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Learning in Network Games

Kovářík, Jaromír and Mengel, Friederike and Romero, José Gabriel (2018) 'Learning in Network Games.' Quantitative Economics, 9 (1). 85 - 139. ISSN 1759-7323

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Abstract

We report the findings of experiments designed to study how people learn in network games. Network games offer new opportunities to identify learning rules, since on networks (compared to e.g. random matching) more rules differ in terms of their information requirements. Our experimental design enables us to observe both which actions participants choose and which information they consult before making their choices. We use these data to estimate learning types using finite mixture models. Monitoring information requests turns out to be crucial, as estimates based on choices alone show substantial biases. We also find that learning depends on network position. Participants in more complex environments (with more network neighbours) tend to resort to simpler rules compared to those with only one network neighbour.

Item Type: Article
Uncontrolled Keywords: Experiments, Game Theory, Heterogeneity, Learning, Finite Mixture Models,, Networks
Subjects: H Social Sciences > HB Economic Theory
Divisions: Faculty of Social Sciences > Economics, Department of
Depositing User: Jim Jamieson
Date Deposited: 27 Mar 2013 12:57
Last Modified: 07 Feb 2020 16:15
URI: http://repository.essex.ac.uk/id/eprint/5809

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