A simple method to estimate discrete-type random coefficients logit models

Abstract

This paper proposes a new method for estimating random coefficients logit models using aggregate data. The method analytically obtains the value of the econometric error term and thus does not require numerical calculations, in contrast to the contraction mapping established by Berry et al. (1995). The proposed approach drastically reduces the computation time and is applicable for models with discrete-type heterogeneity in consumer tastes. The approach requires additional data on total sales for each consumer type, though such data do not have to be observed at the product-level. This data requirement implies that the method mainly captures observed heterogeneity.