ECMZ406 Time Series Models II

4 ECTS - 3-0 Duration (T+A)- 8. Semester- 3 National Credit

Information

Unit FACULTY OF ECONOMICS AND ADMINISTRATIVE SCIENCES
ECONOMETRICS PR. (ENGLISH)
Code ECMZ406
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 İngilizce
Level Lisans Dersi
Type Normal
Label C Compulsory
Mode of study Yüz Yüze Öğretim
Catalog Information Coordinator Dr. Öğr. Üyesi FELA ÖZBEY
Course Instructor Dr. Öğr. Üyesi FELA ÖZBEY (Bahar) (A Group) (Ins. in Charge)


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

The course content covers VAR models, roots, stability, VMA representation, orthogonalization of errors, impulse-response function, cumulative impulse-response function, long-term response, variance decomposition, mean, variance, autocovariance and autocorrelations, lag selection criteria, Granger causality, error correction representation, cointegration, Engle-Granger and Johansen cointegration tests, ARDL models and bounds testing.

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 Determines the roots of VAR(p) models and whether they are stable.
LO02 Obtains the VMA representation of VAR(p) models and decomposes the prediction variance.
LO03 It orthogonalizes the errors of VAR models and obtains the error correction representation.
LO04 Calculates impulse-response functions and cumulative impulse-response functions of VAR(p) models.
LO05 Calculates the long-run response of a VAR(p) model.
LO06 Calculates the mean, autocovariance and autocorrelation of VAR(p) processes.
LO07 Selects the optimal lag for a VAR model.
LO08 Performs the Granger causality test.
LO09 Defines cointegration and performs the Engle-Granger cointegration test.
LO10 Performs the Johansen cointegration tests.
LO11 Recognizes the ARDL models
LO12 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 Analyzes/interprets at the conceptual level to develop solutions to problems 5
PLO07 Beceriler - Bilişsel, Uygulamalı Collects/analyses data from reliable data sources for the purpose of study 5
PLO08 Bilgi - Kuramsal, Olgusal 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 of research
PLO10 Beceriler - Bilişsel, Uygulamalı Adapts traditional approaches, practices and methods to a new study when necessary 2
PLO11 Beceriler - Bilişsel, Uygulamalı Uses a package program of Econometrics, Statistics, and Operation Research
PLO12 Yetkinlikler - Bağımsız Çalışabilme ve Sorumluluk Alabilme Yetkinliği Leads by taking responsibility individually and/or within the team
PLO13 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
PLO14 Yetkinlikler - Öğrenme Yetkinliği Being aware of the necessity of lifelong learning, it follows the current developments in the field / constantly renews itself 2
PLO15 Yetkinlikler - İletişim ve Sosyal Yetkinlik Uses Turkish and at least one other foreign language, academically and in the business context 3
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 Vector Autoregressive Processes - Error Correction Represantation, , FPE, AIC, BIC, HQ criteria 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 Students will be prepared by studying relevant subjects from source books according to the weekly program Öğretim Yöntemleri:
Anlatım, Soru-Cevap, Problem Çözme
8 Mid-Term Exam Preparing for the 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 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 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 Term Exams Final exam preparation Ölçme Yöntemleri:
Yazılı Sınav
17 Term Exams Final exam preparation Ölçme Yöntemleri:
Yazılı Sınav


Assessment (Exam) Methods and Criteria

Current term shares have not yet been determined. Shares of the previous term are shown.
Assessment Type Midterm / Year Impact End of Term / End of Year Impact
1. Midterm Exam 100 40
General Assessment
Midterm / Year Total 100 40
1. Final Exam - 60
Grand Total - 100


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

Update Time: 03.03.2025 01:50