Advanced Econometrics


This course builds up on the course Econometrics I. Its goal is to make students acquainted with some fundamental concepts of estimation and inference for nonlinear econometric models. The course aims at providing students with the necessary theoretical background for further courses in econometrics. The tutorials consist of theoretical exercises, empirical applications and an introduction to the programming language Matlab.

  1. Asymptotic Theory
  2. IV Estimation
  3. ML and Pseudo-ML-Estimation
  4. Generalized Method of Moments
  5. Bayesian Econometrics
  6. Monte Carlo Simulations
  7. Bootstrapping


Econometrics I (or equivalent course).

Helpdesk Advanced Econometrics:

      When? Monday, 8:15-9:45, exception: first session on Thursday, November 10th, 8:15-9:45

      Where? Room F208

      Tutor? Mr. Luis Federico Flores 

Introductory Literature

Anatolsev, S. and Gospodinov, N. (2011): Methods for Estimation and Inference in Modern Econometrics, Chapman & Hall.

Bernardo, J. M., & Smith, A. F. (2000): Bayesian Theory, John Wiley & Sons.

Cameron, A.C. and Triverdi, P.K. (2006): Microeconometrics: Methods and Applications, Cambridge University Press (Cambridge).

Gourieroux, C. and Monfort, A. (1995): Statistics and Econometric Models, Vol. 1 and 2, Cambridge University Press (Cambridge).

Greenberg, Edward (2012): Introduction to Bayesian econometrics, Cambridge University Press (Cambridge).

Hansen, B.E. (2014): Econometrics, current manuscript,

Hayashi, F. (2002): Econometrics, Princeton University Press.

Koop, Gary (2004): Bayesian Econometrics, Wiley.

Lancaster, T. (2004): An introduction to modern Bayesian econometrics, Oxford (Blackwell).

Mittelhammer, R.C., Judge, G.G. and Miller, D.J. (2000): Econometric Foundations, Cambridge University Press (Cambridge).

Ruud, Paul A. (2000): An introduction to classical econometric theory, Oxford Univ. Press

Wooldridge, Jeffrey M. (2009): Introductory econometrics : a modern Approach, South Western Cengage Learning (4.ed.)

Wooldridge, Jeffrey M. (2010): Econometric analysis of cross section and panel data, MIT Press (2. ed.)

Form of Assessment

Grading is based on the Midterm Exam (20 %), 2 Take-Home Assignments (10 % each) and the Final Exam (60 %).

The Midterm exam takes place on Monday, December 12th from 17:00-18:30 in room A701.

Participation in the Midterm exam is compulsory.

There will be an oral exam for those students who cannot attend the mid-term exam due to illness, which takes place on Thursday, December 15th 

Advanced Econometrics Exam

The Advanced Econometrics exam takes place on Monday, 27. February 2017 10:00-11:30 in room R611.

Preparation Course

New msc economics students have the opportunity to visit a voluntary preparation course.
Dates and Rooms can be taken from below, see here for more detailed information.

Tuesday11/10/201613:30 - 16:45G227
Wednesday12/10/201613:30 - 16:45G227
Thursday13/10/201613:30 - 16:45G227
Friday14/10/201613:30 - 16:45G227 & BS 217 (CIP Pool)


17/10/201613:30 - 16:45

BS 217 (CIP Pool)

Lecture & Tutorial Dates

Schedule for the Lectures and Tutorials






R 511

R. Halbleib/ A. Virbickaite





G 300

R. Halbleib/ A. Virbickaite

Please note that the lecture ends on 27.01.2017.

Tutorials (during the weeks without scheduled PC Tutorials)

Group ATuesdaybeginning on: 08/11/16 15:15-16:45

G 227

J. Mareckova/ A. Morozova
Group BWednesdaybeginning on: 09/11/1615:15-16:45G 309J. Mareckova/ A. Morozova

 Computer Tutorials

Group ATuesday 22/11/1615:15-16:45G 309T. Dimitiradis
Tuesday20/12/16 15:15-16:45G 309T. Dimitiradis
Tuesday24/01/1715:15-16:45G 309T. Dimitiradis

Group B

Wednesday23/11/1615:15-16:45G 309

T. Dimitiradis

Wednesday21/12/1615:15-16:45G 309

T. Dimitiradis

Wednesday25/01/1715:15-16:45G 309

T. Dimitiradis

Group CThursday24/11/1617:00–18:30CIP Pool G 310

T. Dimitiradis

Thursday22/12/1617:00–18:30CIP Pool G 310

T. Dimitiradis

Thursday26/01/1717:00–18:30CIP Pool G 310

T. Dimitiradis

Course Materials

Please register for the lecture using ILIAS. The ILIAS password will be announced in the first lecture. Once you are registered, you get all news via mail and you can download the course material.