10122601 Vorlesung

SoSe 21: Big Data in Economics

Lars Winkelmann


Inhalte & Qualifikationsziele

This course focuses on statistical methods and their application. To explore Big Data in Economics you need profound knowledge about statistical methods—their limitations and pitfalls. We will see that your standard stats (10120401) and econometric (10121201) methods fail in data-rich environments. We will focus on some key concepts: Time series, multiple testing, shrinkage, dimension reduction.



All material and instructions will be posted on blackboard. You can read, watch and learn anytime you want.

  • Due date for homework submissions: June 4th, 2021, 24:00.

  • Submission deadline for the paper review: July 2nd, 2021, 24:00.



Bachelor in Economics, 6 LP


Zugangsvoraussetzungen & Vorkenntnisse

Students are required to have taken the math (102007) and stats courses (10120401). Having taken econometrics (10121201) or taking econometrics concurrently is strongly recommended. Students are assumed to be familiar with basic concepts in linear algebra, analysis, probability theory and statistical inference. Basic programming abilities in R are required to be able to actively follow the tutorials and to solve the empirical problems. Students need to be willing to write their seminar report in the processing language LATEX.



You can register for this course via Campus Management.



Problem sets + Paper review








Studienfächer A-Z