We examine the profitability of personalized pricing policies that are derived using different specifications of demand in a typical retail setting with consumer-level panel data. We generate pricing policies from a variety of models, including Bayesian hierarchical choice models, regularized...

We study the estimation of preference heterogeneity in markets where consumers engage in costly search to learn product characteristics. Costly search amplifies the way consumer preferences translate into purchase probabilities, generating a seemingly large degree of preference heterogeneity. We...

Traditional methods for estimating demand are not always well-suited to online markets, where individual products are sold infrequently, unobserved factors such as webpage layout drive substitution, and often only a limited set of product characteristics is observed. We propose a demand model...