University of Illinois at Urbana-Champaign
Econ 507. Econometric Analysis. Spring 2011
Walter Sosa-Escudero ([email protected])TA: German Caruso
([email protected])
Course goals: This is a course for rst year PhD students in
Economics and related elds. It provides andintroduction to a
variety of econometric theories and methods useful for applied
research and further studiesin the eld.
Requisites: Statistics at the level of the Econ 506 course. We
will make intensive use of matrices, linearalgebra and basic
analysis.
Grading: There will be periodic homework assignments (20% of the
nal grade), a midterm (40%) and anal exam (40%). For the homework
you are encouraged to work in groups of no more than three
students,and hand in one copy of your work per-group. Exams are
individual.
Readings and course material: There is no required textbook,
though you may nd useful to consultthe following books, that cover
most of the topics in the course.
Hayashi, F., 2000, Econometrics, Princeton University Press,
Princeton. Davidson, R. and J. G. MacKinnon, 2004, Econometric
Theory and Methods, Oxford University Press,Oxford.
Other specic material that could be useful for parts of the
course are the following:
White, H., 2000, Asymptothic Theory for Econometricians, 2nd.
ed., Academic Press, New York.
Hall, A., 2005, Generalized Method of Moments, Oxford University
Press, Oxford.
Wooldridge, J., 2010, Econometric Analysis of Cross-Section and
Panel Data, 2nd ed., The MIT Press,Cambridge.
Angrist, J. and Pischke, J., 2009, Mostly Harmless Econometrics:
An Empiricists Companion, PrincetonUniversity Press, Princeton.
Newey, W. and McFadden, D., 1999, Large Sample Estimation and
Hypothesis Testing, in Handbook ofEconometrics. Vol. 4, McFadden,
D. Engle, R., eds, Elsevier, North-Holland, chapter 36, pp.
2113-2245.
I will teach mostly using slides, that will also serve the
purpose of lecture-notes. You are advised tobring a print out of
them to the lecture. All course material (slides, homework, data
sets and other courseinformation) will be handled through our
web-site, located at:
http://www.econ.uiuc.edu/ wsosa/econ507/index.htm
Course outline
1. The classical linear model and the least squares
estimator.
2. Finite sample properties of OLS estimator.
3. Hypothesis tests and condence intervals.
4. Large sample properties. Consistency, asymptotic normality
and variance estimation.
5. Geometric and algebraic properties. The Frisch-Waugh-Lovell
theorem.
6. Generalized least squares, heteroskedasticity and serial
correlation. Robust variance estimation.
7. Endogeneities. The generalized method-of-moments.
Instrumental variables. Identication and overi-dentication. Weak
instruments and nite-sample performance.
8. Maximun likelihood. Estimation. Large sample properties.
Examples.
9. Maximum likelihood based inference. LM, W, and LR tests.
10. The generalized method of moments. Non-linear models.
Estimation. Optimality.
11. The generalized method of moments. Inference.
Overidentication.
