Estimation of Treatment Effects

Guest Instructor: 
Jan Nimczik
Time I: 
Tuesday,
08:30am to 10:00am
Time II: 
Tuesday,
02:15pm to 03:45pm
Venue I: 
HU, Spandauer Straße 1, Room 23
Venue II: 
HU, Spandauer Straße 1, Room 23
Description: 

This course presents nonparametric and semiparametric regression techniques and modern microeconometric methods for treatment effects estimation. The treatment focuses on the potential outcome approach, and students learn various methods to account for selection based on observables (regression, matching, inverse probability weighting) and for selection based on unobservables (Heckman selection correction, difference-in-differences, panel regression, instrumental variable regression, regression discontinuity design). These methods are used for cross-section data and longitudinal data, both repeated cross-sections and panel data. Students will familiarize themselves with applying the methods to real empirical data using Stata.

Literature:
Angrist, J. D. and J.-S. Pischke (2009): Mostly Harmless Econometrics – An Empiricist’s Companion, Princeton University Press.
Pagan, A. and A. Ullah (1999): Nonparametric Econometrics, Cambridge University Press
Wooldridge, J. M. (2010): Econometric Analysis of Cross Section and Panel Data. 2nd edition, Cambridge, MA: MIT Press

Exam:
Written exam (to register for the exam, PhD students must present a research paper)

Credits: 
6.00
Program: 
Semester: 
Fall 2018
Affiliation: 
Humboldt-Universität zu Berlin