GAZI UNIVERSITY INFORMATION PACKAGE - 2019 ACADEMIC YEAR

COURSE DESCRIPTION
MULTIVARIATE STATISTICAL ANALYSIS/5080050
Course Title: MULTIVARIATE STATISTICAL ANALYSIS
Credits 3 ECTS 7.5
Semester 2 Compulsory/Elective Elective
COURSE INFO
 -- LANGUAGE OF INSTRUCTION
  Turkish
 -- NAME OF LECTURER(S)
  Assoc.Prof. Yeliz Yalçın
 -- WEB SITE(S) OF LECTURER(S)
  www.gazi.edu.tr/websitem/yyeliz
 -- EMAIL(S) OF LECTURER(S)
  yyeliz@gazi.edu.tr
 -- LEARNING OUTCOMES OF THE COURSE UNIT
Learn the structural analysis in multpile time series models
Learn the structural VAR models
Use multivariate time-series models to analyse time series data and apply techniques such as impulse response analysis, Granger Causality, and varianc






 -- MODE OF DELIVERY
  The mode of delivery of this course is Face to face
 -- PREREQUISITES AND CO-REQUISITES
  There is no prerequisite or co-requisite for this course.
 -- RECOMMENDED OPTIONAL PROGRAMME COMPONENTS
  Time series Analysis
 --COURSE CONTENT
1. Week  Review of matris algebra
2. Week  Stable VAR process
3. Week  Strustural Analysis: 1. Granger Causality 2. Impulse responses 3. Variance decomposition
4. Week  Estimation of VAR process
5. Week  VAR order lag selction and model cheking
6. Week  Cointegrated process and VECM
7. Week  Cointegrated process and VECM and Structural Analysis
8. Week  Midterm
9. Week  Strustural VAR model: A Model B model AB model
10. Week  VAR with Sign restriction
11. Week  Blanchard Quah framework
12. Week  Block restriction and asymmetric VAR models
13. Week  Multivariate ARCH GARCH model
14. Week  Multivariate ARCH GARCH model
15. Week  state-space models
16. Week  Final exam
 -- RECOMMENDED OR REQUIRED READING
  Lütkephol, Helmut (2005), New Introduction to Multiple Time Series Analysis, Springer-Verlag, Berlin Harvey, Andrew (1989), Forecasting, structıral time series models and kalman filter, Cambridge universitry press, cabridge, England Akdi, yılma (2003), Zaman Serielri analizi, Bıçaklar kitapevi
 -- PLANNED LEARNING ACTIVITIES AND TEACHING METHODS
  Lecture
 -- WORK PLACEMENT(S)
  Not Applicable
 -- ASSESSMENT METHODS AND CRITERIA
 
Quantity
Percentage
 Mid-terms
1
50
 Assignment
0
0
 Exercises
0
0
 Projects
0
0
 Practice
0
0
 Quiz
0
0
 Contribution of In-term Studies to Overall Grade  
50
 Contribution of Final Examination to Overall Grade  
50
 -- WORKLOAD
 Efficiency  Total Week Count  Weekly Duration (in hour)  Total Workload in Semester
 Theoretical Study Hours of Course Per Week
14
4
56
 Practising Hours of Course Per Week
13
3
39
 Reading
13
2
26
 Searching in Internet and Library
13
2
26
 Designing and Applying Materials
14
2
28
 Preparing Reports
0
 Preparing Presentation
0
 Presentation
0
 Mid-Term and Studying for Mid-Term
2
3
6
 Final and Studying for Final
2
4
8
 Other
0
 TOTAL WORKLOAD: 
189
 TOTAL WORKLOAD / 25: 
7.56
 ECTS: 
7.5
 -- COURSE'S CONTRIBUTION TO PROGRAM
NO
PROGRAM LEARNING OUTCOMES
1
2
3
4
5
1X
2X
3
4X
5X
6X
7X
8X
9X
10X