Exploiting a rich panel data set on anti-ulcer drug prescriptions, we measure the effects of uncertainty and learning in the demand for pharmaceutical drugs. We estimate a dynamic matching model of demand under uncertainty in which patients learn from prescription experience about the...

Due to differences in the effectiveness and side effects of different drugs, uncertainty is an important component of prescription drug choice. This uncertainty can cause patients and doctors to experiment with different drugs until they find a good match. In this paper, we specify and estimate...

We study physicians' prescription choices when uncertainty about drug efficacy is resolved through two channels: firms' marketing activities (e.g., detailing) and patients' experiences with the drugs. We first provide empirical evidence that suggests the well-understood information incentive for...

A firm launching a new product in an existing category can leverage comparative messages to provide information to customers and to distinguish it from others. Incumbents, on the other hand, benefit less from comparative messaging as this could be interpreted as providing legitimacy to the...

This paper examines the spillover effects of promotions when products from different firms are consumed in a bundle. Using data from the HIV/AIDS category, a canonical example of combination therapy, we estimate a hierarchical Bayesian logit model across treatment regimens and show that...

The recent withdrawal of Cox-2 Inhibitors has generated debate on the role of information in drug diffusion: can the market learn the efficacy of new drugs, or does it depend solely on manufacturer advertising and FDA updates? In this study, we use a novel data set to study the diffusion of...