©2010 INFORMS Structural Estimation of the Effect of Out-of-Stocks

We develop a structural demand model that endogenously captures the effect of out-of-stocks on customerchoice 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 flexible substitution pat-terns, which are based on utility maximization principles and can accommodate categorical and continuous product characteristics. The methodology can be applied to data from multiple markets and in categories with a relatively large number of alternatives, slow-moving products, and frequent out-of-stocks (unlike many existing approaches). In addition, we illustrate how the model can be used to assist the decisions of a store manager in two ways. First, we show how to quantify the lost sales induced by out-of-stock products. Second, we provide insights on the financial consequences of out-of-stocks and suggest price promotion policies that can be used to help mitigate their negative economic impact, which run counter to simple commonly used heuristics. Key words: aggregate demand estimation; Bayesian methods; choice models; data augmentation; inventory management; out-of-stocks; retailin