LOG904-150 Stated Preferences - Discrete Choice Modelling (Autumn 2021)

About the course

Course content (abstract): This course focuses on the practical issues of discrete choice modelling. The course will provide an introduction to the key concept of utility based choice theory and choice modelling. Course participants are presented with case studies originating from applications in transportation economics. Topics discussed in the course are: econometric methodology, model specification, estimation, inference, data issues, analysis, applications. Lecture notes and exercises instructions are delivered at class.

Topics covered:-

The course is connected to the following study programs

• Master of Science in Logistics
• Experience-based Master in Logistics
• Master of Science in Sustainable Energy Logistics
• Exchange programme - Master's level
• Master of Science in Sustainable Transport and Urban Mobility

Recommended requirements

Intermediate course in Microeconomics and Statistics

The student's learning outcomes after completing the course

The course is an introduction to discrete choice modeling, with a focus on how to fit, interpret, and use models. Theoretical background will include econometric underpinnings of the models and foundations for various computations. The course is meant to provide students with the econometric instruction needed to use, understand, and interpret some basic techniques. In hands-on exercises, the participant will learn how to develop and estimate basic choice models and how the results are interpreted introducing the concepts of willingness to pay and elasticities.

Forms of teaching and learning

This is a practical and theory based course. The focus of the course, strictly interlinked with Introduction to State preference Methods I, will be on the entire process of model estimation. Tools and methods to model individual behavior, study of market shares and change in demand in response to policy changes will be discussed with reference to specific case studies. Hands on problems with actual data sets will be used to augment the presentations.

Examination

Form of assessment: Home assessment with presentation

• Proportion: 20%

• Duration: -

• Grouping: Group & Individual

• Grading scale: Letter (A - F)

• Support material: All printed and written supporting material

Form of assessment: Home assessment without presentation

• Proportion: 80%

• Duration: -

• Grouping: Group & Individual

• Grading scale: Letter (A - F)

Support material: All printed and written supporting material

Course evaluation

Students will have to show they can interpret the results of a discrete choice model, discuss the main results deriving from the activities performed and draw policy implications from the models estimated.

Syllabus

Koppelman and Bhat, January 31, 2006, A Self Instructing Course in Mode Choice Modeling: Multinomial and Nested Logit Models, (http://www.caee.utexas.edu/prof/bhat/COURSES/LM_Draft_060131Final-060630.pdf).

Additional material will be made available by the Instructor prior to the beginning of the course.