ECMZ406 Time Series Models II

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

Information

Code ECMZ406
Name Time Series Models II
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
Mode of study Yüz Yüze Öğretim
Catalog Information Coordinator Dr. Öğr. Üyesi FELA ÖZBEY


Course Goal

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 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 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 follows the current developments in the field / constantly renews itself 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 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 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 Ölçme Yöntemleri:
Yazılı Sınav
17 Term Exams 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