Applied Regression Analysis
This course will provide participants who have basic skills in statistics and econometrics with an introduction to current core methods used in the analysis of observational, experimental and quasi-experimental data. The methods covered are widely used in economics and increasingly also required for good publications in top management journals.
The aim is to cover theory and selected applications, but more importantly to introduce participants to the use of statistical software that will allow them to apply the methods discussed in the course to data.
This course covers important methods used in the multivariate analysis of data. The course revisits basic concepts of the linear regression model and its properties and covers selected advanced topics such as the analysis of duration data and (quasi) experimental designs as well as methods to deal with the problems of endogeneity and sample selection. The theoretical basis of these methods is discussed but the focus of the course is on the application of the methods to data sets. Applications will be studied with the help of data provided by the lecturers and with reference to recent publications.
After the course, participants will…
- have a basic understanding of the theoretical underpinnings of multiple regression models.
- be able to apply regression methods to the investigation of economic relationships and processes.
- understand the econometric methods, approaches, ideas, results and conclusions met in the majority of economic books and articles.
- be aware of common pitfalls and mistakes to avoid when conducting regression analysis.
- be able to use the software program STATA to carry out empirical analysis based on regression analysis.
August 31 - September 03, 2021
Schlossplatz 1, 10178 Berlin
Prof. Dr. Georg von Graevenitz
Queen Mary University of London
Prof. Dr. Stefan Wagner
ESMT European School of Management and Technology Berlin