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).
- 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);
- Data collection issues, e.g. choice-based samples, enriched samples, stated preferences surveys, conjoint analysis, panel data;
- Model design issues, e.g. specification of utility functions, generic and alternative specific variables, joint discrete/continuous models, dynamic choice models;
- Model estimation issues, e.g. statistical estimation, testing procedures, software packages, estimation with individual and grouped data, Bayesian estimation;
- Forecasting techniques, e.g. aggregate predictions, sample enumeration, micro-simulation, elasticities, pivot-point predictions and transferability of parameters;
- 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).
|Lecturers:||Prof. Moshe Ben-Akiva||Massachusetts Institute of Technology, Cambridge, Ma (USA)|
|Prof. Daniel McFadden||University of South California|
|Prof. Michel Bierlaire||Ecole Polytechnique Fédérale de Lausanne, Switzerland|
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)