Estimation of Treatment Effects

Time I: 
08:00am to 10:00am
Time II: 
02:00pm to 04:00pm
Venue I: 
HU Berlin, Spandauer Str. 1, room 23
Venue II: 
HU Berlin, Spandauer Str. 1, room 23

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 crosssections and panel data. Students will familiarize themselves with applying the methods to real empirical data using Stata.
Please check the homepage of the chair of econometrics for the course syllabus and for the course material covered in the first lecture before the first lecture on 15 October 2019.

AP: Angrist, J. D. and J.-S. Pischke (2009): Mostly Harmless Econometrics – An Empiricist’s Companion, Princeton University Press.
CT: Cameron, A. C. and P. K. Trivedi (2005): Microeconometrics – Methods and Applications, Cambridge University Press.
GR: Greene, W. (2008): Econometric Analysis, 6th, International Edition, Prentice Hall.
HL: Härdle, W. and O. Linton (1994): “Applied Nonparametric Methods”, in: Handbook of Econometrics, Vol. 4, R. F. Engle and O. F. McFadden, (eds.), Elsevier Science.
PU: Pagan, A. and A. Ullah (1999): Nonparametric Econometrics, Cambridge University Press.
WO: Wooldridge, J. M. (2010): Econometric Analysis of Cross Section and Panel Data. 2nd edition, Cambridge, MA: MIT Press (see also:
Further references, particularly regarding the method of Quantile Regression and the application of the methods, will be given in the course.

Written exam (90 min)

Fall 2019
Humboldt-Universität zu Berlin