Network and timing effects in social learning
Theoretical Economics
2024-12-11 v1
Abstract
We consider a group of agents who can each take an irreversible costly action whose payoff depends on an unknown state. Agents learn about the state from private signals, as well as from past actions of their social network neighbors, which creates an incentive to postpone taking the action. We show that outcomes depend on network structure: on networks with a linear structure patient agents do not converge to the first-best action, while on regular directed tree networks they do.
Cite
@article{arxiv.2412.07061,
title = {Network and timing effects in social learning},
author = {Wade Hann-Caruthers and Minghao Pan and Omer Tamuz},
journal= {arXiv preprint arXiv:2412.07061},
year = {2024}
}