W e develop a structural demand model that endogenously captures the effect of out-of-stocks on customer choice by simulating a time-varying set of available alternatives. Our estimation method uses store-level data on sales and partial information on product availability. Our model allows for...

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...

Disagreement among researchers regarding types of optimal choice experiments is often best seen as resulting from differences in the set of assumptions researchers are willing to make about the underlying data generating process. Much of the current debate may have confused, rather than...