Discrete Choice Modeling

Lecturer:
Stephen Youngjun Park (Ph.D.)

Target Audience:
Master students of MEB, UF, MAN, FRS, GLOB, WINF, Wi-Päd, Steuerlehre, IECO, Development Economics, History of global markets or Angewandte Statistik

Course Language:
English

Learning Outcome, Competences:
Discrete choice modeling deals with analyzing choice behavior of individuals (e.g., consumers) as a function of variables that describe the choice alternatives and/or the individuals. After successful attendance the students will understand the methodological principles of discrete choice modeling. Further, they will be able to estimate own discrete choice models using the statistical programming language R. (Previous knowledge in R is not required!)

Content:

• Random Utility Theory
• Collecting Choice Data
• Choice-based Conjoint
  - Consumer Purchase Data
  - Analyzing Choice Data
• Multinomial Logit (MNL) Models
  - Finite Mixture and Mixed MNL Models
  - Hierarchical Bayesian MNL Models

Time and Place:
Lecture: (Start: 21.10.2024)
Mondays, 2:15 pm – 3:45 pm, room: MZG 7.153 (21.10.2024 - 24.11.2024)
Thursdays, 2:15 pm – 3:45 pm, room: MZG 5.111 (24.10.2024 - 28.11.2024)

There is no lecture on Thursday, October 31, 2024.

Examination:
Term Paper (max. 6000 words) - 6 Credits