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
- Probit and logit kernel methods
- Panel data
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).