Fragility of Confounded Learning

TL;DR

This paper investigates how confounded learning, where private signals are obscured by external shocks, is generally unlikely to occur in observational learning models with public payoff shocks, despite divergent preferences.

Contribution

It demonstrates that confounded learning is rare across most private signals and shocks, providing insight into the robustness of learning processes under external shocks.

Findings

Confounded learning is unlikely for most private signals.

External public payoff shocks do not typically lead to confounded learning.

The model shows robustness of learning despite divergent preferences.

Abstract

We consider an observational learning model with exogenous public payoff shock. We show that confounded learning doesn't arise for almost all private signals and almost all shocks, even if players have sufficiently divergent preferences.