E572 : Econometrics II - Regression / Time Series
This course is the second course in the three-semester core econometrics sequence for the economics Ph.D. students. The course is intended to teach extensively and rigorously the linear models, covering classical single equation models, multivariate regression models, seemingly unrelated regressions, panel data models, and simultaneous equation models. Basic time series models are also covered.
Semester(s) Offered: Spring
Instructor: Yoosoon Chang - email@example.com
Other Contact(s): Yoosoon Chang - firstname.lastname@example.org
Sequence: 2nd course in the 3-course core econometrics sequence
Prerequisites: Econ 571(Econometircs 1- Statistical Foundations)
Algebra Required?: Yes, extensively used for notation, proofs and also for assignments.
Calculus Required?: Assumed.
Day(s) per week offered: Two lectures a week
Recommended follow-up classes: E672-time Series, E724-Financial Econometrics and other econometrics topics courses.
Substantive Orientation: Finance, marketing, management science, statistics, applied mathematics, and SPEA and HPER(with strong math background)
Statistical Orientation: Classical approach
Applied/Theoretical: Theoretical, but empirical exercises are also given.
Software Used: NONE, MatLab
How the software is used: For empirical assignments. Matlab(recommended, but students may use other softwares if they so desire)
Problem Sets: Yes
Data Analysis: Yes
Exams: Yes - 2 midterms and final
Keywords: Univariate and multivariate linear regressions, seemingly unrelated regressions, analysis of panel data models, and simultaneous equation models