces either excessive retention at all tenure levels or excessive firing at the early stages of the relationship, followed by excessive retention after sufficiently long tenure.

Global games of regime change–coordination games of incomplete information in which a status quo is abandoned once a sufficiently large fraction of agents attacks it–have been used to study crises phenomena such as currency attacks, bank runs, debt crises, and political change. We extend the static benchmark examined in the literature by allowing agents to take actions in many periods and to learn about the underlying fundamentals over time. We first provide a simple recursive algorithm for the characterization of monotone equilibria. We then show how the interaction of the knowledge that the regime survived past attacks with the arrival of information over time, or with changes in fundamentals, leads to interesting equilibrium properties. First, multiplicity may obtain under the same conditions on exogenous information that guarantee uniqueness in the static benchmark. Second, fundamentals may predict the eventual regime outcome but not the timing or the number of attacks. Finally, equilibrium dynamics can alternate between phases of tranquillity–where no attack is possible–and phases

Abstract We study platform markets in which the information about users’ preferences is dispersed. First, we show how the dispersion of information introduces idiosyncratic uncertainty about participation decisions and how the latter shapes the elasticity of the demands and the equilibrium prices. We then study the effects on profits, consumer surplus, and welfare of platform design, blogs, forums, conferences, advertising campaigns, post-launch disclosures, and other information management policies affecting the agents’ ability to predict participation decisions on the other side of the market.

We propose a robust solution concept for Bayesian persuasion that accounts for the Sender's concern that her Bayesian belief about the environment—which we call the conjecture —may be false. Specifically, the Sender is uncertain about the exogenous sources of information the Receivers may learn from, and about strategy selection. She first identifies all information policies that yield the largest payoff in the “worst‐case scenario,” that is, when Nature provides information and coordinates the Receivers' play to minimize the Sender's payoff. Then she uses the conjecture to pick the optimal policy among the worst‐case optimal ones. We characterize properties of robust solutions, identify conditions under which robustness requires separation of certain states, and qualify in what sense robustness calls for more information disclosure than standard Bayesian persuasion. Finally, we discuss how some of the results in the Bayesian persuasion literature change once robustness is accounted for, and develop a few new applications.

This paper introduces signaling in a global game so as to examine the informational role of policy in coordination environments such as currency crises and bank runs. While exogenous asymmetric information has been shown to select a unique equilibrium, we show that the endogenous information generated by policy interventions leads to multiple equilibria. The policy maker is thus trapped into a position in which self-fulfilling expectations dictate not only the coordination outcome but also the optimal policy. This result does not rely on the freedom to choose out-of-equilibrium beliefs, nor on the policy being a public signal; it may obtain even if the policy is observed with idiosyncratic noise.

Matching theory typically assumes that agents know their values for possible partners and confines attention to settings in which matching is either static, or driven by population dynamics. In many environments of interest, instead, dynamics originate in the agents learning their preferences through interactions with other agents. In this short paper, we illustrate how platforms can use appropriately designed auctions to account for the joint value of experimentation and cross-subsidization in dynamic matching markets. The model is a stylized version of the general one in Fershtman and Pavan (2016).

We study optimal income taxation when workers’ productivity is stochastic and evolves endogenously because of learning by doing. Learning by doing calls for higher wedges and alters the relation between wedges and tax rates. In a calibrated model, we find that reforming the US tax code brings significant welfare gains and that a simple tax code invariant to past incomes is approximately optimal. We isolate the role of learning by doing by comparing the aforementioned tax code to its counterpart in an economy that is identical to the calibrated one except for the exogeneity of the productivity process. Ignoring learning by doing calls for fundamentally different proposals.