Econometrics II (Advanced Econometrics)

Guest Instructor: 
Gabor Uhrin
Time I: 
Tuesday, 08:30am to 10:00am
Time II: 
Tuesday, 02:00pm to 04:00pm
Venue I: 
online
Venue II: 
online
Description: 

This course deals with advanced estimation techniques in modern econometrics. In the first part we study Pesudo-ML and GMM as extremum estimation problems with special attention to asymptotic theory and the weak instruments problem. The second part covers non- and semi-parametric topics including the bootstrap, density estimation, and non- and semi-parametric regression. The third part covers the concept of econometric identification, and possible frameworks to write down and interpret causal estimands (treatment effects). We also discuss a number of techniques for estimation of treatment effects (IV, Diff-and-Diff, RDD, Matching).

Literature:

tba

Exam:

Written exam (90 min)

More information can be found on Moodle: https://moodle.hu-berlin.de/enrol/index.php?id=102843

Credits: 
9.00
Program: 
Semester: 
Spring 2021
Affiliation: 
Humboldt-Universität zu Berlin