018708 – Advanced Models for demand analysis

1. Course Objectives

In this course we will expend on the quantitative tools for demand analysis. These tools are useful in analysis of transportation demand, but also in other decision-making contexts, such marketing, finance and others. The course will revisit and expend the basic models of discrete choice.

2. Course Content

The course will cover the following topics:

  • Introduction – review of statistics and discrete choice theory
  • Discrete choice models: specification, estimation, testing and prediction
  • Nested logit and GEV models
  • Revealed and stated preferences
  • Sampling
  • Probit and logit kernel methods
  • Panel data

  3. Bibliography

The course is based on the books:

  • Moshe Ben-Akiva & Steven Lerman (1985) Discrete Choice Analysis: Theory and Application to Travel Demand, MIT PRESS
  • Kenneth Train (2003) Discrete Choice Methods with Simulation

Additional readings will be distributed during the course   4. Course structure and grading The course will consist of weekly lectures, assignments (60% of the grade) and a final seminar (40% of the grade).