arXiv subjects

Hiroto Sato

Publications and source records attributed to Hiroto Sato.

4 recordsLinked to original sources

arXiv2026

Information Aggregation and Social Networks: Responsiveness and Overturning

This paper studies how network structures affect the efficiency of information aggregation in social learning environments. We consider a model in which rational agents sequentially choose actions based on private signals and observations of their neighbors' actions in a network. Focusing on comparisons of expected payoffs at a given finite period, we show that there exists an information structure under which the star network achieves a strictly higher expected payoff than any other network, and another information structure under which the complete network achieves a strictly higher expected payoff than any other network. Taken together, these results imply that no network is uniformly optimal across all information structures. Our analysis highlights a trade-off between the responsiveness effect and the overturning effect: disconnected networks preserve responsiveness of actions to private signals, whereas highly connected networks facilitate the aggregation of extreme information that overturns public beliefs.

econ.TH↗

arXiv2025

Allocating Common-Value Goods

We study a simple problem of allocating common-value goods. The designer seeks to allocate the goods to as many unit-demand agents as possible without monetary transfers, while agents, who possess partial private information about the goods, are willing to receive them only when the goods are of high value. Mechanisms screen each agent's private information using the information of other agents, and in doing so shape what agents learn from other agents about the value of the goods. The optimal mechanism can be summarized by two parameters: one adjusts the allocation probability, while the other governs the amount of learning induced by allocation. Although the designer prefers to allocate the goods, the optimal mechanism excludes some agents and, as a result, may withhold allocation even when all agents would be willing to receive them. The optimal mechanism has the same structure even when payments are available, but it may not exclude any agent and may involve strictly positive payments that are decreasing in allocation.

econ.TH↗

arXiv2025

Value of History in Social Learning: Applications to Markets for History

In social learning environments, agents acquire information from both private signals and the observed actions of predecessors, referred to as history. We define the value of history as the gain in expected payoff from accessing both the private signal and history, compared to relying on the signal alone. We first characterize the information structures that maximize this value, showing that it is highest under a mixture of full information and no information. We then apply these insights to a model of markets for history, where a monopolistic data seller collects and sells access to history. In equilibrium, the seller's dynamic pricing becomes the value of history for each agent. This gives the seller incentives to increase the value of history by designing the information structure. The seller optimal information discloses less information than the socially optimal level.

econ.TH↗

arXiv2025

Value of Information in Social Learning

This study extends Blackwell's (1953) comparison of information to a sequential social learning model in which agents make decisions sequentially based on both private signals and observed actions of others. In this context, we introduce a binary relation over information structures: an information structure is {\it more socially valuable} than another if it yields higher expected payoffs for {\it all} agents, regardless of their preferences and equilibrium realizations. First, we establish that this binary relation is strictly stronger than the Blackwell order. Next, we provide a necessary and sufficient condition for our binary relation and propose a simpler sufficient condition that is easier to verify. We further explore comparisons of information structures in terms of long-run payoffs, limit welfare, and canonical binary environments.

econ.TH↗