Syllabus
This is the first part of the basic sequence of econometric courses
provided by the graduate program of the Department of Economics at
FEA-USP. This first course covers the estimation of linear regression
models in cross-sections and panel data, and introduces the student to
the problem of identification of economic models. Knowledge of
probability, statistics, and matrix algebra (all at the level of the
summer course provided by the department) are prerequisites for the
course.
Content and readings
The ordinary least squares estimator: asymptotic properties; conditional expectations and linear projections; inference and hypothesis testing; heteroskedasticity and clustered sampling. Bibliography: Hansen (2022): ch. 2 (up to 2.25), ch. 3 (up to 3.18), ch. 4, ch. 7.1-7.3 and 7.12-14, and ch. 9 (up to 9.10 and 9.20). [Slides] [Exercise list].
Instrumental variables and causal effects: identification: Rubin causal model and potential outcomes; omitted variable bias and measurement errors; properties of the estimator and two-stages least squares; average and local average treatment effects; control functions and specification tests. Regression in discontinuity design. Bibliography: Hansen (2022): ch. 12. [Slides] [Exercise list].
Panel data: Panel data and pooled linear regression; fixed effects and random effects models; first differencing and lagged dependent variables. Difference-in-differences. Bibliography: Hansen (2022). ch. 17 and ch. 18. [Slides] [Exercise list].
The textbook mentioned above used for this course is:
- Hansen, Bruce. Econometrics. Princeton University Press, 2022.
Other books that are potentially useful:
- Hayashi, Fumio. Econometrics. Princeton University Press, 2000.
- Greene, William H. Econometric Analysis. Prentice Hall, 6th edition, 2008.
- Newey, W.K. And Mcfadden, D.L. Large sample estimation and hypothesis testing. In: Handbook of Econometrics, vol IV, ch. 36, 1994.
- Wooldridge, Jeffrey M. Econometric analysis of cross section and panel data. MIT press, 2010. (2ª edição.)
- Cameron, A. Colin, and Pravin K. Trivedi. Microeconometrics: methods and applications. Cambridge university press, 2005.
Grading
Three (3) lists of exercises, graded, worth 10% of final grade each, one per topic. One exam, worth 70% of the final grade, based on the lists and class material: 5 points applied/interpretative, 1 question from the list with small changes, 1 new analytic question. [Exam 2023]
- If the final grade \(\geq\) 50%: letter grade B or more
- Else: second evaluation: second evaluation is another exam (same style). Those with grade > 50% are approved with C; otherwise fail.
Ethics
Lists can be discussed in group, and you are free to ask questions of your colleagues and/or the TA, but the lists need to be written and delivered individually. Plagiarism in any of the exercise lists (analytical and/or applied) will lead to a zero on all three lists.
Exams are individual and closed book. Any kind of cheating on the exam will lead to an immediate fail (R) in the course, without prejudice of any administrative action.
Office Hours
I’ll leave the link to schedule office hours at the Moodle website for the course. If the office-hours time is not possible for you, please send me an e-mail.
Teaching assistant
The teaching assistant for this course will be Felipe Santos. Please schedule a weekly session with him.