|Delivery Type||Delivery length / details|
|Assessment Type||Assessment length / details||Proportion|
|Semester Assessment||ASSESSED PROJECT WORK Semester two. Students will be required to undertake a brief research project, collecting their own data and identifying appropriate analytical methods as identified principally from learning outcomes 4-7.||30%|
|Semester Assessment||ASSESSED PRACTICAL COURSEWORK Semester one. Each student will be allocated a data set and required to undertake an analysis and to interpret the results with particular reference to learning outcomes 1-3.||20%|
|Semester Exam||2 Hours EXAM Semester two. Questions will be drawn from all of the module content.||50%|
On successful completion of this module students should be able to:
On completion of this module the 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 of single and multiple equation estimation techniques and
7) The advantages and shortcomings of panal data and the techniques for estimation of panel data models and their application.
The module is an advanced level study of econometrics. Building from basic principles in statistics we will discuss practical applications, both in the interpretation of empirical results and the use of computers to estimate original models.
This module is at CQFW Level 7