| Day | Time | Lecture Hall | Session Type |
|---|---|---|---|
| Monday | 14:00 - 15:30 | H80 (Philosophikum) | Lecture |
| Wednesday | 17:45 - 19:15 | S82 (Philosophikum) | Exercises |
Advanced Econometrics II
Nonlinear Methods and Applications
Summer 2025 – University of Cologne
Organization of the Course
Advanced Econometrics II – Nonlinear Methods and Applications is a graduate-level course in regression analysis focusing on specialized econometric tools. We cover topics such as linear regression, panel data methods, causal inference, high-dimensional regression, and time series methods. Emphasis is on both theoretical understanding of the methods and practical applications using the R programming language.
Timetable
See KLIPS Lecture and KLIPS Exercises for a detailed schedule.
Note: On Wednesday, April 16, we will have a lecture instead of exercises.
Please bring your own laptop to the Wednesday exercise sessions. If you do not have a laptop available, please let me know by email.
Lecture Material
This online script and its pdf version
Rscripts and additional files: sciebo folder
More info on exam: ILIAS course
Literature
The script is self-contained. To prepare well for the exam, it’s a good idea to read this script.
The course is based on James H. Stock and Mark W. Watson’s Introduction to Econometrics (Fourth Edition). The Stock and Watson textbook is available for download: PDF by chapter (Uni Köln VPN connection required).
Further recommended textbooks are:
- Econometric Theory and Methods, by Russell Davidson and James G. MacKinnon. PDF.
- Econometric Analysis of Cross Section and Panel Data, by Jeffrey M. Wooldridge. PDF by chapter.
- An Introduction to Statistical Learning with Applications to R (Second Edition), by Gareth James, Daniela Witten, Trevor Hastie, and Robert Tibshirani. PDF.
- Causal Inference: The Mixtape, by Scott Cunningham. Online version.
- Mostly Harmelss Econometrics, by J. Angrist and J. Pischke PDF by chapter.
Printed versions of the books are available from the university library.
Assessment
The course will be graded by a 90-minute exam. For detailed information please visit the ILIAS course.
Communication
Feel free to use the ILIAS Metrics Forum to discuss lecture topics and ask questions. Please let me know if you find any typos in the lecture material. Of course, you can reach me via e-mail: sven.otto@uni-koeln.de
Important Dates
| Registration deadline exam 1 | July 28, 2025 |
| Exam 1 | August 04, 2025 |
| Registration deadline exam 2 | September 12, 2025 |
| Exam 2 (alternate date) | September 19, 2025 |
Please register for the exam on time. If you miss the registration deadline, you will not be able to take the exam (the Examinations Office is very strict about this). You only need to take one of the two exams to complete the course. The second exam will serve as a make-up exam for those who fail the first exam or do not take the first exam.
R-Packages
To run the R code of the lecture script, you will need to install some additional packages. Here are the most important ones for this lecture:
install.packages(
c("fixest", "AER", "moments", "glmnet", "urca", "caret", "neuralnet",
"dplyr", "knitr", "tinytex", "stargazer", "scatterplot3d", "readxl", "modelsummary")
)Some further datasets are contained in my package TeachData, which is available in a GitHub repository. It can be installed using the following command:
install.packages("remotes")
remotes::install_github("ottosven/TeachData")