Introduction to Discrete Choice Models

The course introduces the theoretical foundations to choice modeling and describes the steps of operational modeling.

Description

Human behavior is complex and unpredictable. Or is it?

The focus of this course is methods for predicting the behavior using mathematical models. More specifically, we'll explore choice modeling in order to obtain disaggregate demand models.  

Focusing on the logit model, the course covers the specification of the model, the estimation of its parameters, the validation process, and its application. Exercises using the software Biogeme are also part of its makeup. The course relies on concrete case studies with real data sets, which are provided in course content.

What you will learn

• The behavioral assumptions associated with disaggregate choice models


• The derivation of operational models


• The art of model specification


• The estimation of model parameters from choice data


• The testing of model specifications


• Concrete applications of the estimated models

Prerequisites

Statistics (bachelor level), linear regression

Plan

1. Introduction to behavior modeling
2. Theoretical foundations
3. Binary choice
4. Biogeme: an open-source software for estimating choice models
5. Choice with multiple alternatives
6. Testing
7. Forecasting