Vorlesung mit integrierter Übung

Advanced R for Econometricians

Name im Diploma SupplementAdvanced R for Econometricians
Anbieter Lehrstuhl für Ökonometrie (
LehrpersonProf. Dr. Christoph Hanck
M.Sc. Martin Christopher Arnold
M.Sc. Alexander Gerber
Turnusunregelmäßigmaximale Hörerschaft20

empfohlenes Vorwissen

A solid understanding of basic R programming as, for example, taught in our Master-level econometrics courses is required.


This course teaches advanced topics in R programming that become increasingly relevant for everyday applications in both applied and theoretical econometrics and empirical economics.

The first part of the course covers intermediate concepts in functional and object orientated programming, error handling, profiling and benchmarking as well as a treatment of selected R packages tailored for big data applications. Students are also introduced to reporting with dynamic documents. Part II deals with the tidyverse, a collection of packages designed for modern applications in data science. The third part introduces topics such as multi-core computing, C++ integration and other cutting-edge R extensions.

Students are prepared for applications in future studies and are able to efficiently tackle research-related programming tasks.


Part I

  • R at its Heart: Functional Programming
  • Getting it right: debugging, profiling and testing
  • Reporting: Reproducible Research with R Markdown

Part II

  • A Grammar of graphics: ggplot2
  • Keep it clean: selected tidyverse packages
  • Getting data: webscraping and text mining

Part III

  • Version control: git and github
  • Need for speed: Rcpp and RcppArmadillo
  • Harnessing power: parallelization
  • Show it to others: Shiny, R Packages


  • Eddelbuettel, D. (2013). Seamless R and C++ Integration with Rcpp. Springer
  • Grolemund, G.; Wickham, H. (2017); R for Data Science. O’Reilly
  • Matloff, N. (2011). The Art of R Programming. No Starch Press
  • Wickham, H. (2019). Advanced R. CRC Press
  • Wickham, H. (2009). ggplot2 - Elegant Graphics for Data Analysis. Springer
  • Xie, Y. (2018); R Markdown: The Definitive Guide. CRC Press

didaktisches Konzept

Presentation, discussion and joint solving of programming exercises.

Die Veranstaltung entspricht einem Vorlesungsanteil von 2 SWS und einem Übungsanteil von 2 SWS.


  • BWL-EaF-Ma-2015 > Wahlpflichtbereich > (1.-3. Fachsemester, Wahlpflicht) Modul "Advanced R for Econometricians"
  • ECMX-Ma-2019 > Wahlpflichtbereich > ME6 Applied Econometrics > (1.-3. Fachsemester, Wahlpflicht) Modul "Advanced R for Econometricians"
  • VWL-Ma-2009-V2013 > Wahlpflichtbereich I > (1.-3. Fachsemester, Wahlpflicht) Modul "Advanced R for Econometricians"
  • WiInf-Ma-2010 > Wahlpflichtbereich > Wahlpflichtbereich II: Informatik, BWL, VWL > Wahlpflichtmodule der Volkswirtschaftslehre > (1.-3. Fachsemester, Wahlpflicht) Modul "Advanced R for Econometricians"
WIWI‑C1138 - Vorlesung mit integrierter Übung: Advanced R for Econometricians