The Emergence of Fads in a Changing World

We study how fads emerge under social learning in a changing environment. 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 despite the rise of temporary information cascades, in the long run, actions change more often than the state. This result provides a theoretical foundation for faddish behavior in which people often change their actions more frequently than necessary.