Individual Choice Behavior: Theory and Application of Discrete Choice Analysis
Venue: MIT Campus - Cambridge, MA
|Event Date/Time: Jun 18, 2007||End Date/Time: Jun 22, 2007|
This one-week program undertakes an in-depth study of discrete choice models and their applications. It provides participants with the practical tools necessary for applying new discrete choice techniques. By examining actual case studies of discrete choice methods, students will be familiarized with problems of data collection, model formulation, testing, and forecasting, and will gain hands-on application experience by applying freely available software to estimate and test discrete choice models from real databases.
Who Should Attend
This program is intended for marketing researchers and analysts, economists, operations researchers, engineers, planners, managers and industry, government and academic researchers who are interested in understanding and predicting consumer choices, demand and market share. Participants should have a working knowledge of basic statistical methods.
Topics Covered Include the Following
The material covered includes: theories of choice, random utility models, probabilistic choice models, alternative model formulations, statistical estimation procedures appropriate for alternative data sources, currently available computer software, tests of validity, forecasting procedures and examples of empirical applications.
More specifically, the following subjects will be addressed during the course:
Binary Choice Models
Stated Preference Surveys
Multinomial Choice Models: Properties of Probit, Logit and Discriminant Analysis
Specification and Estimation of Discrete Choice Models
Statistical Tests of Discrete Choice Models
Forecasting and Micro-Simulation
Nested Logit Models
Multi-variate(Generalized) Extreme Value Models
Mixture Models, such as Logit Kernel or Mixed Logit
Discrete Panel Data
Combining Revealed and Stated Preferences
Sampling Strategies for Discrete Choice Analysis
Joint Discrete / Continuous Models
Choice from a Menu
Choice Models with Latent Variables