Alternative nested logit models: structure, properties and estimation

Abstract

Two distinctly different nested logit models have been widely used in both research and applications. The differences, not widely recognized, between these models will substantially influence estimation results, behavioral interpretation and policy analysis. The McFadden nested logit model is derived from random utility theory; the Daly or non-normalized nested logit model is based on probability relationships and is not consistent with utility maximization. This paper describes and compares the model structure and properties of these different nested logit models identifying important differences between the different model structures. An empirical application demonstrates that the different nested logit models produce dramatically different results with respect to nesting structure and the relative importance of utility components. Thus, the selection of one or another of the nested logit models has important consequences for model interpretation and prediction with consequent impacts on policy analysis. The authors prefer the McFadden model because of its basis in utility theory, intuitively reasonable elasticity relationships and a clear interpretation of utility function parameters across alternatives.