Module Identifier ECM1020  
Module Title EMPIRICAL METHODS IN FINANCE  
Academic Year 2003/2004  
Co-ordinator Professor Andrew Henley  
Semester Semester 2 (Taught over 2 semesters)  
Other staff Dr Mark J Rhodes  
Pre-Requisite Registered on the MSc Accounting and Finance  
Course delivery Seminars / Tutorials   1 seminars per week over semester 1 and 2  
  Lecture   1 lectures per week over semester 1 and 2  
Assessment
Assessment TypeAssessment Length/DetailsProportion
Semester Exam2 Hours  50%
Semester Assessment assessed practical  20%
Semester Assessment project  30%
Supplementary Assessment students who fail must resit any or all failed elements   

Learning outcomes

On completion of this module students should be able to: Critically evaluate (1) the use of classical linear regression in estimation and inference, (2) the consequences of the failure of the classical regression assumptions, their diagnosis, consequences and solutions, (3) the specification, estimation and properties of dynamic time series models, including those with dynamic error structures, (4) the specification, estimation and properties of simultaneous equation regression models, (5) the implications of unit roots in time series and the importance of cointegration, (6) the use single and multiple equation estimation techniques and (7) the advantages and shortcomings of panel data and the techniques for estimation of panel data models and their application.

Aims

The module is an advanced level study of econometrics. The module is a combination of two existing MSc level econometrics modules and will be core on the revised MSc Accounting and Finance scheme. The module will not be available to students registered on other degree schemes.

Brief description

The module is an advanced level study of econometrics. On completion of this module students should be able to: Critically evaluate (1) the use of classical linear regression in estimation and inference, (2) the consequences of the failure of the classical regression assumptions, their diagnosis, consequences and solutions, (3) the specification, estimation and properties of dynamic time series models, including those with dynamic error structures, (4) the specification, estimation and properties of simultaneous equation regression models, (5) the implications of unit roots in time series and the importance of cointegration, (6) the use single and multiple equation estimation techniques and (7) the advantages and shortcomings of panel data and the techniques for estimation of panel data models and their application.

Reading Lists

Books
Gujarati D. (1995) Basic Econometrics 3rd edition. McGraw-Hill
Johnston, J. and J Dinardo (1997) Econometrics Methods 4th edition. McGraw-Hill
Enders W. (1995) Applied Econometric Time Series Wiley

Notes

This module is at CQFW Level 7