Dear Colleagues,
We would like to invite you to a one-week MIT course taught remotely from June 12-16, 2023:
Discrete Choice Analysis: Predicting Individual Behavior and Market Demand
Discrete choice models are used in many fields such as economics, engineering, environmental management, marketing, urban planning, and transportation. The course is designed for modelers who wish to acquire in-depth knowledge of the latest developments. It is intended for both academics and professionals.
The course covers: alternative models including Logit, Probit, Nested Logit, Multivariate Extreme Value, discrete and continuous Logit Mixtures and Hybrid Choice Models; and alternative estimation methods including simulated maximum likelihood, Hierarchical Bayes, instrumental variable methods and random effects in panel data. Recent additions to the course include “Foundations of Stated Preference Elicitation: Consumer Behavior and Choice-based Conjoint Analysis” by Moshe Ben-Akiva, Daniel McFadden and Kenneth Train, estimation of flexible model specifications using machine learning methods and online applications for optimization and personalization. Each day of this course consists of lectures followed by a computer lab to apply the lectured methods with open source software and data sets. Initial lectures and lab session review required fundamental concepts.
Partial scholarships (50%) are available for junior faculty, postdocs, and doctoral students.
Additional information is available here. We appreciate your help in making people aware of this unique opportunity to study this summer at MIT.
Thanks, Moshe
Moshe Ben-Akiva
Massachusetts Institute of Technology
Edmund K. Turner Professor of Civil and Environmental Engineering
Director, Intelligent Transportation Systems Lab