We are pleased to announce the following paper has been awarded the 2019 "Best Paper Prize" by the award committee:
"Learning in Network Games," by Jaromír Kovářík, Friederike Mengel, and José Gabriel Romero, Quantitative Economics, Volume 9, Issue 1 (March 2018).
From 2019 onwards, this “Best Paper” prize will alternate yearly between Quantitative Economics and Theoretical Economics. The single paper winner is selected from all papers published in the corresponding journal during the previous two years by an external committee appointed by the President of the Society.
The authors 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. The authors' experimental design enables them to observe both which actions participants choose and which information they consult before making their choices. They 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. They also find that learning depends on network position. Participants in more complex environments (with more network neighbors) tend to resort to simpler rules compared to those with only one network neighbor.
Thank you to the "Best Paper Prize" committee members Elie Tamer (Chair), Nikhil Agarwal, and Juan Rubio-Ramirez for their work on behalf of the Econometric Society.