Email: sato.hiroto.s9(at)f.mail.nagoya-u.ac.jp
I am a postdoctoral researcher at Nagoya University. I am a microeconomic theorist with a focus on information and uncertainty.
I received my PhD in Economics from the University of Tokyo in 2024.
Review of Economic Design, July 2022
Review of Economic Design Nedim Okan Prize in 2023
This paper studies sequential information design (Doval and Ely 2020) in which a designer can construct the extensive form along with the information structure. In this framework, I investigate robust implementations against adversarial equilibrium selection, when players and the designer have a supermodular payoff function with dominant states and an outside option. The main results show that the optimal partially implementable outcome is fully implementable in sequential information design, which essentially coincides with the optimal partially implementable outcome in static information design. For economic applications such as global game of regime change, this paper proposes a way to robustly achieve the desired outcome in static information design by providing the extensive form and the information structure.
Joint work with Ryo Shirakawa
R&R at Journal of Economic Behavior and Organization
Priority uncertainty is prevalent in practical matching markets. This study investigates the role of priority information structures in a simple decentralized college admissions model. The first main theorem characterizes equilibrium distributions of students across schools, which are implementable with a class of simple disclosure rules, cutoff signals. The cutoff signal induces an ex-ante fair allocation that is also the closest to being ex-post fair among the allocations achieving the same distribution. As an application, we consider an information design problem. The second main theorem shows that each equilibrium distribution is implementable as a unique equilibrium.
Joint work with Ryo Shirakawa Submitted
Consider a situation wherein a decision maker sequentially searches for the best alternative among heterogeneous options with an arbitrary search order. The agent partially learns the value of an option when inspecting it. We characterize the set of all search behaviors which may arise under some information structure, which forms a polytope. Moreover, a single information structure induces all feasible search behaviors, which minimizes the agent's welfare among all information structures. Applications include information design and comparative statics.
( This paper subsumes Information Design in Pandora's Problem )
Joint work with Ryo Shirakawa Submitted
In many economic situations, such as job search and online shopping, agents are sequentially searching for information to choose one of a few options. Information revealed through their search process affects the eventual choice outcomes of such economies. This study explres a Bayesian persuasion problem in Weitzman's (1979) ordered search models. We show that an optimal signal structure consists of three signals for any risk-neutral planner. Neither providing no information nor full information is optimal except for trivial cases. We further derive comparative statics results for the tight bounds of each option's chosen probability and find that Bayesian persuasion minimizes agents' welfare in many cases.
Joint work with
Konan Shimizu
New!
This study extends Blackwell's (1953) comparison of information to a sequential social learning model, where agents make decisions sequentially based on both private signals and the observed actions of others. In this context, we introduce a new binary relation over information structures: An information structure is more socially valuable than another if it yields higher expected payoffs for all agents, regardless of their preferences. First, we establish that this binary relation is strictly stronger than the Blackwell order. Then, we provide a necessary and sufficient condition for our binary relation and propose a simpler sufficient condition that is easier to verify.
Joint work with
Konan Shimizu
Download: Curriculum Vitae (PDF)