Higher-Order Learning

40 Pages Posted: 23 Dec 2018 Last revised: 9 Dec 2021

See all articles by Piotr Evdokimov

Piotr Evdokimov

Humboldt University Berlin

Umberto Garfagnini

University of Surrey - School of Economics

Date Written: September 6, 2021

Abstract

We design a novel experiment to study how subjects update their beliefs about the beliefs of others. Three players receive sequential signals about an unknown state of the world. Player 1 reports her beliefs about the state; Player 2 simultaneously reports her beliefs about the beliefs of Player 1; and Player 3 simultaneously reports her beliefs about the beliefs of Player 2. We say that beliefs exhibit higher-order learning if the beliefs of Player k about the beliefs of Player k-1 become more accurate as more signals are observed. We find that some of the predicted dynamics of higher-order beliefs are reflected in the data; in particular, higher-order beliefs are updated more slowly with private than public information. However, higher-order learning fails even after a large number of signals is observed. We argue that this result is driven by base-rate neglect, heterogeneity in updating processes, and subjects' failure to correctly take learning rules of others into account.

Keywords: Higher-order expectations, learning, theory of mind

JEL Classification: C90, D83, D89

Suggested Citation

Evdokimov, Piotr and Garfagnini, Umberto, Higher-Order Learning (September 6, 2021). Available at SSRN: https://ssrn.com/abstract=3296226 or http://dx.doi.org/10.2139/ssrn.3296226

Piotr Evdokimov

Humboldt University Berlin ( email )

Umberto Garfagnini (Contact Author)

University of Surrey - School of Economics ( email )

Guildford
Guildford, Surrey GU2 5XH
United Kingdom

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