Action Volatility in a Changing World

Wanying Huang

Papers from arXiv.org

Abstract: We study how volatile agents' behavior is in a social learning environment with a changing state. We consider a simple sequential social learning model where rational agents arrive in order, each acting only once, and the underlying unknown state constantly evolves. Each agent receives a private signal, observes all past actions of others, and chooses an action to match the current state. Because the state changes over time, cascades cannot last forever, and actions also fluctuate. We show that actions change less often than private signals but, despite the presence of temporary information cascades, still more often than the underlying state in the long run.

Date: 2022-08, Revised 2026-11
New Economics Papers: this item is included in nep-gth and nep-mic
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