Book Description

Chapter 1 proposes a moment inequality approach to estimating random utility models when consumers consideration sets are unobservable to econometricians. I show that, without relying on a specific model of consideration set formation, the random utility model can be identified and estimated via a system of conditional moment inequalities derived from the utility maximization assumption. I apply the moment inequality approach to study whether attention inertia can explain some of the observed persistence in consumers brand choices, as opposed to alternative explanations in terms of preference, e.g., state-dependent utilities. The estimation results, obtained using household scanner data, show that up to twenty percent of the observed persistence, in terms of re-purchase probability, can be attributed to the fact that previous purchase of a brand increases its present consideration probability. Chapter 2 introduces a new approach to estimating differentiated product demand system that allows for error in market shares as measures of choice probabilities. In particular, our approach allows for products with zero sales in the data, which is a frequent phenomenon that arises in product differentiated markets but lies outside the scope of existing demand estimation techniques. We use our approach to study consumer demand from scanner data using the Dominicks Finer Foods database, and find that even for the baseline logit model, demand elasticities nearly double when the full error in market shares is taken into account.