An empirical model of learning and patient spillovers in new drug entry

摘要

We specify and estimate a diffusion model for the new molecule omeprazole into the anti-ulcer drug market. Our model is based on a Bayesian learning process whereby doctors update their beliefs about omeprazole's quality relative to existing drugs after observing its effects on the patients that have been prescribed this drug. The model also accommodates informational spillovers and heterogeneity in informativeness across patients with different diagnoses. We obtain estimates of the learning processparameters using a novel panel data set tracking doctors' complete prescription histories over a 3-year period.