Logo Doctoral Certificate Program in Agricultural Economics Deutsch
Overview
Admission
Course of Study
Modules
Schedule
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Instructors

Module 6500 in Bonn
Advanced Applied Econometrics 2:
Limited Dependent Variable (LDV) / Choice models

Lecturers

Prof. Dr. Thomas Heckelei,  thomas.heckelei@ilr.uni-bonn.de
Prof. Dr. Silke Hüttel,  silke.huettel@uni-rostock.de

Aims

At the end of the course students shall

Skills: Methodological competence, quantitative analysis, conceptual thinking

Contents

Outline

I Maximum Likelihood Estimation (Verbeek Ch. 6.1 and 6.2

II Binary Choice Models (Verbeek Ch. 7.1)

III Multiple Choice Models

  1. Ordered Response Models (Verbeek Ch. 7.2, Greene Ch. 18.3)
    • Introduction
    • The ordered probit model
    • Estimation, Effects and Interpretation
    • Testing
  2. 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

IV Count data models (Verbeek Ch. 7.3)

V Tobit models (Verbeek Ch. 7.4-7.5)

  1. Tobit I
    • Utility maximisation problem
    • Standard Tobit model
    • Tobit estimation
    • Tobit specification test
  2. Tobit II (Double Hurdle)
    • Statistical model
    • Heckmann selection model
    • Estimation
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

Language: English

Literature

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