| 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 | Professor. Windmeijer |
| 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, nonlinear regression functions, and ways to assess the internal and external valididty of studies based on multiple regression. This part will also introduce asymptotic analysis, heteroskedasticity, serial correlation, 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 methods before examining the methods and properties of maximum likelihood estimation and related test statistics. The course finishes with an introduction to econometric time series analysis.
Aims:
To give students a thorough understanding of econometrics, in particular OLS and its extensions to GLS and IV.
Students will be understand econometric models, know how they are estimated and be able to evaluate econometric results.
Lectures and classes.
Summative assessment is by 3 hour unseen exam which will assess the learning outcomes specified above.
Formative assessment is by exercises and computer work.
In all cases the latest edition is most appropriate but students may be able to use earlier editions.
