ECONOMETRICS PROGRAMME COURSE DESCRIPTION

Code	Name of the Course Unit	Semester	In-Class Hours (T+P)	Credit	ECTS Credit
ECF352	ECONOMETRICS	6	4	3	7

GENERAL INFORMATION
Language of Instruction :	English
Level of the Course Unit :	BACHELOR'S DEGREE, TYY: + 6.Level, EQF-LLL: 6.Level, QF-EHEA: First Cycle
Type of the Course :	Compulsory
Mode of Delivery of the Course Unit	-
Coordinator of the Course Unit	Prof. BÜLENT EŞİYOK
Instructor(s) of the Course Unit
Course Prerequisite	No

OBJECTIVES AND CONTENTS
Objectives of the Course Unit:	The aim of this course is to familiarize students with the basic concepts and techniques used in econometrics with practical applications. To enhance the analytical skills of students to interpret the regression results, the lectures will focus on both the theoretical and empirical aspects of regression analysis.
Contents of the Course Unit:	The course will introduce the basis of the classical linear regression model; assumptions, the problems of estimation and inference, violation of the assumptions of the model.

KEY LEARNING OUTCOMES OF THE COURSE UNIT (On successful completion of this course unit, students/learners will or will be able to)
Describe the basic econometric concepts. (2)
Solve basic econometric problems. (3)
Use basic econometric forecast methods. (3)
Explain the econometrics-related terms, forecast and prediction techniques. (2)
Analyze the validity of economic theory by using econometric techniques. (4)
Compare the relationship between economic variables graphically, mathematically and econometrically. (4)
Interpret the results of econometric model. (4)

WEEKLY COURSE CONTENTS AND STUDY MATERIALS FOR PRELIMINARY & FURTHER STUDY
Week	Preparatory	Topics(Subjects)	Method
1	Reading	What is Econometrics? Steps in Empirical Economic Analysis, The Structure of Economic data, Causality and the notion of Ceteris Paribus in Econometric Analysis	Lecture & Question Answer & Research
2	Reading	Definition of the Simple Regression Model, Deriving the Ordinary Least Squares Estimates, Properties of OLS on Any Sample of Data, Units of Measurement and Functional Form, Expected Values and Variances of the OLS Estimators, Regression Through the Origin and Regression on a Constant	Lecture & Question Answer & Research
3	Reading	Definition of the Simple Regression Model, Deriving the Ordinary Least Squares Estimates, Properties of OLS on Any Sample of Data, Units of Measurement and Functional Form, Expected Values and Variances of the OLS Estimators, Regression Through the Origin and Regression on a Constant	Lecture & Question Answer & Research
4	Reading	Motivation for Multiple Regression, Mechanics and Interpretation of Ordinary Least Squares, The Expected Value of the OLS Estimators, The Variance of the OLS Estimators, Efficiency of OLS: The Gauss-Markov Theorem, Some Comments on the Language of Multiple Regression Analysis	Lecture & Question Answer & Research
5	Reading	Motivation for Multiple Regression, Mechanics and Interpretation of Ordinary Least Squares, The Expected Value of the OLS Estimators, The Variance of the OLS Estimators, Efficiency of OLS: The Gauss-Markov Theorem, Some Comments on the Language of Multiple Regression Analysis	Lecture & Question Answer & Research
6	Reading	Sampling Distributions of the OLS Estimators, Testing Hypotheses About a Single Population Parameter: The t Test, Confidence Intervals, Testing Hypotheses About a Single Linear Combination of the Parameters, Testing Multiple Linear Restrictions: The F Test, Reporting Regression Results	Lecture & Question Answer & Research
7	Reading	Effects of Data Scaling on OLS Statistics Beta Coefficients, More on Functional Form, More on Goodness-of-Fit and Selection of Regressors, Prediction and Residual Analysis	Lecture & Question Answer & Research
8	-	MID-TERM EXAM	-
9	Reading	Describing Qualitative Information, A Single Dummy Independent Variable, Using Dummy Variables for Multiple Categories, Interactions Involving Dummy Variables (Sections 7.5 – 7.7 are not included.)	Lecture & Question Answer & Research
10	Reading	Describing Qualitative Information, A Single Dummy Independent Variable, Using Dummy Variables for Multiple Categories, Interactions Involving Dummy Variables (Sections 7.5 – 7.7 are not included.)	Lecture & Question Answer & Research
11	Reading	Consequences of Heteroskedasticity for OLS Heteroskedasticity-Robust Inference After OLS Estimation Testing for Heteroskedasticity	Lecture & Question Answer & Research
12	Reading	The Nature of Time Series Data, Examples of Time Series Regression Models, Finite Sample Properties of OLS Under Classical Assumptions, Functional Form, Dummy Variables, and Index Numbers, Trends and Seasonality	Lecture & Question Answer & Research
13	Reading	Properties of OLS with Serially Correlated Errors, Testing for Serial Correlation (Sections 12.3, 12.4, 12.5. 12.6 are not included.)	Lecture & Question Answer & Research
14	Reading	Properties of OLS with Serially Correlated Errors, Testing for Serial Correlation (Sections 12.3, 12.4, 12.5. 12.6 are not included.)	Lecture & Question Answer & Research
15	Reading	Revision	Lecture & Question Answer & Research
16	-	FINAL EXAM	-
17	-	FINAL EXAM	-

SOURCE MATERIALS & RECOMMENDED READING
Wooldridge, J. M., 2012, Introductory Econometrics: A Modern Approach, 5/e., Thomson-South-Western.
Damodar, N. G., 2004, Basic Econometrics-Damodar N. Gujarati. McGraw− Hill.

ASSESSMENT
Assessment & Grading of In-Term Activities	Number of Activities	Degree of Contribution (%)	Description

Level of Contribution
0	1	2	3	4	5

KNOWLEDGE
Theoretical
	Programme Learning Outcomes	Level of Contribution
		0	1	2	3	4	5
1	Define the basic concepts of economics, administrative and human sciences. (Bloom 1)		1
2	Evaluate the economic environment and overall sustainability of firms. (Bloom 4)		1

KNOWLEDGE
Factual
	Programme Learning Outcomes	Level of Contribution
		0	1	2	3	4	5
1	Relate principles and concepts of economics and finance with other disciplines. (Bloom 4)				3
2	Define principles, concepts, methods and theories related with economics and finance. (Bloom 1)			2

SKILLS
Cognitive
	Programme Learning Outcomes	Level of Contribution
		0	1	2	3	4	5
1	Interpret the charts and tables related to the field. (Bloom 2)				3

SKILLS
Practical
	Programme Learning Outcomes	Level of Contribution
		0	1	2	3	4	5
1	Evaluate the theoretical models of economic policies which have direct or indirect effects by using the facts and dynamics of the economic system.(Bloom 4)			2
2	Analyze economic and financial reports. ((bloom 4)				3
3	Use basic mathematics, statistics and econometric methods and tools to solve economic and financial problems. (Bloom 3)						5
4	Interpret the operation of current economic, political and social events by using institutional information related with Economics and Finance.(Bloom 2)			2

OCCUPATIONAL
Autonomy & Responsibility
	Programme Learning Outcomes	Level of Contribution
		0	1	2	3	4	5
1	Organize economic and financial activities in humanitarian and social terms with adherence to ethics. (Bloom 4).		1

OCCUPATIONAL
Learning to Learn
	Programme Learning Outcomes	Level of Contribution
		0	1	2	3	4	5
1	Develop a critical perspective on national and international economic, political, social, financial and development problems. (bloom 6)		1

OCCUPATIONAL
Communication & Social
	Programme Learning Outcomes	Level of Contribution
		0	1	2	3	4	5
1	Follow the agenda on economics, politics and social issues and improve himself/ herself. (bloom 6)			2

OCCUPATIONAL
Occupational and/or Vocational
	Programme Learning Outcomes	Level of Contribution
		0	1	2	3	4	5
1	Analyze current issues and problems by using the structure and properties of Macro and Microeconomics and variables. (Bloom 4)		1
2	Evaluate the effectiveness of the general economic system and public policies and their effects on markets and basic economic variables.(Bloom 4)			2
3	Analyze the cause and effect relationships between the relevant economic variables. (Bloom 4)				3
4	Evaluate the expected trends and portfolio analyzes in interest and exchange rates within the framework of the general financial system. (Bloom 4)		1

WORKLOAD & ECTS CREDITS OF THE COURSE UNIT
Workload for Learning & Teaching Activities
Type of the Learning Activites	Learning Activities (# of week)	Duration (hours, h)	Workload (h)
Lecture & In-Class Activities	14	3	42
Preliminary & Further Study	13	2	26
Land Surveying	0	0	0
Group Work	0	0	0
Laboratory	0	0	0
Reading	0	0	0
Assignment (Homework)	6	3	18
Project Work	0	0	0
Seminar	0	0	0
Internship	0	0	0
Technical Visit	0	0	0
Web Based Learning	0	0	0
Implementation/Application/Practice	0	0	0
Practice at a workplace	0	0	0
Occupational Activity	0	0	0
Social Activity	0	0	0
Thesis Work	0	0	0
Field Study	0	0	0
Report Writing	0	0	0
Final Exam	1	1	1
Preparation for the Final Exam	6	10	60
Mid-Term Exam	1	1	1
Preparation for the Mid-Term Exam	3	10	30
Short Exam	0	0	0
Preparation for the Short Exam	0	0	0
TOTAL	44	0	178