COURSE SYLLABUS

TIME SERIES ANALYSIS

1	Course Title:	TIME SERIES ANALYSIS
2	Course Code:	EKO4111
3	Type of Course:	Optional
4	Level of Course:	First Cycle
5	Year of Study:	4
6	Semester:	7
7	ECTS Credits Allocated:	5
8	Theoretical (hour/week):	3
9	Practice (hour/week) :	0
10	Laboratory (hour/week) :	0
11	Prerequisites:	No
12	Recommended optional programme components:	None
13	Language:	Turkish
14	Mode of Delivery:	Face to face
15	Course Coordinator:	Prof. Dr. Mehmet Çınar
16	Course Lecturers:
17	Contactinformation of the Course Coordinator:	mcinar@uludag.edu.tr Uludağ Üniversitesi İktisadi ve İdari Bilimler Fakültesi Görükle Kampüsü 16059 Nilüfer / Bursa
18	Website:
19	Objective of the Course:	The main aim of this course is to teach basic econometrics, econometric models, statistical theory and basic economic literatüre and how to use them in real.
20	Contribution of the Course to Professional Development	To be able to study in applied area using these techniques with economic series.

Learning Outcomes:

1	To be able to compass economic theory, statistical and econometric analyzes. ;
2	To be able to analyze economic event with qualitative and quantitative methods.;
3	To be able to compare econometric and statistical analyzes with economic hppening;
4	To be able to plan an programme economic events using econometric and statistical methods. ;
5	To be able to follow economic events happens in our country and around the world easily.;
6	To be able to analyzes short-term relations by considering real world relations. ;
7	To be able to search long term economic relations and make inferences. ;
8	To be able to study in applied area using these techniques with economic series. ;

22	Course Content:

Week	Theoretical	Practical
1	Introuction to Time Series Models
2	Graphical Analyses of Time Series
3	Time Series Analyzes, Models and Some Basic Concept
4	Autocorrelation Analyzes for Time Series, Partial Autocorrelation Analyzes
5	Portmanteau Tests in Time Series, Correlogram of Time Series and Stationary Tests
6	Time Series Models and Lag Equations, Distribution Processor and Applied to Time Series Models
7	Make Stationary the Series That are Non-Stationary
8	Repeating courses and midterm exam
9	Stationary Tests with Correlogram
10	Statistical Models of Autoregressive (AR) Models, Moving Average Models (MA) and Autoregressive Moving Average Models (ARMA)
11	Non-Stationary and Integrated Process, Autoregressive Integrated Moving Average Models (ARIMA), Statistical Models for Them, Seasonal Box-Jenkins ARIMA Models.
12	Unit Root Tests for Univariate Process
13	Cointegration and Conintegration Tests
14	Error Correction Models, Seasonal Integration and Cointegration

23	Textbooks, References and/or Other Materials:	1. Sevüktekin, M.ve M. Çınar, Ekonometrik Zaman Serileri Analizi: EViews Uygulamalı, Geliştirilmiş Dördüncü Baskı Bursa: Dora Yayın, 2014. 2. Enders, W., Applied Econometric Time Series, New York: John Wiley &Sons,Inc., 1995. 3. Hamilton, J. D., Time Series Analysis, Princeton, New Jersey: Princeton University Pres, 1994. 4. Patterson, K., An Introduction to Applied Econometrics: A Time Series Approach, New york: Macmillan Pres., 2000.
24	Assesment

TERM LEARNING ACTIVITIES	NUMBER	PERCENT
Midterm Exam	1	40
Quiz	0	0
Homeworks, Performances	0	0
Final Exam	1	60
Total	2	100
Contribution of Term (Year) Learning Activities to Success Grade		40
Contribution of Final Exam to Success Grade		60
Total		100
Measurement and Evaluation Techniques Used in the Course	Classical exams are held in midterm and final exams.
Information	This course is evaluated with a relative evaluation system.

ECTS / WORK LOAD TABLE

CONTRIBUTION OF LEARNING OUTCOMES TO PROGRAMME QUALIFICATIONS

LO: Learning Objectives

PQ: Program Qualifications

Contribution Level:

1 Very Low

2 Low

3 Medium

4 High

5 Very High