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| EKOZ6570 | Selected Topics inTime Series Analysis II | 3+0+0 | ECTS:7.5 | | Year / Semester | Spring Semester | | Level of Course | Third Cycle | | Status | Compulsory | | Department | DEPARTMENT of ECONOMETRICS | | Prerequisites and co-requisites | None | | Mode of Delivery | | | Contact Hours | 14 weeks - 3 hours of lectures per week | | Lecturer | Prof. Dr. Zehra ABDİOĞLU | | Co-Lecturer | | | Language of instruction | Turkish | | Professional practise ( internship ) | None | | | | The aim of the course: | | The main objective of this course is to introduce some of the techniques that are used in time series analysis. |
| Programme Outcomes | CTPO | TOA | | Upon successful completion of the course, the students will be able to : | | | | PO - 1 : | recognize some of the frequently-used time series techniques. | 2 - 3 | 1, | | PO - 2 : | recognize when and how to use these new techniques. | 2 - 3 | 1, | | PO - 3 : | make predictions by using time series. | 2 - 3 | 1, | | PO - 4 : | evaluate the findings of applications about time series. | 2 - 3 | 1, | | PO - 5 : | produce micro or macro policies based on hypothesis investigated and forecast chosen. | 2 - 3 | 1, | | CTPO : Contribution to programme outcomes, TOA :Type of assessment (1: written exam, 2: Oral exam, 3: Homework assignment, 4: Laboratory exercise/exam, 5: Seminar / presentation, 6: Term paper), PO : Learning Outcome | | |
| Cointegration, Vector Autoregressive Models (VAR), Structural VAR, Causality, Eviews Uygulamaları. |
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| Course Syllabus | | Week | Subject | Related Notes / Files | | Week 1 | Testing for Cointegration: The Engle-Granger Methodology | | | Week 2 | Testing for Cointegration: Johansen Methodology | | | Week 3 | Testing for Cointegration: ARDL Methodology | | | Week 4 | Testing for Cointegration: NARDL Methodology | | | Week 5 | Threshold Autoregressive Models (TAR) | | | Week 6 | Momentum Threshold Autoregressive Model (MTAR) | | | Week 7 | Error Correction Model | | | Week 8 | Cointegration and Error Correction: Eviews Applications | | | Week 9 | Mid-term exam | | | Week 10 | Vector Autoregressive Models (VAR) | | | Week 11 | The Impulse Response Function and Variance Decomposition | | | Week 12 | Quiz | | | Week 13 | Granger Causality Test and Sims Causality Test | | | Week 14 | VAR Analysis: Eviews Applications | | | Week 15 | Structural VAR | | | Week 16 | End-of-term exam | | | |
| 1 | Hamilton, James.D. (1994) Time Series Analysis, Princeton University Press, Second Edition, USA | | | |
| Method of Assessment | | Type of assessment | Week No | Date | Duration (hours) | Weight (%) | | Mid-term exam | 9 | 04/2025 | 1 | 30 | | Homework/Assignment/Term-paper | 12 | 05/2025 | 1 | 20 | | End-of-term exam | 16 | 06/2025 | 1 | 50 | | |
| Student Work Load and its Distribution | | Type of work | Duration (hours pw) | No of weeks / Number of activity | Hours in total per term | | Yüz yüze eğitim | 3 | 14 | 42 | | Sınıf dışı çalışma | 8 | 14 | 112 | | Arasınav için hazırlık | 12 | 2 | 24 | | Arasınav | 2 | 1 | 2 | | Ödev | 3 | 2 | 6 | | Kısa sınav | 1 | 1 | 1 | | Dönem sonu sınavı için hazırlık | 12 | 3 | 36 | | Dönem sonu sınavı | 2 | 1 | 2 | | Total work load | | | 225 |
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