About this series

Discrete choice models are the workhorses of modern applied econometrics, used to predict everything from commuter transport choices to consumer product selection. However, the standard textbook treatment often overlooks the rich mathematical and computational properties that govern these models.

In this series, we follow the roadmap of the book and we start with peeling back the layers of the “Random Utility Model” to reveal its deep connections with convex analysis, information theory, optimal transport, extreme value theory, and generalized linear models.
Still following the book, we then use random utility models as a building block for demand inversion methods, models of trade, dynamic pricing and hedonic models, as well as matching models with and without transfers.

Table of Contents