Econometrics I

Program Type:

Thesis

Non Thesis

Course Code:

ECON 510

Semester:

Autumn

Course Type:

Core

P:

3

Lab:

0

Credits:

3

ECTS:

10

Course Language:

English

Course Coordinator:

Ahmet ÖZÇAM

Courses given by:

Ahmet ÖZÇAM

Course Objectives:

Econometrics I intends to provide a solid research skills that are useful in conducting empirical research in the fields of economics and related areas. To this extend, the students will be introduced fundemantals of econometric techniques and how these techniques will be utilized in testing economic, finance and business theories. The students will be encouraged to implement the acquired knowledge via project works.

Course Content:

This course will deals with data analysis and handling, simple and multiple regression techniques, regression with dummies and lagged variables, testing the reliability of estimators, understanding the causes and consequences of main econometric problems and providing appropriate solutions to them.

Teaching Methods:

1: Lecture, 2: Question-Answer, 3: Discussion

Assessment Methods:

A: Testing, C: Homework, Q: Quiz

Vertical Tabs

Course Learning Outcomes

Learning Outcomes	Program Learning Outcomes	Teaching Methods	Assessment Methods
Understand the meaning and usefulness of data handling	1,2,3,4,5	1,2,3	A,C
Be able to understand and apply simple and multiple regression techniques.	1,2,3,4,5	1,2,3	A,C
Be able to test and conduct different hypohesis testing proecdures	1,2,3,4,5	1,2,3	A,C
Be able to undersand and apply dummy variables in regression analysis	1,2,3,4,5	1,2,3	A,C
Be able to understand and apply different dynamic econometric techniques	1,2,3,4,5	1,2,3	A,C
Be able to understand and apply fundemantals of forecasting	1,2,3,4,5	1,2,3	A,C

Course Flow

COURSE CONTENT
Week	Topics	Study Materials
1	Basic data handling
2	Basic data handling continued
3	Simple regression
4	Multiple regression
5	Extensions in multiple regression
6	Causes and consequences of econometric problems
7	Midterm
8	Regression with dummy variables
9	Lojistik regression techniques
10	Regression with lagged variables
11	Extension in regression with lagged variables
12	Basic forecating techniques
13	Further analysis in forecesting
14	Revision

Recommended Sources

RECOMMENDED SOURCES
Textbook		List of selected text books
Additional Resources		Weekly hand outs will be distributed

Material Sharing

MATERIAL SHARING
Documents		Lecture notes
Assignments		Regular practises and applications in computing labs
Exams		Tutorial on exam questions

Assessment

ASSESSMENT
IN-TERM STUDIES	NUMBER	PERCENTAGE
Mid-terms	1	50
Quizzes (attendance, presentation, etc.)
Assignments
	Total	50
Contribution of Final Examination to Overall Grade		50
Contribution of In-Term Studies to Overall Grade		50
	Total	100

Course’s Contribution to Program

COURSE'S CONTRIBUTION TO PROGRAM
No	Program Learning Outcomes	Contribution
		1	2	3	4	5
1	Formulate and develop a critical and comprehensive understanding of global and national economic problems, and construct and design practical solutions;			x
2	Extract information and concepts from various disciplines in social sciences and integrate them under the rubric of economics;			x
3	Construct testable hypotheses to find original, practical solutions to various social ills and problems;					x
4	Develop an analytical understanding of economic problems, and the ability to evaluate the inherent logic, assumptions and conclusions of alternative approaches;				x
5	Develop the necessary technical skills to evaluate alternative approaches in economics;					x
6	Formulate research projects, plan and conduct research in social sciences in general and in economics in particular;					x
7	Present the results of their research in national and international conferences and in scientific and professional venues;			x
8	Apply the scientific / academic modes of thought and analysis to their professional lives and form a bridge between the analytical and abstract modes of thinking of academia and the practical and dynamic skills of business life;				x
9	Nurture and develop the analytical and technical skills necessary to continue their studies at a Ph.D. level, either in Turkey or elsewhere around the globe.			x

ECTS

ECTS ALLOCATED BASED ON STUDENT WORKLOAD BY THE COUSE DESCRIPTION
Activities	Quantity	Duration (Hour)	Total Workload (Hour)
Course Duration (Including the Exam Week: 15 x total course hours)	15	3	45
Hours for off-the-classroom study (Pre-study, practice)	15	10	150
Mid-terms	1	20	20
Quizzes (attendance, presentation, etc.)			0
Assignments			0
Final Examination	1	25	25
Total Work Load			240
Total Work Load / 25 (s)			9.6
ECTS Credit of the Course			10

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