Discrete Choice Analysis: Predicting Demand and Market Shares
The course will cover the following topics: - Fundamental methodology, e.g. the foundations of individual choice modeling, random utility models, discrete choice models (binary, multinomial, nested, cross-nested logit models, GEV 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; - 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).
|Event dates:||2007-03-25 – 2007-03-29|
|Classification:||C3 - Econometric Methods: Multiple/Simultaneous Equation Models|
Persistent link: https://www.econbiz.de/10005873269