Course Description
The course provide modern tools and papers relevant to big data in econometrics. The aim of the course will be a)provide the necessary toolbox b) go over the main proofs in the big data literature c) analyze some papers. The main topics will be high dimensional inference, moderate self deviation, Neyman orthogonality, approximate means, multiplier bootstrap, and deep learning.
Fall 2024
Instructors
Meeting Patterns
Classes Start:
August 19, 2024
Classes End:
December 3, 2024
Location:
04163 Nelson Hall
Class Days:
M W
Class Start Time:
10:15am
Class End Time:
11:30am
Class Type:
Lecture
Credits:
3.00
Restrictions:
P: ECG 751
