Content
The seminar gives an introduction to regression shrinkage methods (e.g. Ridge and Lasso
regressions). The students should be enabled to understand basic concepts in regression
shrinkage and to utilize recent results for their own applied work. Both econometric theory and
(economic) applications will be included in the course.
Learning outcomes
At the end of this module, students will be able to
- use regression shrinkage 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.
Examination
Seminar paper (50%), presentation (50%); seminar paper (approx. 10 pages without figures and
tables) and presentation (approx. 15 minutes) and participation in the discussions during the
seminar.
Prerequisites
The prerequisite courses include Empirical Research Methods or equivalent.
Media & reading list
Hansen Bruce: Econometrics, online textbook
available at http://www.ssc.wisc.edu/~bhansen/econometrics
Hastie Trevor, Tibshirani Robert and Friedman Jerome: The Elements of Statistical Learning,
Springer,
available at https://web.stanford.edu/~hastie/Papers/ESLII.pdf
Gareth James, Witten Daniela, Hastie Trevor and Tibshirani Robert: An Introduction to Statistical
Learning with Applications in R, Springer,
available at https://www.statlearning.com
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