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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 data.
|Student Effort Type||Hours|
|Autonomous Student Learning||
|Computer Aided Lab||
Not applicable to this module.
|Description||Timing||Component Scale||% of Final Grade|
|Examination: Final exam. Essay type questions.||2 hour End of Trimester Exam||No||Alternative linear conversion grade scale 60% (Chinese modules)||No||
|Assignment: Graded assignment that will involve analysis of real world data using the methods of the course||Week 4||n/a||Alternative linear conversion grade scale 40%||No||
|Assignment: Graded assignment involving the analysis of real world data using the methods of the course.||Week 8||n/a||Alternative linear conversion grade scale 40%||No||
|Resit In||Terminal Exam|
|Summer||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.
|Lecture||Offering 1||Week(s) - 20, 21, 22, 23, 24, 25, 26, 29, 30, 32, 33||Fri 11:00 - 12:50|
|Computer Aided Lab||Offering 2||Week(s) - 20, 21, 22, 23, 24, 25, 26, 29, 30, 31, 32, 33||Thurs 13:00 - 13:50|