Courses

EPFL proposes a 5-day short course entitled "Discrete Choice Analysis: Predicting Individual Behavior and Market Demand". It is organized every year in March (occasionally in February).

Content:

1. Fundamental methodology, e.g. the foundations of individual choice modeling, random utility models, discrete choice models (binary, multinomial, nested, cross-nested logit models, MEV models, probit models, and hybrid choice models such as logit kernel and mixed logit);
2. Data collection issues, e.g. choice-based samples, enriched samples, stated preferences surveys, conjoint analysis, panel data;
3. Model design issues, e.g. specification of utility functions, generic and alternative specific variables, joint discrete/continuous models, dynamic choice models;
4. Model estimation issues, e.g. statistical estimation, testing procedures, software packages, estimation with individual and grouped data, Bayesian estimation;
5. Forecasting techniques, e.g. aggregate predictions, sample enumeration, micro-simulation, elasticities, pivot-point predictions and transferability of parameters;
6. Examples and case studies, including marketing (e.g., brand choice), housing (e.g., residential location), telecommunications (e.g., choice of residential telephone service), energy (e.g., appliance type), transportation (e.g., mode of travel).

MIT proposes a 5-day short course entitled "Discrete Choice Analysis: Predicting demand and market shares". It is organized every year in June.

Lecturer: Prof. Moshe Ben-Akiva, Massachusetts Institute of Technology, Cambridge, Ma (USA)