We estimate the direct effects of rewards card programs on consumer payment choice for in-store transactions. By using a data set that contains information on consumer perceived attributes of payment methods and consumer perceived acceptance of payment methods by merchants, we control for consumer heterogeneity in preferences and choice sets. We conduct policy experiments to examine the effects of removing rewards from credit and/or debit cards. The results suggest that: (i) only a small percentage of consumers would switch from electronic to paper-based payment methods, (ii) the effect of removing credit card rewards is greater than that of removing debit card rewards, and consequently, (iii) removing rewards on both credit and debit cards would reduce credit card transactions, but increase debit card transactions.

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This article incorporates consumer learning and heterogeneity into a dynamic oligopoly model for the prescription drug market. In the model, both firms and patients need to learn the generic qualities via patients' experiences, generic firms' entry decisions are endogenous, but their entry timings depend on a random approval process. I apply the model to examine the impact of shortening the expected generic approval time. Although this policy experiment brings generics to the market sooner, it increases a potential entrant's likelihood of entering a crowded market and hence could reduce the total number of generic entrants and consumer welfare.

We develop a structural model of detailing and prescribing decisions under an environment where detailing helps physicians obtain the current information sets about drug qualities. Our model assumes that a representative opinion leader is responsible for updating the prior belief about the quality of drugs via patients' experiences, and manufacturers use detailing as a means to build/maintain the measure of physicians who are informed of the current information sets. We estimate our model using data on sales, prices, and detailing minutes at the product level for ACE-inhibitor with diuretic in Canada. We quantify the marginal impact of detailing on current demand at different points in time, and demonstrate how it depends on the measure of well-informed physicians and the information sets. Furthermore, we conduct a policy experiment to examine how a public awareness campaign, which encourages physicians/patients to report their drug experiences, would affect managerial incentives to detail.

Learning models extend the traditional discrete choice framework by postulating that consumers have incomplete information about product attributes, and that they learn about these attributes over time. In this survey we describe the literature on learning models that has developed over the past 20 years, using the model of Erdem and Keane (1996) as a unifying framework. We described how subsequent work has extended their modeling framework, and applied learning models to a wide range of different products and markets. We argue that learning models have contributed greatly to our understanding of consumer behavior, in particular in enhancing our understanding of brand loyalty and long run advertising effects. We also discuss the limitations of existing learning models and discuss potential extensions. One key challenge is to disentangle learning as a source of dynamics from other key mechanisms that may generate choice dynamics (inventories, habit persistence, etc.). Another is to enhance identification of learning models by collecting and utilizing direct measures of signals, perceptions and expectations.