The Sound of Silence: Observational Learning in the U.S. Kidney Market

Abstract:     
Mere observation of others' choices can be informative about product quality. This paper develops an individual-level dynamic model of observational learning, and applies it to a novel data set from the U.S. kidney market where transplant candidates on a waiting list sequentially decide whether to accept a kidney offer. We find strong evidence of observational learning: patients draw negative quality inferences from earlier refusals in the queue, thus becoming more inclined towards refusal themselves. This self-reinforcing chain of inferences leads to poor kidney utilization despite the continual shortage in kidney supply. Counterfactual policy simulations show that patients would have made more efficient use of kidneys had the concerns behind earlier refusals been shared. This study yields a set of marketing implications. In particular, we show that observational learning and information sharing shape consumer choices in markedly different ways. Optimal marketing strategies should take into account on how consumers learn from others.

Keywords: observational learning, learning models, informational cascades, herding, quality inference, Bayes' rule, dynamic programming, kidney allocation

JEL Classifications: D62, D81, D82, D83, M31

Working Paper Series