Course: Introductory Econometrics (lecture) (5202-421)

Persons:

• Prof. Dr. Robert Jung (verantwortlich)
• Prof. Dr. Aderonke Osikominu (verantwortlich)

Type of Course:

lecture

In-Class Hours Per Week:

4

Contents:

The purpose of the course is to familiarize you with core techniques in modern Econometrics. We extensively cover Ordinary Least Squares (OLS) estimation of the linear regression model, the econometric workhorse. We consider the properties of the OLS estimator and the main specification issues of the linear regression model both in a cross-section and a time series context. We further discuss important microeconometric methods such as instrumental variables estimation and models for binary dependent variables. Finally, we turn to important methods and concepts necessary to analyze economic and financial time series data. We cover stationary ARMA-models, dynamic regression models and
(univariate) models for non-stationary time series.
While we spend some time with formal derivations, we focus on the essential ideas and intuition of the methods. The applications discussed in class provide hands-on experiences in implementing econometric estimators in Stata and interpreting empirical results. At the end of the course, you will understand the basics of empirical research and be able to conduct own basic empirical analyses. The course also provides the basis for further courses specializing in Microeconometrics or Time Series Econometrics.

Literature:

Kirchgässner, Gebhard, Jürgen Wolters, and Uwe Hassler (2013): Introduction to Modern Time Series Analysis. Heidelberg: Springer, second edition.

Verbeek, Marno (2012): A Guide to Modern Econometrics, Chichester: John Wiley, fourth edition.

Wooldridge, Jeffrey M. (2013): Introductory Econometrics: A Modern Approach, Cincinnati (OH): Thomson South-Western, fifth edition.

Location:

Hohenheim

Module:

• 5202-420 Introductory Econometrics (compulsory)

eLearning:

Course in ILIAS