We estimate a dynamic model of how consumers learn about and choose between different brands of personal computers (PCs). To estimate the model, we use a panel data set that contains the search and purchase behavior of a set of consumers who were in the market for a PC. The data includes the information sources visited each period, search durations, as well as measures of price expectations and stated attitudes toward the alternatives during the search process. Our model extends recent work on estimation of Bayesian learning models of consumer choice behavior in environments characterized by uncertainty by estimating a model of active learning—i.e., a model in which consumers make optimal sequential decisions about how much information to gather prior to making a purchase. Also, following the suggestion of Manski (2003), we use our data on price expectations to model consumers’ price expectation process, and, following the suggestion of McFadden (1989a), we incorporate the stated brand quality information into our likelihood function, rather than modeling only revealed preference data. Our analysis sheds light on how consumer forward-looking price expectations and the process of learning about quality influence the consumer choice process. A key finding is that estimates of dynamic price elasticities of demand exceed estimates that ignore the expectations effect by roughly 50%. This occurs because our estimated expectations formation process implies that consumers expect mean reversion in price changes. This enhances the impact of a temporary price cut. Finally, while our work focuses specifically on the PC market, the modeling approach we develop here may be useful for studying a wide range of high-tech, high-involvement durable goods markets where active learning is important. Copyright Springer Science + Business Media, Inc. 2005brand choice models, technology choice, decision-making under uncertainty, information search, consumer expectations, dynamic programming,

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One of the several regulatory failures behind the global financial crisis that started in 2007 has been the regulatory focus on individual, rather than systemic, risk of financial institutions. Focusing on systemically important assets and liabilities (SIALs) rather than individual financial institutions, we propose a set of resolution mechanisms, which is not only capable of inducing market discipline and mitigating moral hazard but also of addressing the associated systemic risk, for instance, due to the risk of fire sales of collateral assets. Furthermore, because of our focus on SIALs, our proposed resolution mechanisms would be easier to implement at the global level compared with mechanisms that operate at the level of individual institutional forms. We, then, outline how our approach can be specialized to the repo market and propose a repo resolution authority for reforming this market.

We develop a structural dynamic demand model that examines how brand preferences evolve when consumers are uncertain about product quality and their needs change periodically. We allow for strategic sampling behavior of consumers under quality uncertainty and allow for strategic sampling to increase periodically as consumers' needs change periodically. We differ from previous work on forward-looking consumer Bayesian learning by allowing for 1) spill-over learning effects across different versions of products or products in different product categories that share a brand name and 2) duration-dependence in utility for a specific version of a product or product class to capture systematic periodic changes in consumer utility and migration of consumers across product versions or classes. We also assess the evolution of price elasticities in markets where there is consumer quality uncertainty that diminishes over time as consumers get more experienced. We estimate our model using scanner data for the disposable diapers category and discuss the consumer behavior and managerial implications of our estimation and policy simulation results.

One of the several regulatory failures behind the global financial crisis that started in 2007 has been the regulatory focus on individual, rather than systemic, risk of financial institutions. Focusing on systemically important assets and liabilities (SIALs) rather than individual financial institutions, we propose a set of resolution mechanisms, which is not only capable of inducing market discipline and mitigating moral hazard but also of addressing the associated systemic risk, for instance, due to the risk of fire sales of collateral assets. Furthermore, because of our focus on SIALs, our proposed resolution mechanisms would be easier to implement at the global level compared with mechanisms that operate at the level of individual institutional forms. We, then, outline how our approach can be specialized to the repo market and propose a repo resolution authority for reforming this market.