Unit name | Econometrics |
---|---|
Unit code | ECONM1022 |
Credit points | 15 |
Level of study | M/7 |
Teaching block(s) |
Teaching Block 1 (weeks 1 - 12) |
Unit director | Dr. David Pacini |
Open unit status | Not open |
Pre-requisites |
None |
Co-requisites |
None. |
School/department | School of Economics |
Faculty | Faculty of Social Sciences and Law |
The course is divided into two parts. The first part will cover the linear regression model with one regressor, the linear regression model with multiple regressors, hypothesis testing, confidence intervals and ways to assess the internal and external validity of studies based on multiple regression. This part will also introduce asymptotic analysis, heteroskedasticity, and several potential sources of biases and inconsistency in OLS estimation. The second half of the course will investigate more advanced methods of estimation such as generalised least squares (GLS) and instrumental variables (IV) methods before examining the methods and properties of maximum likelihood estimation and related test statistics.
Aims:
To give students a thorough understanding of econometrics, in particular OLS and its extensions to GLS and IV.
At the end of this unit students will be able to:
24 hours divided typically between 16 x 1 hour lectures, 4 x 1 hour exercise lectures and 4 x 1 hour seminars.
Summative assessment is by 3 hour unseen exam which will assess the learning outcomes specified above.
Formative assessment is by weekly exercises.
The main textbook is:
M. Verbeek, A Guide to Modern Econometrics, 2012, Fourth Edition, Wiley.
Other recommended textbooks are:
M. Murray, Econometrics: A Modern Introduction, 2006, Pearson Education.
J. H. Stock and M.W. Watson, Introduction to Econometrics, 2nd edition, 2007, Pearson Education.
J. Wooldridge, Introduction to Econometrics, Europe, Middle East and Africa Edition, 2014, Cengage Learning.