IEM710 Time Series Analysis II

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

Information

Code IEM710
Name Time Series Analysis II
Term 2024-2025 Academic Year
Semester . Semester
Duration (T+A) 3-0 (T-A) (17 Week)
ECTS 6 ECTS
National Credit 3 National Credit
Teaching Language Türkçe
Level Yüksek Lisans Dersi
Type Normal
Mode of study Yüz Yüze Öğretim
Catalog Information Coordinator Dr. Öğr. Üyesi FELA ÖZBEY


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 of stochastic and deterministic trends,Unit root tests, VAR models, determination of the maximal lag of the system, Granger Causality, error correction represantation, cointegration, Engle-Granger cointegration test, Johansen cointegration test, ARDL models, bounds test.

Course Precondition

None

Resources

James Douglas Hamilton, (1994) Time Series Analysis, Princeton University Press, ISBN: 9780691042893 Gebhard Kirchgässner, Jürgen Wolters (2007), Introduction to Modern Time Series Analysis, Springer, ISBN: 978-3-540-73291-4 Burak Güriş (2020) R Uygulamalı Doğrusal Olmayan Zaman Serileri Analizi, Der Yayınları ISBN: 978-975-353-628-8

Notes

Gebhard Kirchgässner, Jürgen Wolters (2007), Introduction to Modern Time Series Analysis, Springer, ISBN: 978-3-540-73291-4


Course Learning Outcomes

Order Course Learning Outcomes
LO01 Distinguishes betweendeterministic trend and stochastic trend.
LO02 Determines whether VAR models are stable or not.
LO03 Calculates impulse-response functions of VAR models.
LO04 Decomposes the variance of a VAR model forecast.
LO05 Performs the Granger causality test.
LO06 Performs the cointegration tests.
LO07 Performs the bounds test.
LO08 Performs stationarity tests.


Relation with Program Learning Outcome

Order Type Program Learning Outcomes Level
PLO01 Bilgi - Kuramsal, Olgusal Explains contemporary concepts about Econometrics, Statistics, and Operation Research 5
PLO02 Bilgi - Kuramsal, Olgusal Explains relationships between acquired knowledge about Econometrics, Statistics, and Operation Research 5
PLO03 Bilgi - Kuramsal, Olgusal Explains how to apply acquired knowledge in the field to Economics, Business, and other social sciences 5
PLO04 Beceriler - Bilişsel, Uygulamalı Performs conceptual analysis to develop solutions to problems 5
PLO05 Beceriler - Bilişsel, Uygulamalı Models problems with Mathematics, Statistics, and Econometrics 5
PLO06 Beceriler - Bilişsel, Uygulamalı Interprets the results obtained from the most appropriate method to predict the model 5
PLO07 Beceriler - Bilişsel, Uygulamalı Synthesizes the information obtained by using different sources within the framework of academic rules in a field that does not research 3
PLO08 Beceriler - Bilişsel, Uygulamalı Uses acquired knowledge in the field to determine the vision, aim, and goals for an organization/institution 3
PLO09 Beceriler - Bilişsel, Uygulamalı Searches for new approaches and methods to solve problems being faced 3
PLO10 Beceriler - Bilişsel, Uygulamalı Presents analysis results conveniently 3
PLO11 Beceriler - Bilişsel, Uygulamalı Collects/analyzes data in a purposeful way 5
PLO12 Yetkinlikler - İletişim ve Sosyal Yetkinlik Converts its findings into a master's thesis or a professional report in Turkish or a foreign language 3
PLO13 Beceriler - Bilişsel, Uygulamalı Develops solutions for organizations using Econometrics, Statistics, and Operation Research 3
PLO14 Yetkinlikler - Bağımsız Çalışabilme ve Sorumluluk Alabilme Yetkinliği Performs an individual work to solve a problem with Econometrics, Statistics, and Operation Research 5
PLO15 Yetkinlikler - Bağımsız Çalışabilme ve Sorumluluk Alabilme Yetkinliği Leads by taking responsibility individually and/or within the team
PLO16 Yetkinlikler - Öğrenme Yetkinliği Being aware of the necessity of lifelong learning, it constantly renews itself by following the current developments in the field of study 3
PLO17 Yetkinlikler - İletişim ve Sosyal Yetkinlik Uses a package program of Econometrics, Statistics, and Operation Research or writes a new code
PLO18 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
PLO19 Yetkinlikler - Alana Özgü Yetkinlik Interprets data on economic and social events by following current issues 3
PLO20 Yetkinlikler - Alana Özgü Yetkinlik Applies social, scientific and professional ethical values


Week Plan

Week Topic Preparation Methods
1 Nonstationary Processes - Forms of Nonstationarity, Trend Elimination Students will be prepared by studying relevant subjects from source books according to the weekly program Öğretim Yöntemleri:
Anlatım, Soru-Cevap, Alıştırma ve Uygulama
2 Nonstationary Processes - Dickey-Fuller Tests Students will be prepared by studying relevant subjects from source books according to the weekly program Öğretim Yöntemleri:
Anlatım, Soru-Cevap, Alıştırma ve Uygulama
3 Nonstationary Processes - The Phillips-Perron Test, Unit Root Tests and Structural Breaks, KPSS test Students will be prepared by studying relevant subjects from source books according to the weekly program Öğretim Yöntemleri:
Anlatım, Soru-Cevap, Alıştırma ve Uygulama
4 Nonstationary Processes - HEGY Tests Students will be prepared by studying relevant subjects from source books according to the weekly program Öğretim Yöntemleri:
Anlatım, Soru-Cevap, Alıştırma ve Uygulama
5 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, Alıştırma ve Uygulama
6 Vector Autoregressive Processes - 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, Alıştırma ve Uygulama
7 Vector Autoregressive Processes - Variance Decomposition Students will be prepared by studying relevant subjects from source books according to the weekly program Öğretim Yöntemleri:
Anlatım, Soru-Cevap, Alıştırma ve Uygulama
8 Mid-Term Exam Ölçme Yöntemleri:
Yazılı Sınav
9 Cointegration - 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, Alıştırma ve Uygulama
10 Cointegration - 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, Gösterip Yaptırma
11 Cointegration - 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, Alıştırma ve Uygulama
12 Cointegration - 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, Alıştırma ve Uygulama
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, Alıştırma ve Uygulama
14 Bounds test Students will be prepared by studying relevant subjects from source books according to the weekly program Öğretim Yöntemleri:
Anlatım, Soru-Cevap, Alıştırma ve Uygulama
15 An overview Students will be prepared by studying relevant subjects from source books according to the weekly program Öğretim Yöntemleri:
Anlatım, Soru-Cevap, Alıştırma ve Uygulama
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 5 70
Assesment Related Works
Homeworks, Projects, Others 0 0 0
Mid-term Exams (Written, Oral, etc.) 1 15 15
Final Exam 1 30 30
Total Workload (Hour) 157
Total Workload / 25 (h) 6,28
ECTS 6 ECTS

Update Time: 09.05.2024 04:21