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| EKO5580 | Time Series Analyses - II | 3+0+0 | ECTS:7.5 | | Year / Semester | Spring Semester | | Level of Course | Second Cycle | | Status | Elective | | 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. Rahmi YAMAK | | Co-Lecturer | | | Language of instruction | Turkish | | Professional practise ( internship ) | None | | | | The aim of the course: | | This course is a continuation of Time Series Analyses-I course and has the same objectives. |
| Programme Outcomes | CTPO | TOA | | Upon successful completion of the course, the students will be able to : | | | | PO - 1 : | understand those time series techniques that have been recently developed. | 1,2 | 1,3, | | PO - 2 : | recognize that when and how to use these new techniques. | 1,2 | 1,3, | | PO - 3 : | produce forecasts and test economic, financial or fiscal hypothesis by using time series. | 1,2 | 1,3, | | PO - 4 : | determine the best forecast by evaluating various forecasts and choose acceptable hypotheses that are suitable for Turkish case. | 1,2 | 1,3, | | PO - 5 : | produce micro or macro policies based on hypothesis investigated and forecast chosen. | 1,2 | 1,3, | | 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 | | |
| Models With Trends: Deterministic and Stochastic Trends, Random Walk Models and Their Statistical Properties, Removing the Trend, Unit Roots and Stationary, Unit Roots and Regression Residuals, Monte Carlo Method, Power of Dickey Fuller Tests, Determination of Deterministic Regressors in Dickey Fuller Tests, Structural Change and Dickey Fuller Tests: Perron (1989) Test, Zivot and Andrews (1992) Test, Some Other Unit Root Tests: Phillips-Perron (1988) Test, DF-GLS (1996) Test, KPSS (1992) Test, Seasonal Unit Roots: HEGY (1990) Test, Seasonal Unit Roots: Franses (1991) Test, Trends and Decomposition Methods: Beveridge and Nelson (1981) Decomposition, Hodrick-Prescott (1997) Decomposition. Multiequation Time Series Models: Intervention Analysis, Transfer Function Models, VAR Analysis, Structural VAR. |
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| Course Syllabus | | Week | Subject | Related Notes / Files | | Week 1 | Deterministic and stochastic trends, the random walk model, the random walk plus drift model. | | | Week 2 | Removing the trend: differencing and detrending. Difference stationary and trend stationary series. | | | Week 3 | Unit roots and regression residuals. Introduction to Monte Carlo Methods, an exammple of experiment: generating the Dickey-Fuller distribution. | | | Week 4 | Some remarks about Dickey-Fuller tests: (low) power of tests, determination of deterministic regressors and lag length selection. | | | Week 5 | A unit root test that allows a (exogenous) structural change: Perron (1989) test. Alternative forms of test equation. | | | Week 6 | A unit root test that allows a (endogenous) structural change: Zivot and Andrews (1992) test. Alternative forms of test equation. | | | Week 7 | Some Other Unit Root Tests: Phillips-Perron (1988) Test, DF-GLS (1996) Test, KPSS (1992) Test. | | | Week 8 | A seasonal unit root test for quarterly time series: HEGY (1990) Test. Alternative forms of test equation. | | | Week 9 | Mid-term exam | | | Week 10 | A seasonal unit root test for monthly time series: Franses (1991) Test. Alternative forms of test equation. | | | Week 11 | Some univariate decomposition methods: Beveridge and Nelson (1981) decomposition, Hodrick-Prescott (1997) decomposition. Introduction to intervention analysis, alternative forms of intervention, estimation of intervention function. | | | Week 12 | Quiz | | | Week 13 | Introduction to transfer function analysis, Cross-correlogram, identification and estimation of transfer function. | | | Week 14 | Introduction to VAR Analysis, difference between VAR in standard form and structural VAR, different approaches to selecting lag length: information based criteria and LR Test. | | | Week 15 | Estimation and identification of VAR, interpreting the VAR results: Granger causality, impulse-response function and variance decomposition, Structural VAR. | | | Week 16 | End-of-term exam | | | |
| 1 | Enders, W. 2004; Applied Econometric Time Series, John Wiley & Sons, USA. | | | |
| 1 | Harris, R. ve Sollis, R. 2003; Applied Time Series Modelling and Forecasting, John Wiley & Sons, USA. | | | |
| Method of Assessment | | Type of assessment | Week No | Date | Duration (hours) | Weight (%) | | Mid-term exam | 9 | 04/2024 | 1 | 30 | | Homework/Assignment/Term-paper | 12 | 05/2024 | 2 | 20 | | End-of-term exam | 16 | 06/2024 | 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 | 11 | 2 | 22 | | Arasınav | 2 | 1 | 2 | | Uygulama | 1 | 14 | 14 | | Ödev | 3 | 2 | 6 | | Kısa sınav | 1 | 1 | 1 | | Dönem sonu sınavı için hazırlık | 12 | 2 | 24 | | Dönem sonu sınavı | 2 | 1 | 2 | | Total work load | | | 225 |
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