Self-Prospecting: Optimal Experimentation Under Present-Bias

About this event

A present-biased decision maker (DM) faces a two-armed bandit problem whose risky arm generates random payoffs at exponentially distributed times. Under full information, the DM's belief remains unchanged prior to payoff arrivals, generating a ``lumpy' belief process that updates infrequently but conclusively. Our main finding is that coarsening the DM's information to foster ``gradual optimism' - a continuously increasing path of beliefs during active experimentation - helps motivate the DM more effectively and deliver them greater welfare. We relate our findings to those in behavioral psychology relating to motivation, learning, and self-control, and apply our results to parenting and pedagogy.