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Curricular information is subject to change
By the end of this module students should be able to:
1. describe the properties and shortcomings of a variety of econometric models and estimators,
2. apply the methods analyzed in class on macro and finance data.
Student Effort Type | Hours |
---|---|
Lectures | 22 |
Computer Aided Lab | 10 |
Autonomous Student Learning | 80 |
Total | 112 |
Not applicable to this module.
Description | Timing | Component Scale | % of Final Grade | ||
---|---|---|---|---|---|
Assignment: Graded assignment involving the estimation of econometric models on real world data | Week 8 | n/a | Alternative linear conversion grade scale 40% | No | 20 |
Examination: 2 hour end of trimester exam. Essay type questions. | 2 hour End of Trimester Exam | No | Alternative linear conversion grade scale 40% | No | 80 |
Resit In | Terminal Exam |
---|---|
Spring | Yes - 2 Hour |
• Group/class feedback, post-assessment
• Self-assessment activities
1. Regular problem sets will be assigned throughout the semester for self-assessment; solutions will be posted on Brightspace and will be explained in detail during tutorials. 2. Appointments will be given to those students wishing to get individual feedback on the empirical assignments and the final examination.
Name | Role |
---|---|
Xidong Guo | Tutor |
Lecture | Offering 1 | Week(s) - Autumn: All Weeks | Fri 13:00 - 13:50 |
Lecture | Offering 1 | Week(s) - Autumn: All Weeks | Tues 14:00 - 14:50 |
Tutorial | Offering 1 | Week(s) - Autumn: All Weeks | Mon 13:00 - 13:50 |
Tutorial | Offering 2 | Week(s) - Autumn: All Weeks | Wed 17:00 - 17:50 |