The course covers key concepts in econometrics and intends to widen and deepen students’ knowledge of econometric methods. The first few lectures introduce some important econometric estimators, focusing on asymptotic theory in a cross-sectional data setting. The second part of the course is devoted to time series econometrics. Techniques for modeling stationary and non-stationary time series are discussed.
The main goal of this course is to provide a fairly high level introduction to standard econometric theory. After completing the course, students should be able to (i) understand the theory behind the most commonly used econometric estimators; (ii) critically evaluate and undertake empirical work in economics; (iii) undertake more advanced studies in econometrics either in a classroom setting or as self-study.
Three or four assignments (15% each) and a final exam (40% or 55%). For audit: students should turn in each assignment and attain at least 50% on each; the final exam is not required.
- Mandatory for doctoral students unless exempted based on evidence of previous studies. Optional for MA students; first year core econometrics sequence or instructor's consent is required.