Learning Efficiency of Multi-Agent Information Structures

Mira Frick (mira.frick@yale.edu), Ryota Iijima (ryota.iijima@yale.edu) and Yuhta Ishii
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Mira Frick: Cowles Foundation, Yale University
Ryota Iijima: Cowles Foundation, Yale University, https://economics.yale.edu/people/faculty/ryota-iijima
Yuhta Ishii: Department of Economics at Pennsylvania State University

No 2299R2, Cowles Foundation Discussion Papers from Cowles Foundation for Research in Economics, Yale University

Abstract: We study which multi-agent information structures are more effective at eliminating both first-order and higher-order uncertainty, and hence at facilitating efficient play in incomplete-information coordination games. We consider a learning setting à la Cripps, Ely, Mailath, and Samuelson (2008) where players have access to many private signal draws from an information structure. First, we characterize the rate at which players achieve approximate common knowledge of the state, based on a simple learning efficiency index. Notably, this coincides with the rate at which players’ first-order uncertainty vanishes, as higher-order uncertainty becomes negligible relative to first-order uncertainty after enough signal draws. Based on this, we show that information structures with higher learning efficiency induce more efficient equilibrium outcomes in coordination games that are played after sufficiently many signal draws. We highlight some robust implications for information design in games played in data-rich environments.

Keywords: higher-order beliefs; common learning; coordination; speed of learning; comparison of information structures. (search for similar items in EconPapers)
Pages: 50 pages
Date: 2021-08, Revised 2022-07
New Economics Papers: this item is included in nep-gth and nep-mic
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