Discrete Choice Analysis

Abstract

This chapter gives an overview of discrete choice analysis techniques. First we present a reflection about the meaning of the words 'discrete' and 'choice'. Then we provide an overview of the sorts of choices in passenger and freight transport that have been treated as discrete choice problems. The next section presents the basic random utility theory, upon which most discrete choice models have been based. Different types of discrete choice models are then discussed: the workhorse of discrete choice modelling—the multinomial logit model (MNL), the nested logit and other Generalised Extreme Value (GEV) models, the probit model, the mixed logit and latent class models, ordered response models and aggregate logit models. Then we briefly discuss the estimation of discrete choice models and their application for demand forecasting and for policy simulation. The last section contains a summary and conclusions and a discussion on the future research directions.