Mathematical Methods of Discrete Choice Models

Princeton University Press (to appear Spring 2026)

This text provides an overview of discrete choice models with in-depth coverage of the random utility model framework, logistic regressions, generalized linear models and applications to the gravity equation, empirical models of matching, hedonic models. The theory of multivariate extreme value is reviewed with applications to the nested logit model and other generalizations. The characteristics approach is covered as well as BLP demand estimation, and dynamic discrete choice methods. Equilibrium in models with non-transferable utility are discussed. The book features exercises and problem sets, and it includes a rich mathematical appendix, as well as extensive Python code examples.

The table of content and the book’s preface is available here.

A slide deck will be posted soon.