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Information
| Code | EKMZ406 |
| Name | Time Series Models II |
| Term | 2024-2025 Academic Year |
| Semester | 8. Semester |
| Duration (T+A) | 3-0 (T-A) (17 Week) |
| ECTS | 4 ECTS |
| National Credit | 3 National Credit |
| Teaching Language | Türkçe |
| Level | Lisans Dersi |
| Type | Normal |
| Mode of study | Yüz Yüze Öğretim |
| Catalog Information Coordinator | Dr. Öğr. Üyesi FELA ÖZBEY |
| Course Instructor |
1 2 |
Course Goal / Objective
The aim of this course is to give the students a good theoretical and empirical understanding of statistical methods used in multivariate time series analysis.
Course Content
This course involves the study ofVAR models, Roots of VAR models, Stability of VAR models, VMA representation of a VAR model, Orthogonalization of the error vectors in VAR models, Impulse-response functions of VAR models, Cumulative impulse-response functions of VAR models, Long-run response of a VAR model. Variance decomposition in VAR models. Mean of VAR(p) processes, Variance of VAR(p) processes, Autocovariances of VAR(p) processes, Autocorrelations of VAR(p) processes, determination of the maximal lag of the system, Granger Causality, error correction represantation of VAR models, cointegration, Engle-Granger cointegration test, Johansen cointegration test, ARDL models, bounds test.
Course Precondition
None
Resources
Gebhard Kirchgässner, Jürgen Wolters (2007), Introduction to Modern Time Series Analysis, Springer, ISBN: 978-3-540-73291-4
Notes
James Douglas Hamilton, (1994) Time Series Analysis, Princeton University Press, ISBN: 9780691042893
Course Learning Outcomes
| Order | Course Learning Outcomes |
|---|---|
| LO01 | Calculates the roots of VAR(p) models. |
| LO02 | Determines whether VAR(p) models are stable or not. |
| LO03 | Evaluates VMA representation of a VAR model. |
| LO04 | Orthogonalizes error terms of a VAR model. |
| LO05 | Calculates impulse-response functions of VAR(p) models. |
| LO06 | Calculates cumulative impulse-response functions of VAR(p) models. |
| LO07 | Calculates the long-run response of a VAR(p) model. |
| LO08 | Decomposes the variance of a VAR(p) model forecast. |
| LO09 | Calculates the mean of a VAR(p) model. |
| LO10 | Calculates the autocovariances of a VAR(p) model. |
| LO11 | Calculates the autocorrelations of a VAR(p) model. |
| LO12 | Selects the optimal lag for a VAR model. |
| LO13 | Performs the Granger causality test. |
| LO14 | Evaluates the error correction represantation of VAR models. |
| LO15 | Defines the cointegration. |
| LO16 | Performs the Engle-Granger cointegration test. |
| LO17 | Performs the Johansen cointegration tests. |
| LO18 | Recognizes the ARDL models. |
| LO19 | Performs the bounds test. |
Relation with Program Learning Outcome
| Order | Type | Program Learning Outcomes | Level |
|---|---|---|---|
| PLO01 | Bilgi - Kuramsal, Olgusal | Explain the basic concepts and theorems in the fields of Econometrics, Statistics and Operations research | 5 |
| PLO02 | Bilgi - Kuramsal, Olgusal | Acquires basic Mathematics, Statistics and Operation Research concepts | 5 |
| PLO03 | Bilgi - Kuramsal, Olgusal | Describes the necessary concepts of Business | |
| PLO04 | Beceriler - Bilişsel, Uygulamalı | Equipped with the foundations of Economics, and develops Economic models | 3 |
| PLO05 | Beceriler - Bilişsel, Uygulamalı | Models problems with Mathematics, Statistics, and Econometrics | 5 |
| PLO06 | Beceriler - Bilişsel, Uygulamalı | Has the ability to analyze/interpret at the conceptual level to develop solutions to problems | 5 |
| PLO07 | Beceriler - Bilişsel, Uygulamalı | Collects/analyses data | 5 |
| PLO08 | Beceriler - Bilişsel, Uygulamalı | Interprets the results analyzed with the model | 5 |
| PLO09 | Beceriler - Bilişsel, Uygulamalı | Combines the information obtained from different sources within the framework of academic rules in a field which does not research | |
| PLO10 | Beceriler - Bilişsel, Uygulamalı | It develops traditional approaches, practices and methods into new working methods when it deems necessary | 2 |
| PLO11 | Yetkinlikler - Bağımsız Çalışabilme ve Sorumluluk Alabilme Yetkinliği | Leads by taking responsibility individually and/or within the team | |
| PLO12 | Yetkinlikler - Öğrenme Yetkinliği | In addition to herself/himself professional development, constantly improves in scientific, cultural, artistic and social fields in line with interests and abilities | |
| PLO13 | Yetkinlikler - Öğrenme Yetkinliği | Being aware of the necessity of lifelong learning, it constantly renews itself by following the current developments in its field. | 2 |
| PLO14 | Yetkinlikler - İletişim ve Sosyal Yetkinlik | Uses a package program of Econometrics, Statistics, and Operation Research | |
| PLO15 | Yetkinlikler - İletişim ve Sosyal Yetkinlik | Uses Turkish and at least one other foreign language, academically and in the business context | 2 |
| PLO16 | Yetkinlikler - İletişim ve Sosyal Yetkinlik | Interprets the feelings, thoughts and behaviors of the related persons correctly/expresses himself/herself correctly in written and verbal form | |
| PLO17 | Yetkinlikler - Alana Özgü Yetkinlik | Interprets data on current economic and social issues | 2 |
| PLO18 | Yetkinlikler - Alana Özgü Yetkinlik | Applies social, scientific and professional ethical values |
Week Plan
| Week | Topic | Preparation | Methods |
|---|---|---|---|
| 1 | Vector Autoregressive Processes: Stability conditions and MA Represantation of the System | Students will be prepared by studying relevant subjects from source books according to the weekly program | Öğretim Yöntemleri: Anlatım, Soru-Cevap, Problem Çözme |
| 2 | The mean vector and the autocovariance matrices of VAR models | Students will be prepared by studying relevant subjects from source books according to the weekly program | Öğretim Yöntemleri: Anlatım, Soru-Cevap, Problem Çözme |
| 3 | Autocorrelations matrices of VAR models | Students will be prepared by studying relevant subjects from source books according to the weekly program | Öğretim Yöntemleri: Anlatım, Soru-Cevap, Problem Çözme |
| 4 | Hata Düzeltme Modeli, VAR modellerinde gecikme belirleme kriterleri-FPE, AIC, BIC, HQ kriterleri | Students will be prepared by studying relevant subjects from source books according to the weekly program | Öğretim Yöntemleri: Anlatım, Soru-Cevap, Problem Çözme |
| 5 | Orthogonalizing the errors of VAR models | Students will be prepared by studying relevant subjects from source books according to the weekly program | Öğretim Yöntemleri: Anlatım, Soru-Cevap, Problem Çözme |
| 6 | Granger Causality, Impulse Response Analysis | Students will be prepared by studying relevant subjects from source books according to the weekly program | Öğretim Yöntemleri: Anlatım, Soru-Cevap, Problem Çözme |
| 7 | Variance Decomposition, Eviews applications for VAR analysis. | Students will be prepared by studying relevant subjects from source books according to the weekly program | Öğretim Yöntemleri: Anlatım, Soru-Cevap, Problem Çözme |
| 8 | Midterm Exam | Ölçme Yöntemleri: Yazılı Sınav |
|
| 9 | Definition and Properties of Cointegrated Processes | Students will be prepared by studying relevant subjects from source books according to the weekly program | Öğretim Yöntemleri: Anlatım, Soru-Cevap, Problem Çözme |
| 10 | Cointegration in Single Equation Models: Represantation, Estimation and Testing | Students will be prepared by studying relevant subjects from source books according to the weekly program | Öğretim Yöntemleri: Anlatım, Soru-Cevap, Problem Çözme |
| 11 | Cointegration in Vector Autoregressive Models: The Vector Error Correction Representation, The Johansen Approach | Students will be prepared by studying relevant subjects from source books according to the weekly program | Öğretim Yöntemleri: Anlatım, Soru-Cevap, Problem Çözme |
| 12 | Cointegration in Vector Autoregressive Models: Analysis of Vector Error Correction Models, Cointegration and Economic Theory, Eviews applications for cointegration analysis. | Students will be prepared by studying relevant subjects from source books according to the weekly program | Öğretim Yöntemleri: Anlatım, Soru-Cevap, Problem Çözme |
| 13 | ARDL models, static and dynamic equilibrium | Students will be prepared by studying relevant subjects from source books according to the weekly program | Öğretim Yöntemleri: Anlatım, Soru-Cevap, Problem Çözme |
| 14 | Bounds test, Eviews applications. | Students will be prepared by studying relevant subjects from source books according to the weekly program | Öğretim Yöntemleri: Anlatım, Soru-Cevap, Problem Çözme |
| 15 | An overview | Students will be prepared by studying relevant subjects from source books according to the weekly program | Öğretim Yöntemleri: Anlatım, Soru-Cevap, Problem Çözme |
| 16 | Final exam | Ölçme Yöntemleri: Yazılı Sınav |
|
| 17 | Final exam | Ölçme Yöntemleri: Yazılı Sınav |
Student Workload - ECTS
| Works | Number | Time (Hour) | Workload (Hour) |
|---|---|---|---|
| Course Related Works | |||
| Class Time (Exam weeks are excluded) | 14 | 3 | 42 |
| Out of Class Study (Preliminary Work, Practice) | 14 | 3 | 42 |
| Assesment Related Works | |||
| Homeworks, Projects, Others | 0 | 0 | 0 |
| Mid-term Exams (Written, Oral, etc.) | 1 | 7 | 7 |
| Final Exam | 1 | 18 | 18 |
| Total Workload (Hour) | 109 | ||
| Total Workload / 25 (h) | 4,36 | ||
| ECTS | 4 ECTS | ||