Course Overview

This module deals with the advanced econometric methods applicable to micro data. In particular, discrete choice and selection models as well as advanced empirical evaluation methods are covered. Within the lecture, the participants are introduced to the theoretical concepts of the methods. Within the tutorials, these methods are discussed based on examples from the scientific literature.

Learning Achievement

Qualification targets: By the end of this course, students should be able to understand and evaluate empirical studies based on micro data and to be proficient in the subject-related terminology. Moreover, they should have the ability to choose the right empirical estimation strategy based on a given dataset/problem. Imparted soft skills: Analytical thinking, Independent studying and learning, Critical thinking

Competence

Course prerequisites

Advanced knowledge of empirical research and/or econometrics is recommended.

Grading Philosophy

100 % Written exam (90 min)

Course schedule

Week1: Introduction Week2: followed by Week3 to the Final Week

Course type

Online Course Requirement

Instructor

Prof. Dr. Thomas Bauer

Other information

a) Lecture b) Tutorial Learning material and relevant literature: Angrist/Pischke, (2008), Mostly Harmless Econometrics: An Empiricist’s Companion. Princeton University Press.; Cameron/Trivedi (2005), Microeconometrics: Methods and Applications. Cambridge University Press.; Further literature (journal articles) will be provided during the course

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