Unobserved Product Differentiation in Discrete-Choice Models: Estimating Price Elasticities and Welfare Effects

Commonly used discrete-choice models such as logit, nested logit, and random-coefficients models place very strong restrictions on how unobservable characteristic space changes with the number of products. We argue (and show with Monte Carlo experiments)that these restrictions can lead to biased estimates of price elasticities and the welfare consequences from additional products. In addition, these restrictions can identify parameters that are not intuitively identified given the data at hand. We suggest an alternative model that does not have these properties and present a structural interpretation of the model. Monte Carlo experiments and an empirical example show that this issue can be important in practice.