Data Science the Econometric Way WS 2026/27

 

Lehrende/r: Prof. Dr. Reyn van Ewijk / Paul Witte

Veranstaltungsart: Vorlesung mit integrierter Übung / Lecture with integrated exercise

Anzeige im Stundenplan: Data Science EconWay

Semesterwochenstunden: 2+1

Unterrichtssprache: Englisch

 

Zugangsvoraussetzungen / Prerequisites

This course assumes that you already have some experience with regression analysis using ordinary least squares (OLS). Having passed the course “Empirische Wirtschaftsforschung” or a comparable course in Empirical Economics is therefore strongly recommended.

 

Lernziele / Learning Goals

This course provides students with essential data science skills. After completing the course, you should be able to:

  • Handle and analyze data using Stata
  • Understand and apply a core set of econometric methods (see below)
  • Apply a structured approach to data analysis, and understand and evaluate the assumptions underlying econometric analyses

 

Inhalt / Content

Handling and analyzing data, and understanding relationships between variables, are essential skills in today’s world. Econometrics can be seen as the original data science. It analyzes data in a highly structured way, with a focus on causal relationships, regression-based methods, and careful checking of assumptions.

In this course, you will gain practical experience in data handling and analysis using Stata. You will learn a core set of widely used econometric techniques, including ordinary least squares regression, panel data methods such as fixed and random effects and difference-in-differences analysis, as well as methods for handling binary dependent variables (probit and logit). The course also includes a “learn it from the pros” section, in which we discuss scientific articles.

 

Language: English

 

Literature: Selected chapters from Stock & Watson (2019), Huntington-Klein (2021), Wooldridge (2020), Cameron & Trivedi (2022), plus a few selected scientific articles