Information Package / Course Catalogue
Advanced Econometrics
Course Code: ECN507
Course Type: Area Elective
Couse Group: Second Cycle (Master's Degree)
Education Language: Turkish
Work Placement: N/A
Theory: 3
Prt.: 0
Credit: 3
Lab: 0
ECTS: 5
Objectives of the Course

The objective of this course is to introduce applied and theoric fundamentals of econometrics to the students. Special emphasis will paid to application of multiple regression and simultaneous equation systems.

Course Content

The course will mainly cover the theories and applications of the simple and multiple regression analysis. Afterwards the consequences of the relaxing the assumptions of the classical regression model will be discussed. Within this framework regular computer lab sessions will be held during the course.

Name of Lecturer(s)
Learning Outcomes
1.Comprehend fundamentals of CLRM (Classical linear regression model).
2.Learn inference methods, asymptotic properties of estimators.
3.Use common linear regression models used in applied econometric analysis of cross- sectional and time-series data.
4.Understand consequences of the violation of the assumptions of linear regression model.
5.Learn how to address different estimation/specification problems typically faced in applied economic research using linear regression techniques (such as heteroskedasticity, multicollinearity, autocorrelation).
Recommended or Required Reading
1.Greene, W. H. (1997): Econometric Analysis, Second Edition, Prentice Hall..
2.Griffiths, Hill and Judge (1993)"Learning and Practicing Econometrics", Wiley and Sons.
3.Gujarati, Damodar N. Basic Econometrics, 3rd Edition. New York, NY: McGraw-Hill.
Weekly Detailed Course Contents
Week 1 - Theoretical
Introduction of the course
Week 2 - Theoretical
Review of Probability and Mathematical concepts
Week 3 - Theoretical
Review of Probability and Mathematical concepts
Week 4 - Theoretical
Simple Linear Regression Model
Week 5 - Theoretical
Simple Linear Regression Model
Week 6 - Theoretical
Computer Lab
Week 7 - Theoretical
Multiple Regression: Estimation
Week 8 - Theoretical
Violation of the Assumptions of CLRM: Autocorrelation
Week 9 - Intermediate Exam
Midterm Examination
Week 10 - Theoretical
Violation of the Assumptions of CLRM: Heteroscedasticity
Week 11 - Theoretical
Model Specification and Diagnostic Testing
Week 12 - Theoretical
Computer Lab
Week 13 - Theoretical
Simultaneous-Equation Models
Week 14 - Theoretical
Computer Lab
Week 15 - Theoretical
Presentation of the Research Projects
Week 16 - Final Exam
Final Examination
Assessment Methods and Criteria
Type of AssessmentCountPercent
Midterm Examination1%30
Final Examination1%70
Workload Calculation
ActivitiesCountPreparationTimeTotal Work Load (hours)
Lecture - Theory140342
Individual Work140228
Midterm Examination123225
Final Examination128230
TOTAL WORKLOAD (hours)125
Contribution of Learning Outcomes to Programme Outcomes
PÇ-1
PÇ-2
PÇ-3
PÇ-4
PÇ-5
PÇ-6
PÇ-7
PÇ-8
PÇ-9
PÇ-10
PÇ-11
PÇ-12
PÇ-13
PÇ-14
PÇ-15
OÇ-1
2
5
3
3
4
5
4
OÇ-2
3
4
2
2
3
4
5
OÇ-3
2
3
3
3
3
4
3
OÇ-4
3
3
2
3
3
3
4
OÇ-5
2
4
3
4
3
4
3
Adnan Menderes University - Information Package / Course Catalogue
2026