COURSE INFORMATION Course Title: TIME SERIES IN ECONOMETRICS

Code	Course Type	Regular Semester	Theory	Practice	Lab	Credits	ECTS
ECO 402	E	2	3	0	0	3	7.5

Academic staff member responsible for the design of the course syllabus (name, surname, academic title/scientific degree, email address and signature)	NA
Lecturer (name, surname, academic title/scientific degree, email address and signature) and Office Hours:	Uğur Ergün
Second Lecturer(s) (name, surname, academic title/scientific degree, email address and signature) and Office Hours:	NA
Teaching Assistant(s) and Office Hours:	NA
Language:	English
Compulsory/Elective:	Compulsory
Classroom and Meeting Time:
Course Description:	The course consists of econometric models which are employed in time series analyses. It covers the topics such as time series regression, exploratory data analysis, ARMA/ARIMA models, model identification/estimation/linear operators, GARCH family models, Co-integration, VAR analysis, Causality, Panel Data analyses. The Analyses are performed using E-views software program.
Course Objectives:	- to teach applied Time Series methodologies with an emphasis on model building and accurate prediction in order to apply to real life situations. - to provide the ability to bring together and flexibly apply knowledge to characterize, analyses and solve a wide range of social, economic and scientific problems. - to provide students skills required to research in economics and finance with exposure to more advanced econometric practices and models.

COURSE OUTLINE

Week	Topics
1	Introduction
2	Basic Regression Analysis with Time Series Data
3	Basic Regression Analysis with Time Series Data
4	Further Issues in Using OLS with Time series data
5	Serial Correlation
6	Heteroskedasticity
7	Midterm exam
8	ARMA models
9	VAR and VECM
10	Cointegration
11	ARCH and GARCH models
12	ARDL model
13	Panel Data Analysis
14	Revision

Prerequisite(s):
Textbook:	Wooldridge J.M.(2015). Introduction to Econometrics. Cengage Learning. Verbeek M. (2015). A Guide to Modern Econometrics. John Wiley & Sons Ltd.
Other References:	Vogelvang B. (2015). Econometrics Theroy and Applications with E-views. Printice Hall.
Laboratory Work:
Computer Usage:	E-views software program
Others:	No

COURSE LEARNING OUTCOMES

1	Provide skill to apply economic models in econometrics
2	Provide skill to set up econometric models
3	Provide ability for testing specification of the model
4	Provide skill to apply time series econometric methods in academic research

COURSE CONTRIBUTION TO... PROGRAM COMPETENCIES (Blank : no contribution, 1: least contribution ... 5: highest contribution)

No	Program Competencies	Cont.
Master of Science in Economics Program
1	Students apply advanced knowledge in economics	4
2	Students explain the interaction between related disciplines and economics	4
3	Students apply scientific methods to address economic problems	5
4	Students define existing theory in a specialized branch of economics	5
5	Students critically evaluate knowledge in economics and carry out advanced research independently	5
6	Students develop economic models and formulate policy options	4
7	Students make an original contribution to the discipline	5
8	Students effectively communicate in a variety of professional and academic contexts	4
9	Students will develop new strategic approaches for unexpected, complicated situations in economics and take responsibility in solving them	4
10	Students uphold and defend ethical values data collection, interpretation and dissemination	4
11	Students use advanced empirical analyses to address social problems	5
12	Students interact with professional networks in their field of specialization	3

COURSE EVALUATION METHOD

Method	Quantity	Percentage
Project	1	30
Lab/Practical Exams(s)	1	20
Final Exam	1	30
Attendance		20
	Total Percent:	100%

ECTS (ALLOCATED BASED ON STUDENT WORKLOAD)

Activities	Quantity	Duration(Hours)	Total Workload(Hours)
Course Duration (Including the exam week: 16x Total course hours)	16	3	48
Hours for off-the-classroom study (Pre-study, practice)	16	5	80
Mid-terms			0
Assignments	1	29.5	29.5
Final examination			0
Other	1	30	30
Total Work Load:			187.5
Total Work Load/25(h):			7.5
ECTS Credit of the Course:			7.5