Course Details

ECONOMETRICS II

Course Information

Semester	Course Unit Code	Course Unit Title	T+P+L	Credit	Number of ECTS Credits
6	ECON302	ECONOMETRICS II	3+0+0	3	5

Course Details

Language of Instruction	English
Level of Course Unit	Bachelor's Degree
Department / Program	ECONOMICS
Type of Program	Formal Education
Type of Course Unit	Compulsory
Course Delivery Method	Face To Face
Objectives of the Course	Introducing time-series and panel data model as well as the issue of heteroscedasticity. Showing how to analyze and test economic theory with empirical data.
Course Content	Statistics and econometrics knowledge that is necessary to understand and conduct econometric analysis is developed throughout the course at advanced undergraduate level. This is the second course in the undergraduate econometrics sequence. Students are assumed to have known regression analysis before taking this class. The course will focus on time-series and panel data analysis. It will cover both theory and applications, and the approach to applications will be built on econometric theory.
Course Methods and Techniques	Course applications are done by using STATA software
Prerequisites and co-requisities	( ECON301 )
Course Coordinator	None
Name of Lecturers	Asist Prof.Dr. Eda Ustaoglu eda.ustaoglu@agu.edu.tr
Assistants	Research Assist. Gulcan Doganay gulcan.doganay@agu.edu.tr
Work Placement(s)	No

Recommended or Required Reading

Resources	1) Wooldridge. J.M. (2020). Introductory Econometrics: A Modern Approach. 7th Edition. Cengage Learning. ISBN-13: 978-1-3375-5886-0 2) Gujarati, D. N. (2003) Basic Econometrics. McGraw-Hill, New York
	Wooldridge. J.M. (2020). Introductory Econometrics: A Modern Approach. 7th Edition. Cengage Learning. ISBN-13: 978-1-3375-5886-0 2) Gujarati, D. N. (2003) Basic Econometrics. McGraw-Hill, New York
	1) Wooldridge. J.M. (2020). Introductory Econometrics: A Modern Approach. 7th Edition. Cengage Learning. ISBN-13: 978-1-3375-5886-0 2) Gujarati, D. N. (2003) Basic Econometrics. McGraw-Hill, New York
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Course Category

Social Sciences

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Planned Learning Activities and Teaching Methods

Activities are given in detail in the section of "Assessment Methods and Criteria" and "Workload Calculation"

Assessment Methods and Criteria

In-Term Studies	Quantity	Percentage
Yarıyıl İçi Çalışmalarının Başarı Notunun Katkısı	1	% 20
Quiz/Küçük Sınav	1	% 25
Ödev	1	% 20
Final examination	1	% 35
Total	4	% 100

ECTS Allocated Based on Student Workload

Activities	Quantity	Duration	Total Work Load
Ev Ödevi	5	5	25
Sınıf İçi Aktivitesi	2	14	28
Okuma	3	14	42
Araştırma	3	14	42
Final Sınavı	1	20	20
Total Work Load			Number of ECTS Credits 5 157

Course Learning Outcomes: Upon the successful completion of this course, students will be able to:

No	Learning Outcomes
1	Test economic hypotheses and check significance properties
2	Construct a novel time-series and/or panel data econometric model and test overall performance of the model.
3	Understand strengths and limitations of the methods covered in the course
4	Interpretation of the model outcomes

Weekly Detailed Course Contents

Week	Topics	Study Materials	Materials
1	Introduction to the course
2	Introduction to the course
3	Basic regression analysis with time series data
4	Basic regression analysis with time series data
5	Basic regression analysis with time series data
6	Serial correlation and heteroscedasticity in time series regressions
7	LWF
8	Review and Midterm Exam
9	Serial correlation and heteroscedasticity in time series regressions
10	Pooling cross sections across time: Simple panel data methods
11	Pooling cross sections across time: Simple panel data methods
12	Pooling cross sections across time: Simple panel data methods
13	Pooling cross sections across time: Simple panel data methods
14	Pooling cross sections across time: Simple panel data methods

Contribution of Learning Outcomes to Programme Outcomes

Contribution: 1: Very Slight 2:Slight 3:Moderate 4:Significant 5:Very Significant

https://sis.agu.edu.tr/oibs/bologna/progCourseDetails.aspx?curCourse=70498&lang=en