Aims

The module seeks to:
- explain how econometrics have been used and can be used to test theories in economics and finance literature
- provide a comprehensive set of fundamental technical skills necessary to pursue empirical research in economics and finance
- offer the opportunity to develop some key quantitative skills that are highly valued in the private sector

The module covers essential material from probability theory, data description, hypothesis testing, and regression analysis with a particular focus on the analysis of cross-sectional data.

Outline Of Syllabus

1. Simple Regression Model: population versus sample regression function, the method of Ordinary Least Squares (OLS), assumptions of the classical linear regression model, obtaining and interpreting the OLS estimates, statistical properties of estimators, measures of fit
2. Classical Normal Linear Regression Model: hypothesis testing and confidence interval estimation.
3. Extensions of the linear regression model: regression through the origin, units of measurement, standardization, logarithmic and semi-logarithmic models.
4. Multiple Regression Model: restricted least squares, tests for multiple linear restrictions.
5. Dummy Variable Regression Models: describing qualitative information, qualitative regressors, analysis of variance (ANOVA) models, regression with a mixture of quantitative and qualitative regressors (ANCOVA models).
6. Relaxing the assumptions of the classical model – multicollinearity, non-normality, heteroskedasticity, and serial correlation: consequences, detection, and robust inferences in their presence.

Teaching Rationale And Relationship

-Lectures provide the fundamental technical structure of the methods introduced and an overview of the essential empirical economic and financial modelling methods
- Seminars provide an opportunity to enhance both theoretical and practical (computer-based) aspects of modelling

Assessment Rationale And Relationship

The PC examination is an appropriate way to assess the theoretical understanding and problem solving skills under the time constraint as required in industry.