Module 6500
Advanced Applied Econometrics 2:
Limited Dependent Variable (LDV) / Choice models
Lecturers
Prof. Dr. Thomas Heckelei, thomas.heckelei@ilr.uni-bonn.de
Prof. Dr. Stefan Hirsch, s.hirsch@uni-hohenheim.de
Aims
At the end of the course students shall
- understand the basics econometric methods and be able to apply these to real problems,
- understand, apply and interpret theory-based econometric models,
- be able to work with the econometrics package R
Skills: Methodological competence, quantitative analysis, conceptual thinking
Contents
- Binary and multiple choice models
- Maximum Likelihood estimation
- Models for limited dependent variables
- Heckman-Models
- Empirical problems
Outline
- Maximum Likelihood Estimation (Verbeek Ch. 6.1 and 6.2
- Introduction to and examples for ML estimation
- General approach and estimation of the variance of the ML estimator
- Specification Tests
- Binary Choice Models (Verbeek Ch. 7.1)
- Why not Linear Regression?
- Probit and Logit models
- Underlying latent variable model
- Estimation
- Goodness-of-fit
- Specification tests
- Multiple Choice Models
- Ordered Response Models (Verbeek Ch. 7.2, Greene Ch. 18.3)
- Introduction
- The ordered probit model
- Estimation, Effects and Interpretation
- Testing
- Multinomial Models (Verbeek Ch. 7.2, Greene Ch. 18.1-18.2)
- Introduction, formalization, distributions
- The conditional logit model: introduction, estimation and interpretation
- The multinomial logit model: introduction, estimation and interpretation
- Independence of irrelevant alternatives IIA assumption
- The nested logit model: : introduction, estimation and interpretation
- Ordered Response Models (Verbeek Ch. 7.2, Greene Ch. 18.3)
- Count data models (Verbeek Ch. 7.3)
- General motivation
- Poisson model
- Negative Binomial Model
- Illustrations
- Tobit models (Verbeek Ch. 7.4-7.5)
- Tobit I
- Utility maximisation problem
- Standard Tobit model
- Tobit estimation
- Tobit specification test
- Tobit II (Double Hurdle)
- Statistical model
- Heckmann selection model
- Estimation
- Tobit I
Teaching forms | Workload (h) |
---|---|
1 week block seminar with lecture and exercise | 40 |
Exercises | 50 |
Total | 90 |
Examination: Exercises
Grading: In-class and homework assignments, where a minimum score of 50% is required to pass the module.
Credit points: 3 CP
Requirements: Basics in econometric course or
module 2500 AAE-1: Linear Models and Panel Data or
module 7600 Applied Microeconometrics and Impact Analysis
Language: English
Literature
- Greene, W. (2012): Econometric Analysis, 7th edition. Pearson
- Verbeek, M. (2012): A Guide to Modern Econometrics, 4th edition. John Wiley & Sons
Software: R
During the course all exercises can be conducted in R or Stata, while support will be given in R only and our handouts will be in R. If R is new to you please familiarize yourself with basics in R.
http://www.r-tutor.com/r-introduction
https://cran.r-project.org/doc/contrib/Torfs+Brauer-Short-R-Intro.pdf