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

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 how consumers learn from others

The Seeds of Negativity: Knowledge and Money

This paper studies the tendency to use negative ads. For this purpose, we focus on an interesting industry (political campaigns) and an intriguing empirical regularity (the tendency to "go negative" is higher in close races). We present a model of electoral competition in which ads inform voters either of the good traits of the candidate or of the bad traits of his opponent. We find that in equilibrium, the proportion of negative ads depends on both voters' knowledge and the candidate's budget. Furthermore, for an interesting subset of the parameter space, negativity increases in both knowledge and budget. Using data on the elections for the U.S. House of Representative in 2000, 2002, and 2004, we examine the model and its implications. Using nonstructural estimation, we find that negativity indeed increases in both voters' knowledge and the candidate's budget. Furthermore, we also find that knowledge and budget mediate the effect of closeness on negativity. Using structural estimation, we reinforce these findings. Specifically, we find that the model's parameters are within the subset of the parameter space discussed above. Thus, the evidence implies that the model is not only helpful in identifying variables that were ignored by previous studies (i.e., knowledge and budget) but also in explaining an intriguing empirical regularity.political marketing, advertising, analytical models, Bayesian estimation, cross-sectional analysis