Higher-order learning

Piotr Evdokimov and Umberto Garfagnini ()
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Piotr Evdokimov: Higher School of Economics
Umberto Garfagnini: University of Surrey

Experimental Economics, 2022, vol. 25, issue 4, No 6, 1234-1266

Abstract: 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; 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 $$k-1$$ 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 (search for similar items in EconPapers)
JEL-codes: C90 D83 D89 (search for similar items in EconPapers)
Date: 2022
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DOI: 10.1007/s10683-021-09743-6

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