There are no formal requirements, and students from all fields are welcome. However, a basic understanding of econometrics and statistical programming at the level of KS Empirical Economics and/or KS Intermediate Econometrics is necessary. Students who did not take these classes are urged to learn the material prior to the start of the semester.
Students learn advanced concepts in programming and data management using the statistical software package R. Upon successful completion, students are capable to handle R and understand data management at a level required for the subsequent classes in the JKU econometrics curriculum (e.g., KS/IK Treatment Evaluation, KS Microeconometrics, etc).
We start by discussing how to set up projects, arrange codes, and how to work with R objects. Based on these preliminaries, we will cover topics in data management (specifically how to combine, reorganize, and clean data), programming (e.g., how to use loops), as well as data analysis and visualization. A specific emphasis is placed on econometrics and big data. Most examples and exercises will be based on exemplary real-world data from the Austrian Social Security Database. We will discuss several particularities in handling big data sets throughout the course of the lecture.
The course will be taught in class but will also be live-streamed. Please make sure to download the following software packages before the start of the course:
If you're already comfortable with R/RStudio try and install the TinyTex package (Latex Distribution tailored to R) using the following command line: tinytex::install_tinytex().
50% problem sets, 50% take-home exam/ term-paper at the end of the semester.