EKO638 - APPLIED TIME SERIES ANALYSIS
| Course Name | Code | Semester | Theory (hours/week) |
Application (hours/week) |
Credit | ECTS |
|---|---|---|---|---|---|---|
| APPLIED TIME SERIES ANALYSIS | EKO638 | Any Semester/Year | 3 | 0 | 3 | 7.5 |
| Prequisites | None | |||||
| Course language | Turkish | |||||
| Course type | Elective | |||||
| Mode of Delivery | Face-to-Face | |||||
| Learning and teaching strategies | Lecture Team/Group Work Drill and Practice | |||||
| Instructor (s) | Academic Staff | |||||
| Course objective | This course aims to introduce time series modelling for both stationary and nonstationary processes. | |||||
| Learning outcomes |
| |||||
| Course Content | ? ARMA models ? ARCH models ? VAR models ? VECM models ? ARDL models ? Nonlinear ARDL models ? TAR Models ? Introduction to STAR Models | |||||
| References | 1. Enders, W., Applied Econometric Time Series, John Wiley & Sons. 2. Harvey, A.C., The Econometric Analysis of Time Series, Philip Allan. 3. Mills, T., Time Series Analysis for Economists, Cambridge University Press. | |||||
Course outline weekly
| Weeks | Topics |
|---|---|
| Week 1 | Basic Probability and Statistics Concepts |
| Week 2 | Difference Equations |
| Week 3 | Stationary Time Series Models: ARMA Models |
| Week 4 | Modelling Nonstationary Process |
| Week 5 | Modelling Volatility: ARCH Processes |
| Week 6 | ARCH Modelling Applications |
| Week 7 | Midterm exam |
| Week 8 | Multivariate Time Series Analyses: VAR |
| Week 9 | Cointegration and Vector Error Correction Models |
| Week 10 | ARDL Models |
| Week 11 | Granger Causality |
| Week 12 | Midterm exam |
| Week 13 | Nonlinear ARDL Model |
| Week 14 | TAR Models |
| Week 15 | Introduction to STAR Models |
| Week 16 | Final Exam |
Assesment methods
| Course activities | Number | Percentage |
|---|---|---|
| Attendance | 0 | 0 |
| Laboratory | 0 | 0 |
| Application | 0 | 0 |
| Field activities | 0 | 0 |
| Specific practical training | 0 | 0 |
| Assignments | 0 | 0 |
| Presentation | 0 | 0 |
| Project | 0 | 0 |
| Seminar | 0 | 0 |
| Midterms | 2 | 40 |
| Final exam | 1 | 60 |
| Total | 100 | |
| Percentage of semester activities contributing grade succes | 2 | 40 |
| Percentage of final exam contributing grade succes | 1 | 60 |
| Total | 100 | |
WORKLOAD AND ECTS CALCULATION
| Activities | Number | Duration (hour) | Total Work Load |
|---|---|---|---|
| Course Duration (x14) | 14 | 3 | 42 |
| Laboratory | 0 | 0 | 0 |
| Application | 0 | 0 | 0 |
| Specific practical training | 0 | 0 | 0 |
| Field activities | 0 | 0 | 0 |
| Study Hours Out of Class (Preliminary work, reinforcement, ect) | 14 | 6 | 84 |
| Presentation / Seminar Preparation | 0 | 0 | 0 |
| Project | 0 | 0 | 0 |
| Homework assignment | 0 | 0 | 0 |
| Midterms (Study duration) | 2 | 24 | 48 |
| Final Exam (Study duration) | 1 | 51 | 51 |
| Total Workload | 31 | 84 | 225 |
Matrix Of The Course Learning Outcomes Versus Program Outcomes
| D.9. Key Learning Outcomes | Contrubition level* | ||||
|---|---|---|---|---|---|
| 1 | 2 | 3 | 4 | 5 | |
| 1. To develop and deepen the knowledge of economics to an expert level, building on the competencies of the undergraduate education. | X | ||||
| 2. To comprehend the interaction between related disciplines and economics. | X | ||||
| 3. To be able to apply the advanced level knowledge acquired in economics. | X | ||||
| 4. To create new knowledge by combining the knowledge of economics with the knowledge coming from other disciplines. | X | ||||
| 5. To be able to critically evaluate the knowledge in economics, to lead learning and carry out advanced level research independently. | X | ||||
| 6. To be able to develop new strategic approaches for unexpected, complicated situations in economics and take responsibility in solving them. | X | ||||
| 7. To possess the communication network to bring up the economic and social needs of the region of residence on the agenda. | X | ||||
| 8. To have sufficient social responsibility and awareness about the needs of society | X | ||||
| 9. To be able to think analytically to identify problems in economics and to be able to make policy recommendations in economics based on scientific analysis of issues and problems. | X | ||||
| 10. To protect the social, scientific and ethical values at the data collection, interpretation and dissemination stages. | X | ||||
| 11. To be able to use the skills of modeling, empirical analysis and formulating policy options that are developed for economics in interdisciplinary contexts. | X | ||||
*1 Lowest, 2 Low, 3 Average, 4 High, 5 Highest