University of Illinois at Urbana-Champaign

Econ 507. Econometric Analysis. Spring 2011

Walter Sosa-Escudero (wsosa@illinois.edu)TA: German Caruso (gdcarus2@illinois.edu)

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.