This module revises and expands the fundamental econometric techniques that students will have been exposed to at undergraduate level. On the basis that not all students will be strong econometrically, this module will focus on the key estimation process of econometrics (OLS) and the associated testing procedures around this technique. Students will also be introduced to econometric model building, the relevant data types and associated data issues as well as being exposed to econometric software. It is intended to deliver the module at a more rapid pace than at undergraduate level with a significant emphasis on the practical aspects of the subject.
The module will concentrate on 5 main econometric themes as follows:
Introduction to Econometrics: Data types, normal distribution, the sampling distribution, central limit theorem, measures of dispersion, the population mean and its properties. Hypothesis testing and confidence intervals.
Regression Analysis: Simple and multiple regressions, properties of the error term, regression estimates, regression methods, the residual and fitted values, OLS, R2 and adjusted R2, reverse regressions, the classical model.
Model Specification and the Associated Problems: Specification issues (omitted variables, irrelevant variables, lagged variables, functional form) and the Ramsey error specification test. Use of dummy variables and other specification issues.
Violations of the Classical OLS Assumptions:
- Multicollinearity: Perfect and imperfect multicollinearity consequences of multicollinearity, detection of and remedies for multicollinearity.
- Serial Correlation: Pure and impure serial correlation, first-order and higher order serial correlation, consequences of serial correlation, detection of and correcting serial correlation.
- Heteroskedasticity: Pure and impure heteroskedasticity, consequences of heteroskedasticity, testing of and remedies for heteroskedasticity.
Applying Econometric Techniques and Model Building: Using statistical software to produce and test econometric models while working with financial/economic datasets. Interpretation of and presentation of key econometric findings.
While formal lectures will be utilised, there will also be an emphasis upon laboratory work and, where appropraite, the undertaking of projects.
| Module Content & Assessment | |
|---|---|
| Assessment Breakdown | % |
| Formal Examination | 60 |
| Other Assessment(s) | 40 |