Econometrics (Master)
Lecture — Master's programme, Otto-von-Guericke University Magdeburg
Overview
This is a course about empirical research and micro-econometric methods. It is built from five blocks: lectures, quizzes, additional material, an introduction to the software R, and exercises. Each block is described below.
Classic textbooks such as Wooldridge (2003), Greene (2003), and Stock and Watson (2003) cover a wide range of econometrics and the fundamentals of regression theory, and remain useful for checking basic and advanced material. More recently, causal inference and micro-econometric methods have gained momentum, providing a toolbox for analyzing micro-data with an explicit focus on cause and effect — an angle reflected in newer texts by Angrist and Pischke (2008, 2014) and Cunningham (2021).
The course follows Huntington-Klein (2025), The Effect, for two reasons. First, it covers what a researcher doing applied empirical work wants in their toolbox: it starts from fundamental elements but also reaches state-of-the-art research methodology for scholars in economics, business, and finance. Second, students do not need to buy it — the chapters are freely available at theeffectbook.net.
The tables below list the lectures with their mandatory chapters, the additional classes, and the five sets of exercises. Exercises are done in R, and I provide the solutions after each tutorial. The slides, the exercise material, and the quizzes live on the OVGU e-learning page (see Materials), which also carries the exact dates and times for each lecture and exercise. The course textbook is freely available online at theeffectbook.net.
Lectures
| No. | Title | Mandatory chapters from Huntington-Klein (2025) |
|---|---|---|
| L1 | Introduction | 1. Designing Research; 2. Research Questions |
| L2 | Variables and Relationships | 3. Describing Variables; 4. Describing Relationships |
| L3 | Identification | 5. Identification |
| L4 | Causal Diagrams | 6. Causal Diagrams; 7. Drawing Causal Diagrams |
| L5 | Closing Back Doors and Finding Front Doors | 8. Causal Paths and Closing Back Doors; 9. Finding Front Doors |
| L6 | Treatment Effects | 10. Treatment Effects; 11. Causality with Less Modeling |
| L7 | Regression | 12. Opening the Toolbox; 13. Regression |
| L8 | Matching and Simulation | 14. Matching; 15. Simulation |
| L9 | Fixed Effects | 16. Fixed Effects |
| L10 | Event Studies | 17. Event Studies |
| L11 | Difference-in-Differences (DID) | 18. Difference-in-Differences |
| L12 | Instrumental Variables (IV) | 19. Instrumental Variables |
| L13 | Regression Discontinuity (RDD) | 20. Regression Discontinuity |
| L14 | Other Methods and Uncertainty | 21. A Gallery of Rogues: Other Methods; 22. Under the Rug |
Additional Material
| No. | Title | Literature |
|---|---|---|
| A1 | Introduction to R | Alexander (2023), appendix A and B (online version) |
| A2 | The Issue of Endogeneity and Causality | Cunningham (2021), chapters 2.11 ff. and 4 (online version) |
A1: Introduction to R
This lecture introduces the software R. Before it, students need to install R and RStudio on their computers to follow along and use R on their own (see Alexander 2023, chapters A.3.1 and A.3.2). The lecture is online only. Afterward, students should be acquainted with R's working environment — this is basic, since all exercises are in R. We work through an R script (Introduction to R) to learn how to process data, plot distributions and relationships, and understand and present distribution moments. The script is in the course repository on GitHub (see Materials).
A2: The Issue of Endogeneity and Causality
This is the only session not based on Huntington-Klein (2025). The slides appear after the lecture on regression, and the content is based on Cunningham (2021), chapters 2.11 ff. and 4.
Exercises
There are five sessions with exercises, posed as open questions on a specific topic. Each session comes as a folder on the e-learning page holding a short teaser, the exercise, and an R script with the questions to work through. The worked script, with the answers written out alongside the code, follows after the tutorial. The exercises are done in R.
| No. | Title | Chapters from Huntington-Klein (2025) |
|---|---|---|
| E1 | Regression | 12. Opening the Toolbox; 13. Regression |
| E2 | Fixed Effects | 16. Fixed Effects |
| E3 | DID | 18. Difference-in-Differences |
| E4 | IV | 19. Instrumental Variables |
| E5 | RDD | 20. Regression Discontinuity |
Quizzes
Each lecture is accompanied by a set of quizzes. Their purpose is to let students check their understanding of the content provided by each lecture and the reading material. The quizzes are available on the e-learning platform.
Materials
The lecture slides, the material for the five tutorial sessions, and the quizzes are on the e-learning page at OVGU. Each tutorial folder holds a teaser, the exercise, and an R script with the questions, and the worked script follows after the session.
The course room runs on OVGU Moodle and needs an OVGU account to log in.
The R script for the introduction to R in session A1 is in the public course repository on GitHub, which also carries the same introduction as an optional Python script and extra material added during the term.
References
- Huntington-Klein, N. (2025). The Effect: An Introduction to Research Design and Causality. 2nd ed. Chapman & Hall. theeffectbook.net
- Cunningham, S. (2021). Causal Inference: The Mixtape. Yale University Press. mixtape.scunning.com
- Alexander, R. (2023). Telling Stories with Data: With Applications in R. Chapman and Hall/CRC. tellingstorieswithdata.com
- Angrist, J. D., & Pischke, J.-S. (2008). Mostly Harmless Econometrics: An Empiricist's Companion. Princeton University Press.
- Angrist, J. D., & Pischke, J.-S. (2014). Mastering 'Metrics: The Path from Cause to Effect. Princeton University Press.
- Wooldridge, J. M. (2003). Introductory Econometrics: A Modern Approach. Cengage Learning.
- Greene, W. H. (2003). Econometric Analysis. Pearson Education.
- Stock, J. H., & Watson, M. W. (2003). Introduction to Econometrics. Addison Wesley.