FACULTY OF BUSINESS

Department of Economics

ECON 416 | Course Introduction and Application Information

Course Name
Time Series Analysis
Code
Semester
Theory
(hour/week)
Application/Lab
(hour/week)
Local Credits
ECTS
ECON 416
Fall/Spring
3
0
3
6

Prerequisites
  ECON 301 To succeed (To get a grade of at least DD)
Course Language
English
Course Type
Elective
Course Level
First Cycle
Mode of Delivery -
Teaching Methods and Techniques of the Course -
Course Coordinator
Course Lecturer(s)
Assistant(s)
Course Objectives This course is an introduction the econometric analysis of time series. Previous exposition to an introductory econometrics course is assumed, but the material is designed to be as selfcontained as possible. The focus of the class is mostly empirical. The student will be asked to apply his/her knowledge of the topics to real data on a weekly basis, and carry out a research project on a topic of his/her choice.
Learning Outcomes The students who succeeded in this course;
  • Will be able to define the specific properties of time series data.
  • Will be able to use econometric tools that are specifically designed to analyze time series data.
  • Will be able to build econometric models that describe the behavior of time series.
  • Will be able to identify problems with existing econometric models.
  • Will be able to employ the econometric tools necessary to solve problems with existing econometric models.
  • Will be able to interpret the results that are obtained through econometric analysis.
  • Will be able to pursue an independent empirical research project from start to finish.
Course Description The class covers the theory behind a variety of topics in time series econometrics, and introduces the student to a large number of time series applications. Class exposition is evenly divided between theory and applications, but applications are given priority in assignements and exams. After a brief review of statistical and econometric basics, we discuss the use of difference equations and lag operators. Stationary ARMA models are covered in great detail, and so are ARCH, GARCH, and VAR techniques. The student is also exposed to nonstationary time series, unit roots, and ARIMA models. The class ends with discussions on cointegration and forecasting.

 



Course Category

Core Courses
Major Area Courses
X
Supportive Courses
Media and Management Skills Courses
Transferable Skill Courses

 

WEEKLY SUBJECTS AND RELATED PREPARATION STUDIES

Week Subjects Related Preparation
1 Review of statistical concepts and regression basics
2 Difference equations, lag operators
3 Foundations of time series econometrics
4 Topics in Linear Regression
5 ARMA Modeling 1
6 ARMA Modeling 2
7 ARMA Modeling 3
8 Midterm
9 Nonstationarity, unit roots, and ARIMA Models
10 Autoregressive conditional heteroscedasticity: ARCH and GARCH models
11 Stationary vector models: VAR pt. 1
12 Stationary vector models: VAR pt. 2
13 Cointegration and common trends
14 Forecasting with time series
15 Additional topic (optional and time permitting)
16 Presentations

 

Course Notes/Textbooks Walter Enders, Applied Econometric Time Series (Second Edition), Wiley.
Suggested Readings/Materials Two additional sources are recommended, and may provide additional class material: \n• Paul S. P. Cowpertwait and Andrew V. Metcalfe, Introductory Time Series with R.\n• Brockwell and Davis, Introduction to Time Series and Forecasting (Second Edition).

 

EVALUATION SYSTEM

Semester Activities Number Weigthing
Participation
16
10
Laboratory / Application
Field Work
Quizzes / Studio Critiques
Portfolio
Homework / Assignments
Presentation / Jury
Project
2
40
Seminar / Workshop
Oral Exams
Midterm
1
20
Final Exam
1
30
Total

Weighting of Semester Activities on the Final Grade
70
Weighting of End-of-Semester Activities on the Final Grade
30
Total

ECTS / WORKLOAD TABLE

Semester Activities Number Duration (Hours) Workload
Theoretical Course Hours
(Including exam week: 16 x total hours)
16
3
48
Laboratory / Application Hours
(Including exam week: '.16.' x total hours)
16
0
Study Hours Out of Class
0
Field Work
0
Quizzes / Studio Critiques
0
Portfolio
0
Homework / Assignments
0
Presentation / Jury
0
Project
2
35
70
Seminar / Workshop
0
Oral Exam
0
Midterms
1
20
20
Final Exam
1
27
27
    Total
165

 

COURSE LEARNING OUTCOMES AND PROGRAM QUALIFICATIONS RELATIONSHIP

#
Program Competencies/Outcomes
* Contribution Level
1
2
3
4
5
1

To be able to acquire a sound knowledge of fundamental concepts, theories, principles and methods of investigation specific to the economic field.

X
2

To be able to apply adequate mathematical, econometric, statistical and data analysis models to process economic data and to implement scientific research for development of economic policies.

3

To be able to participate in academic, professional, regional, and global networks and to utilize these networks efficiently.

4

To be able to have adequate social responsibility with regards to the needs of the society and to organize the activities to influence social dynamics in line with social goals.

5

To be able to integrate the knowledge and training acquired during the university education with personal education and produce a synthesis of knowledge one requires.

6

To be able to evaluate his/her advance level educational needs and do necessary planning to fulfill those needs through the acquired capability to think analytically and critically.

X
7

To be able to acquire necessary skills to integrate social dynamics into economic process both as an input and an output.

X
8

To be able to link accumulated knowledge acquired during the university education with historical and cultural qualities of the society and be able to convey it to different strata of society.

9

To be able to take the responsibility as an individual and as a team member.

10

To be able to attain social, scientific and ethical values at the data collection, interpretation and dissemination stages of economic analysis.

X
11

To be able to collect data in economics and communicate with colleagues in a foreign language ("European Language Portfolio Global Scale", Level B1)

X
12

To be able to speak a second foreign at a medium level of fluency efficiently.

13

To be able to relate the knowledge accumulated throughout human history to their field of economics.

*1 Lowest, 2 Low, 3 Average, 4 High, 5 Highest

 


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