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Published October 2004 | public
Journal Article

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

Abstract

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 process parameters using a novel panel data set tracking doctors' complete prescription histories over a 3-year period.

Additional Information

© 2003 Elsevier. Accepted 3 September 2003. We thank Dr. Giuseppe Traversa and Roberto Da Cas at the Istituto Superiore di Sanita' and IMS Italy for providing the data, and Tim Bresnahan, Costas Meghir, Fiona Scott Morton, Peter Reiss, and Frank Wolak for their suggestions. We acknowledge financial support from a European Commission TMR fellowship #ERBFMBICT972232 (Coscelli) and a Sloan Foundation dissertation fellowship (Shum). We are grateful to an associate editor and two anonymous referees for detailed comments on earlier drafts.

Additional details

Created:
August 22, 2023
Modified:
October 17, 2023