In the context of econometrics, statistical methods are applied to solve business problems or to verify and quantify economic theoretical relationships. The courses Statistics I and II already introduce one of the essential methods of econometrics with the classical simple regression and the master course Econometrics deals with further problems of econometrics. In the context of your bachelor or master thesis in the field of econometrics you can extend your basic knowledge from Statistics I & II or deepen your advanced knowledge from econometrics.



  • Regression with non-continuous target variables (discrete, restricted, ordinal, binary target variable)
  • Quantile regression
  • Nonlinear regression (variable transformations, nonparametric models)
  • Variable selection methods (penalized regression, forward and backward selection)
  • Data cleaning: outlier handling and dealing with missing values
  • Robust regression
  • Testing for structural breaks in linear regression models
  • Graphical data analysis


All topics should include an empirical component to illustrate or apply their theoretical basis.


Research associate
Faculty of Business and Economics
  • Room 2324 (Building J)