Choice modeling in R 2400-ZEWW919
This class will introduce students to state-of-the-art methods used in the empirical research involving choice models. The outline of the course looks as follows.
1. Choice, random utility, and the multinomial logit model.
2. Inference based on the random utility models, marginal utilities, willingness-to-pay, consumer surplus, elasticity of demand.
3. Extensions: nested logit and the multinomial probit model.
4. Introduction to stated preference methods – contingent valuation vs. discrete choice experiments.
5. Modeling scale of the random utility. Combining stated and revealed preference data.
6. Panel data and preference heterogeneity – mixed logit model.
7. Simulation methods for the discrete choice data.
8. Panel data and preference heterogeneity (continued) – latent class model.
9. Extensions for panel data: willingness-to-pay space, different mixing distributions, correlations.
10. Behavioral models of choice – random regret minimization.
11. Behavioral models of choice – attribute nonattendance.
12. Programming your own choice models – a simple satisficing model.
13. Accounting for psychological factors – hybrid choice models.
14. Dealing with endogeneity in discrete choice models.
15. Multiple discrete continuous choice models and volumetric choice experiments.
Type of course
Course coordinators
Learning outcomes
Completing the course allows participants to familiarize with methods and tools of choice modeling – both theoretically (rationale, assumptions, theory) and in practice (being able to use them for data analysis – building a model, estimation, interpretation of the results). The course provides a baseline for using the choice analysis in practice and self-teaching the many extensions. The models covered are applied in various fields of microeconomics (analysis of markets, industries, consumers, social research, experimental economics etc.), in which people’s choices reveal their preferences or decision strategies.
Assessment criteria
A research project involving a quantitative analysis of the choice data that will be provided by the teacher or found by the students.
The research project must include:
- introduction to the subject, putting a research hypothesis
- description of the data – basic choice analysis
- specification of the problem / econometric model and expectations
- model estimation and diagnostics
- interpretation of results and conclusions
Additional information
Additional information (registration calendar, class conductors, localization and schedules of classes), might be available in the USOSweb system: