Department of Economics
Faculty of Economics and Political Science
Cairo University
First Semester 2010/2011
Racha Ramadan
racha.ramadan@feps.eun.eg
http://sites.google.com/site/racharamadan/
Advanced Topics in Econometrics
Post Graduate
Introduction
This course covers econometric methods at the post graduate level. The aim of the course is to
provide you with econometric techniques that enable you to answer an interesting economic
question for your own research. Good quantitative analysis and interesting research question are
necessary requirements for a successful research.
The course emphasizes theory and applications. The course is oriented toward Cross Section and
Panel Data analysis. STATA software1 is used for applying the econometric methods studied on
empirical economic problems through computer exercises. There will be brief introduction for
STATA software.
The course requires being familiar with the material taught in the undergraduate Econometrics
courses.
Grades
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Several assignments (exercises, computer exercises, reports, presentations, articles’
discussion…etc) will have to be completed through the semester and delivered at a given
deadline.
Based on the assignment and your total number, you can collaborate and work in groups,
work group can be composed from two or three students.
Final Exam: Details to follow; Project or Written Exam.
Grades will be based on the performance in the final exam (70%) and in the assignments
(30%).
Textbooks:
1. Wooldridge, J., Econometric Analysis of Cross Section and Panel Data, first edition 2002.
2. William H. Greene, Econometric Analysis, Fifth edition.
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STATA software is installed in the Faculty labs.
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3. Additional reading list will be given through the course.
Syllabus:
Part I: Topics in Econometrics
I.1 Classical Regression Models:
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Assumptions.
Least Square (LS).
Partitioned Regression.
Goodness of fit.
Finite Sample properties.
Normality assumption and Basic Statistical Inference.
Data Problems.
I.2 Generalized Regression Model
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OLS and the Maximum Likelihood.
Generalized Least Square (GLS).
Wheighted Least Square (GLS).
Feasible GLS.
I.3 Large Sample properties
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Asymptotic properties of LS estimator.
I.4 Instrumental Variable.
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Hausman’s Specification Test.
Measurement Error.
Part II: System of Regression Equations: Simultaneous Equations Models
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Seemingly Unrelated Regression (SUR) Model.
Generalized Least Square.
Part III: Panel Data Models
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Ordinary Least Square Model.
Fixed Effect Model.
Random Effect Model.
Other Information
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Office hours: Thursday 1p.m-2 p.m.
The corresponding chapters and the readings will be announced for each topic.
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