E703 Advanced Econometrics I - Universität Mannheim

Universität Mannheim Fall Semester 2012
Department of Economics Professor Andrea Weber
E703 Advanced Econometrics I
Syllabus –Sept/03/2012
Course Overview and Objectives:
This course will introduce the statistical analysis of linear models, as applied to economic
data. The first part of the course will be devoted to the formal derivation of the theoretical
foundations of the linear regression model. The second part focuses on applications of
this theory to particular problems in the analysis of economic data.
By the end of the course, students should have a firm grasp of the fundametals of
econometric theory and a critical understanding of sensible applications of econometric
methods to empirical problems.
Time and Place:
Lectures: Tuesday, 10:15 – 11:45, Thursday, 10:15 – 11:45; L7, 001
First Lecture: October 9
Exercise Sections: 1) Monday, 8:30 – 10:00 (Andreas Landmann, L9, 1-2, 003)
2) Monday, 10:15 – 11:45 (Andreas Landmann, L9, 1-2, 003)
3) Friday, 8:30 – 10:00 (Andreas Landmann, L9, 1-2, 003)
Exercise sessions start in the week of October 8.
Contact and Office Hours
Professor Andrea Weber, L7, 3-5, Room 4.20, a.weber@uni-mannheim.de
Office hours: Tuesday 14:00 – 15:00.
Appointment: if you cannot make the office hours, send an email and request an
appointment
Teaching Assisitant:
Andreas Landmann, andreas.landmann@uni-mannheim.de, office hours by appointment.
Course Requirements:
The course is intended for Masters and first year PhD students from the GESS program.
Students should have prior knowledge of undergraduate level econometrics. Working
knowledge of basic probability theory, differential calculus, linear algebra and matrix
algebra are also assumed. Attendance in the lectures and exercise sessions are mandatory.
Exercise sessions are organized such that there are smaller exercise groups with about 20
students each. Preparing reading assignments, attempting exercise questions ahead of
each session, and taking active part during the course of the sessions are essential.
Important: If you have not taken an undergraduate econometrics course, preparatory reading
is strongly advised, for example:
Stock and Watson, “Introduction to Econometrics”, Part one and two (chapters 1-9)

Grading:
Assessment will be based on a final written exam and homework exercises.
Postive credits for the homework exercises will not be applied to the retake exam.
Final exam: Friday, December 21.
Readings:
The first part of the course will concentrate on the theory of the classical linear regression
model and follow closely Hayashi (2000). The second part focuses on applied
econometrics, especially topics in the area of micro-econometrics. This part follows the
textbook by Wooldridge (2010). But time permitting, we will also go over a few applied
papers to discuss the motivation and interpretation of the theoretical estimation
procedures.
Recommended textbooks:
Hayashi, F. (2000) Econometrics, Princeton University Press (Main text, first part)
Jeffrey Wooldridge (2010), Econometric Analysis of Cross Section and Panel Data (MIT
Press), Second Edition. (Main text, second part)
Angrist, J. and S. Pischke, Mostly Harmless Econometrics, Princeton University Press
Wiliam H. Greene, Econometric Analysis, Prentice-Hall
Additional Reading:
Additional reading material will be handed out during the lecture or posted on Ilias.

Tentative Schedule and Reading Assignment
Week Topics
1 Oct 9, 11
The Classical Linear Regression Model, Gauss Markov Theorem, Maximum
Likelihood Hypothesis Testing under Normality
Read: Hayashi, Chapter 1.1-1.5
2 Oct 16, 18 Generalized Least Squares, Concepts of Asymptotic Theory
3 Oct 23, 25
Read: Hayashi, Chapter 1.6, 2.1
Large Sample Propterties of OLS in random samples, Large Sample
Propterties of OLS in stationary ergodic samples, Testing for serial
correlation
Read: Wooldridge Chapter 4.1,4.2; Hayashi, Chapter 2.2-2.6, 2.10
4 Oct 30 Modelling Serial Correlation
Read: Hayashi, Chapter 6.1-6.4
5 Nov 6, 8 GMM and two stage least squares estimation
Read: Hayashi, Chapter 3, Wooldridge Chapter 4.3, 5
6 Nov 13, 15 Causality in the linear regression model, instrumental variables
Read: Wooldridge, Chapter 6
7 Nov 20, 22 Specification Problems: Functional Form Analysis, Measurement Error
Read: Card (1995), Ahenfelter and Krueger (1994)
8 Nov 27, 29 Panel Data, Research Design for Applied Research
Read: Wooldridge, Chapter 7 and 10
9 Dec 4, 6 Heterogeneity and Nonlinearity: The Evaluation Model
December 21 Final Exam
Read: Wooldridge, Chapter 21.1 – 21.3