Estimating a Stockkeeping-Unit-Level Brand Choice Model that Combines Household Panel Data and Store Data

The marketing literature has addressed the issues of heterogeneity and endogeneity when estimating a choice model with household-level panel data. When using these data at the stockkeeping unit or the Universal Product Code level, choices for each item in each of the time periods under consideration cannot be observed. Without such information, it is difficult to control for item- and time period–specific unmeasured characteristics because there is no information on alternatives during those periods in which they are not purchased by any of the panelists. In general, when a product category has many alternatives, each with fairly small shares, the household sample may not contain sufficient choices for each alternative, thus negatively affecting the ability to control for endogeneity with household data. In contrast, because aggregate store-level data (for those stores in which the panel makes purchases) are the aggregation of purchases by all households visiting the stores, the data contain the time period–specific item-level information required to account for endogeneity as long as each item has some sales in each time period. Given the relative merits of household data to estimate the distribution of heterogeneity and store-level data to address the endogeneity problem, the authors propose an integrated estimation procedure that uses the information in both sources. They provide empirical results from their model using data on the fabric softener market. They extend their approach to situations in which there is variation in purchase quantities that households choose.