FACULTY OF BUSINESS

Department of Economics

ECON 301 | Course Introduction and Application Information

Course Name
Econometrics
Code
Semester
Theory
(hour/week)
Application/Lab
(hour/week)
Local Credits
ECTS
ECON 301
Fall
3
0
3
6

Prerequisites
  ECON 101 To succeed (To get a grade of at least DD)
and ECON 102 To succeed (To get a grade of at least DD)
Course Language
English
Course Type
Required
Course Level
First Cycle
Mode of Delivery -
Teaching Methods and Techniques of the Course -
Course Coordinator
Course Lecturer(s)
Assistant(s)
Course Objectives The main objective of the course is to improve the students’ basic statistical knowledge to conduct advanced level econometric analysis. More specifically, it aims to give extensive background on econometric techniques, their implementation and usage in a high level statistical package (R-studio). Each student is required to prepare a project to show their skills developed in this course.
Learning Outcomes The students who succeeded in this course;
  • Will be able to collect data related to social and economic topics.
  • Will be able to get raw data ready for statistical and econometric analysis.
  • Will be able to build econometric models that describe the data generating process behind data.
  • Will be able to interpret the results that are obtained through econometric analysis.
  • Will be able to conduct an independent empirical research project from start to finish.
  • Will be able to use an econometrics software (R-studio) to make statistical and econometric analysis.
Course Description Econometrics can be defined as the “application of statistics to the analysis of economic phenomena”.  The knowledge of econometrics is essential to test economic theories and to understand empirical work being done in Economics. The course will teach how to do empirical work by using examples drawn from various fields in economics. It will also focus on various types of economic data, how one can obtain them, and how they may be used. Topics include regression analysis, ordinary least squares, hypothesis testing, choosing independent variables and functional form, multicollinearity, serial correlation and heteroskedasticity. To aid in empirical work R-studio will be used.

 



Course Category

Core Courses
X
Major Area Courses
Supportive Courses
Media and Management Skills Courses
Transferable Skill Courses

 

WEEKLY SUBJECTS AND RELATED PREPARATION STUDIES

Week Subjects Related Preparation
1 Mathematical and Statistical Foundations Stock and Watson, Ch 1-2-3
2 Introduction to R-studio Lecture Notes
3 Overview of Regression Analysis Stock and Watson, Ch 4
4 Ordinary Least Squares, Learning to Use Regression Analysis Stock and Watson, Ch 4
5 The Classical Model Stock and Watson, Ch 4-5
6 The Classical Model Stock and Watson, Ch 4-5
7 Hypothesis Testing Stock and Watson, Ch 5
8 Hypothesis Testing Stock and Watson, Ch 5
9 Midterm Exam
10 Multicollinearity Stock and Watson, Ch 6-7
11 Heteroskedasticity Stock and Watson, Ch 7-8-9
12 Heteroskedasticity Stock and Watson, Ch 7-8-9
13 Serial Correlation Stock and Watson, Ch 7-8-9
14 Serial Correlation Stock and Watson, Ch 7-8-9
15 Additional Topic(s) (Optional and Time Permitting)
16 Additional Topic(s) (Optional and Time Permitting)

 

Course Notes/Textbooks

Stock, J. H., & Watson, M. W. (2020). Introduction to Econometrics. Fourth Edition, Global Edition: Pearson.

A. H. Studenmund, Using econometrics: a practical guide, sixth edition 2011, Boston: Addison-Wesley

C. Dougherty, Introduction to Econometrics, fifth edition 2016, Oxford University Press

 
Suggested Readings/Materials • Peter E. Kennedy, A Guide to Econometrics (5th Edition) • Jeffrey M. Woolridge, Introductory Econometrics: A Modern Approach (4th Edition) • Joshua D. Angrist and JornSteffen Pischke, Mostly Harmless Econometrics: An Empiricist’s Companion.

 

EVALUATION SYSTEM

Semester Activities Number Weigthing
Participation
16
10
Laboratory / Application
Field Work
Quizzes / Studio Critiques
Portfolio
Homework / Assignments
Presentation / Jury
Project
1
30
Seminar / Workshop
Oral Exams
Midterm
1
30
Final Exam
1
30
Total

Weighting of Semester Activities on the Final Grade
18
60
Weighting of End-of-Semester Activities on the Final Grade
1
40
Total

ECTS / WORKLOAD TABLE

Semester Activities Number Duration (Hours) Workload
Theoretical Course Hours
(Including exam week: 16 x total hours)
16
3
48
Laboratory / Application Hours
(Including exam week: '.16.' x total hours)
16
0
Study Hours Out of Class
16
3
48
Field Work
0
Quizzes / Studio Critiques
0
Portfolio
0
Homework / Assignments
0
Presentation / Jury
0
Project
1
24
24
Seminar / Workshop
0
Oral Exam
0
Midterms
1
30
30
Final Exam
1
30
30
    Total
180

 

COURSE LEARNING OUTCOMES AND PROGRAM QUALIFICATIONS RELATIONSHIP

#
Program Competencies/Outcomes
* Contribution Level
1
2
3
4
5
1

To be able to acquire a sound knowledge of fundamental concepts, theories, principles and methods of investigation specific to the economic field.

X
2

To be able to apply adequate mathematical, econometric, statistical and data analysis models to process economic data and to implement scientific research for development of economic policies.

X
3

To be able to participate in academic, professional, regional, and global networks and to utilize these networks efficiently.

X
4

To be able to have adequate social responsibility with regards to the needs of the society and to organize the activities to influence social dynamics in line with social goals.

5

To be able to integrate the knowledge and training acquired during the university education with personal education and produce a synthesis of knowledge one requires.

6

To be able to evaluate his/her advance level educational needs and do necessary planning to fulfill those needs through the acquired capability to think analytically and critically.

X
7

To be able to acquire necessary skills to integrate social dynamics into economic process both as an input and an output.

X
8

To be able to link accumulated knowledge acquired during the university education with historical and cultural qualities of the society and be able to convey it to different strata of society.

9

To be able to take the responsibility as an individual and as a team member.

10

To be able to attain social, scientific and ethical values at the data collection, interpretation and dissemination stages of economic analysis.

X
11

To be able to collect data in economics and communicate with colleagues in a foreign language ("European Language Portfolio Global Scale", Level B1)

X
12

To be able to speak a second foreign at a medium level of fluency efficiently.

13

To be able to relate the knowledge accumulated throughout human history to their field of economics.

*1 Lowest, 2 Low, 3 Average, 4 High, 5 Highest

 


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