Microeconometric Methods for Big Data

This modul prepares students for empirical research (e.g. for their Master's Thesis). We discuss the following topics: 1. Main Concepts in Econometrics: Causal Effects and Ceteris Paribus Analysis, Data Structures and Sampling, etc. 2. Main Concepts in Asymptotic Analysis: Convergence in Probability, Convergence in Distribution, Slutsky's Lemma, Continuous Mapping Theorem, etc. 3. Asymptotic Theory for OLS, 2SLS and GMM 4. Regression Shrinkage Methods (Ridge, Lasso, Elastic Net) 5. Decision Trees, Random/Causal Forests

At the end of this module, students will be able to - use state-of-the-art econometric methods in empirical economics - understand the technical conditions and assumptions of these models - assess the limitations of these approaches in real applications - interpret the econometric results in a meaningful way - and apply this knowledge to enhance the decision-making process.

The final written exam (90 minutes) is to assess students' understanding of basic and advanced concepts in microeconometrics. Students have to show that they not only understand the econometric theories but also can apply this knowledge in empirical economics and interpret the results in a meaningful way. The exam is at least partly based on multiple choice questions. Students may use a non-programmable calculator. Students have the possibility to improve their final grade by taking a voluntarily midterm assignment. Participating successfully in this assignment improves the final grade by 0.3. The midterm assignment consists of handing in an exercise sheet, which may also include some data work. The completion of the exercise sheet is not mandatory, but highly recommended. The exercise sheet is to assess students' learning progress for the further course of the module.

The prerequisite courses include Empirical Research Methods or equivalent.

The module consists of lectures and integrated exercises. The lectures build a thorough understanding of microeconometric methods. In the exercises students learn to apply these methods in empirical economics. In addition to the integrated exercises, an excercise sheet is provided on which the student can practice individually and improve their final grade. Afterwards, the excercise sheet will be discussed in class. The excercise sheet includes various topics that are relevant for the exam.