458670-FS2025-0-PhD-Machine Learning in Economics





Root number 458670
Semester FS2025
Type of course Lecture
Allocation to subject Economics
Type of exam not defined
Title PhD-Machine Learning in Economics
Description *** IMPORTANT ***
For the most updated administrative course information (date changes, room changes etc) please always refer to the KSL page only and not to the Info page in ILIAS – the ILIAS infopage will not be updated!



The aim of this course is to provide students with an overview of the most common machine learning methods that are currently acquiring more and more importance in the economic analysis. Both the theoretical framework and implementation technique of the methods will be presented. Theory lectures will be complemented by exercise sessions in the computer lab. The software used in this course is RStudio, which can be freely downloaded. In particular, this course starts from the basics of model selection and introduces Lasso and Ridge regression, as well as the random tree, boosting, bagging, the random forest and its recent extension to the causal forest.


Assessment:
As final examination, students are expected to write a short paper (10 pages) in which they will apply one or more of the methods studied during the course. This paper accounts for 100% of the final grade. PhD students have the option of further preparing a presentation, in which they will detail a recent paper on machine learning methods. The presentation is graded with PASS/FAIL and allows PhD students to receive 6 ECTS (instead of 4.5 ECTS) for this course.

Lecture:

Thursday, 14.15 - 16.00 h, A322, PC Pool , UniS

1st term submission paper: 01.06.2025
Presentation: 22.05.2025
2nd term submission paper: 01.09.2025
ILIAS-Link (Learning resource for course) No registration/deregistration in CTS (Admission in ILIAS possible). ILIAS
Link to another web site
Lecturers Prof. Dr. Costanza NaguibDepartment of Economics 
ECTS 6
Recognition as optional course possible No
Grading 1 to 6
 
Dates Thursday 14:15-16:00 Weekly
Sunday 1/6/2025 00:05-23:55
Monday 1/9/2025 00:05-23:55
 
Rooms
External rooms A322, PC Pool, UniS
 
Students please consult the detailed view for complete information on dates, rooms and planned podcasts.