1	Course Title:	ECONOMETRICS II
2	Course Code:	EKO3104
3	Type of Course:	Compulsory
4	Level of Course:	First Cycle
5	Year of Study:	3
6	Semester:	6
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. Mustafa Sevüktekin
16	Course Lecturers:	Prof. Dr. Mustafa Sevüktekin, Doç. Dr. Kadir Yasin Eryiğit, Doç. Dr. Mehmet Çınar, Doç. Dr. Özer Arabacı
17	Contactinformation of the Course Coordinator:	sevuktekin@uludag.edu.tr Uludağ Universitesi İktisadi ve İdari Bilimler Fakültesi Ekonometri A.B.D. 16059 Görükle/Bursa Türkiye Telephone: +90 224 2941160
18	Website:	https://sites.google.com/a/sacit.org/eko3102/
19	Objective of the Course:	The students should get the skills of construction and development of multiple regression models, get acquainted with some non-linear models and special methods of econometric analysis and estimation, understanding the area of their application in economics.
20	Contribution of the Course to Professional Development

21

Learning Outcomes:

1 To be able to use Basic skills of econometric analysis; 2 To be able to understand econometric methods; 3 To be able to understand econometric approaches, ideas, results and conclusions; 4 To be able to use The tools needed to build multiple linear regression model; 5 To be able to understand Small sample properties of regression model; 6 To be able to understand Functional forms of regression models; 7 To be able to understand Variable Transformations; 8 To be able to understand Structural breaks; 9 To be able to understand Large sample properties of regression model; 10 To be able to understand Specification issues;

22	Course Content:

Week	Theoretical	Practical
1	Specification of Multiple Linear Regression Model
2	OLS Estimation of Multiple Linear Regression Model
3	Inference from Multiple Linear Regression Model
4	Small Sample Properties of Regression Model
5	Functional Forms
6	Variable Transformations
7	Other Specification Issues(Midterm exam)
8	Dummy Independent Variables
9	Nature of Time Series Data
10	Deterministic Trend and Structural Break
11	Large Sample Properties of Regression Model
12	Nature and Consequences of Heteroskedasticity
13	Testing for Heteroskedasticity
14	Weighted (Generalized) Least Squares

23	Textbooks, References and/or Other Materials:	Woodridge, Jeffrey M. (2009), Introductory Econometrics: A modern Approach, Fourth Edition, South-Western College Publishing.
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
Information

25

ECTS / WORK LOAD TABLE

Activites	NUMBER	TIME [Hour]	Total WorkLoad [Hour]
Theoretical	14	3	42
Practicals/Labs	0	0	0
Self Study and Preparation	14	2	28
Homeworks, Performances	0	0	0
Projects	0	0	0
Field Studies	0	0	0
Midtermexams	1	35	35
Others	0	0	0
Final Exams	1	40	40
Total WorkLoad			145
Total workload/ 30 hr			4,83
ECTS Credit of the Course			5

26	CONTRIBUTION OF LEARNING OUTCOMES TO PROGRAMME QUALIFICATIONS
PQ1 PQ2 PQ3 PQ4 PQ5 PQ6 PQ7 PQ8 PQ9 PQ10 PQ11 PQ12 LO1 3 4 5 3 4 5 3 4 5 3 4 5 LO2 4 5 3 4 5 3 4 5 3 4 5 3 LO3 5 3 4 5 3 4 5 3 4 5 3 4 LO4 5 4 3 5 4 3 5 4 3 5 4 3 LO5 4 3 5 4 3 5 4 3 5 4 3 5 LO6 3 5 4 3 5 4 3 5 4 3 5 4 LO7 3 4 5 3 4 5 3 4 5 3 4 5 LO8 5 4 3 5 4 3 5 4 3 5 3 5 LO9 4 3 4 4 4 4 3 5 3 4 5 5 LO10 3 5 5 4 3 5 4 4 4 3 3 3

LO: Learning Objectives

PQ: Program Qualifications

Contribution Level:

1 Very Low

2 Low

3 Medium

4 High

5 Very High