96806 - DISCRETE CHOICE MODELS

Learning outcomes

At the end of the course the student is able to choose, among several discrete choice models, the specification most adequate to solve a specific problem of market analytics. Moreover, he is able to estimate the model, check the model and interpret the results. In particular the student: - has a deep knowledge of the theory related to the main discrete choice models (Multinomial Logit/Probit Model, Neste Logit/Probit Models, Mixed Logit/Probit Model); - has the competence to apply these models to business contexts through the solution of case studies.

Course contents

The course will cover the following topics:

Introductory theory: behavioral assumptions for choice models; derivation of discrete choice models.

Logit/probit model; Multinomial logit; Nested Logit; Mixed logit. For each model we will see: theory and specification, estimation, result interpretation, practical examples.

Two case studies will be developed in computer labs, using real data drawn from examples in the area of consumer choice: (I) an application of DCMs to purchase data (II) development of a choice experiment for data collection in a business scenario.

Readings/Bibliography

The course will be mainly based on lecture notes and chapters/papers provided through Virtuale. The teacher will refer also to useful chapters in the following books:

Greene, W. (2009). Discrete choice modeling. In Palgrave handbook of econometrics (pp. 473-556). Palgrave Macmillan, London.

Train, K. E. (2009). Discrete choice methods with simulation. Cambridge University Press.

Hess, S., & Daly, A. (Eds.). (2014). Handbook of choice modelling. Edward Elgar Publishing.

Hensher, D. A., & Johnson, L. W. (2018). Applied discrete-choice modelling. Routledge. A mock exam will be provided at the end of the course.

Teaching methods

The course comprises lectures and computer labs for the development of case studies. Applications will be based on real data using STATA and R.

Assessment methods

The evaluation is made through a written exam. The exam will comprise both theoretical and empirical questions. The exam includes multiple choice and open-ended questions on topics covered during the course.

Teaching tools

- Lecture slides and notes

- Useful readings (articles, book chapters, etc.)

- Data and codes for tutorials

These materials will be provided and integrated throughout the course, and uploaded on Virtuale platform.

Office hours

See the website of Beatrice Biondi