Unit name | Foundations of Econometric Theory |
---|---|
Unit code | EFIM30050 |
Credit points | 20 |
Level of study | H/6 |
Teaching block(s) |
Teaching Block 1 (weeks 1 - 12) |
Unit director | Dr. Hubner |
Open unit status | Not open |
Pre-requisites |
EFIM20011 Econometrics 1 (Minimum mark of 60%) AND |
Co-requisites |
None |
School/department | School of Economics |
Faculty | Faculty of Social Sciences and Law |
The course is taught in two parts. The first part covers statistical theory essential for econometrics. It focuses on mathematical properties of probability distributions and sample statistics and on key concepts of statistical inference (estimators, tests, p-values, confidence intervals). The second part is concerned with detailed examination of linear regression and with maximum likelihood estimation.
[1] A good knowledge of fundamental econometric theory
[2] To handle theoretical propositions
[3] Rigorously prove the properties of the estimators
Teaching will be delivered through a combination of synchronous and asynchronous sessions such as online teaching for large and small group, face-to-face small group classes (where possible) and interactive learning activities
2 x assignments (10% each) (20%)
Online exam (80%)
The following textbooks cover the essential topics of the course. Students will be referred to parts of these
books as we proceed through the lectures:
Freund, J.E. Mathematical Statistics. Pearson Prentice Hall, 6th Edition, 1999. (available in the Arts and Social Sciences Library, ref. QA276 FRE)
Hogg, R.V., J. McKean and A.T. Craig. Introduction to Mathematical Statistics. Pearson Prentice Hall, 6th Edition, 2005. (available in Queen’s building Library, ref. QA276 HOG)
Greene, W.H. Econometric Analysis. Pearson Education, 7th Edition, 2012. (available in the Arts and
Social Sciences Library, ref. HB139 GRE)
Stock, J.H. and M.W. Watson. Introduction to Econometrics. Pearson Education, 3rd Edition, 2012.
(available in the Arts and Social Sciences Library, ref. HB139 STO)
The following textbooks go beyond the course content, but they may also be of interest for students:
Casella, G. and R. Berger. Statistical Inference. Duxbury Press, 2nd Edition, 2002. (available in Queen’s building library, ref. QA276 CAS)
Ruud, P.A. An Introduction to Classical Econometric Theory. Oxford University Press, 1st Edition, 2000.
(available in the Arts and Social Sciences Library, ref. HB139 RUU)