E471: Econometric Theory & Practice I

This course introduces students to basic econometric concepts and their application. Compared to E371, we will put more emphasis on the mathematical and statistical foundations of econometric methods. Therefore, students are expected to have a strong background in Linear Algebra and Calculus on the level of M303 and M311or equivalent. We will start with a review of matrix algebra, probability theory and statistics. Afterwards, the course covers linear regression models, which are the foundation of many econometric and machine learning methods, in detail. We will discuss (and prove) finite-sample and asymptotic properties of the OLS estimator. We continue with a discussion of statistical testing and conclude with an outlook on generalizations of the OLS estimator that tackle many prevalent problems. In several tutorial sessions, students will learn how to apply econometric methods to data using the statistical software R.

Since Fall 2021, this class is cross-listed as M504: Econometrics I, which is the first-semester Econometrics course of the M.Sc. program in Economics.

All lecture material is available on Canvas.