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Course Code: 
ECON 606
Semester: 
Autumn
Course Type: 
Core
P: 
3
Lab: 
0
Credits: 
3
ECTS: 
10
Course Language: 
English
Course Objectives: 

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

Course Content: 

This course will deal with the analysis and handling of data and the basics of the regression analysis: The simple and multiple regression models, Gauss Markov assumptions, Estimation and hypothesis testing, Ordinary Least Squares estimation, asymptotics, Specification and data problems, heterosekedasticity and autocorrelation. 

Teaching Methods: 
Lecture, Question-Answer, Discussion
Assessment Methods: 
Testing, Homework

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 understand the underlying assumptions of the simple and multiple regression models 1,2,3,4,5 1,2,3 A., C
Be able to estimate the unknown population parameters of the regression models 1,2,3,4,5 1,2,3 A., C
Be able to test  different  hypohesis testing proecdures 1,2,3,4,5 1,2,3 A., C
Be able to test  and use generalized estimation procedures in the case of the violations of the basic regression model 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 and its basic assumptions  
4 Multiple regression: Estimation  
5 Multiple regression: Hypothesis testing  
6 Ordinary Least Squares Asymptotics  
7 Mid-Term  
8 Functional form in regression analysis  
9 Prediction and Residual analysis  
10 Misspecification in Regression analysis  
11 Data problems: Proxy variables, measurement error, missing data  
12 Heteroskedasticity  
13 Autocorrelation  
14 Review  

Recommended Sources

RECOMMENDED SOURCES
Textbook Wooldridge, J. M., Introductory Econometrics, Thomson, South-Western
Additional Resources  

Material Sharing

MATERIAL SHARING
Documents Homeworks
Assignments  
Exams  

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 1 50
Contribution of In-Term Studies to Overall Grade 1 50
  Total 100
Course Category Compulsory

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  

ECTS

ECTS ALLOCATED BASED ON STUDENT WORKLOAD BY THE COURSE 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 10 10
Quizzes (attendance, presentation, etc.) 3 3 9
Assignments 2 7 14
Final Examination 1 10 10
Total Work Load     238
Total Work Load / 25 (s)     9,52
ECTS Credit of the Course     10