I will be co-teaching a course titled Advanced Econometrics: Recent Methods and Issues at the University of Copenhagen from June 22 to 26, 2020 with my colleague Arne Henningsen. Though the link lists Arne as the instructor, I will be teaching the lecture part of the course, and Arne will be teaching the lab part of the course.
If you are interested in taking the course, enrollment is open to students outside of the University of Copenhagen, and as of writing, registration is about $145, which is a bargain (though if you do register, you are obviously responsible for your travel and accommodation costs, but Copenhagen is lovely in June).
The course is not identical to the course Arne and I co-taught in May 2018 at Copenhagen, though it will certainly share some similarities. For starters, because I am teaching the entirety of Morgan and Winship (2015) to our first-year PhD students this semester, there will be a lot of emphasis on the nuts and bolts (i.e., potential outcomes model and directed acyclic graphs) of causal inference. Second, we will also update the material by covering recent papers which have been published since we last taught the course. Third, I will be holding office hours every day, and I will be happy to discuss your research project in detail with you.
Here is the course description:
Social science researchers are usually interested in investigating causal relationships. The analysis of causal relationships is generally easiest based on experimental data. The use of experiments in social sciences, however, has many limitations, and most empirical studies are based on observational (i.e., nonexperimental) data. The participants of this course will learn the theory and practice of state-of-the-art empirical approaches used for investigating causal relationships with observational data. The course participants will also learn how to evaluate and discuss the appropriateness of identification strategies for analysing causal relationships and to choose the most appropriate identification strategy for analysing a specific research question. All this will help the participants obtain more credible and reliable results in their empirical work and to publish their work in better journals. This course will have a similar general topic as the course “Advanced Applied Econometrics: Causal Inference with Observational Data” that the same two teachers taught in May 2018 but this new course will cover several new methodologies and innovations in applied econometrics, such as the use of directed acyclic graphs for identification, back-door adjustments, front-door criterion estimation, synthetic control methods, randomization inference, and so on.
My goal with this class is to go beyond the analytics, and to teach what people do in applied work, i.e., the tests they run, the robustness checks they present, the figures they show, and so on to make a convincing use of the various techniques just enumerated. I like to think about this as the live version of this ‘Metrics Monday series of posts. If anything, it’ll just be a good opportunity to hang out and talk about applied econometrics for a week!