Information Package / Course Catalogue
Econometric Analysis I
Course Code: İKP503
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

Econometrics analysis 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.

Name of Lecturer(s)
Assoc. Prof. Hatice AKDAĞ
Learning Outcomes
1.Formulate and develop a critical and comprehensive understanding of global and national economic problems, and construct and design practical solutions
2.Extract information and concepts from various disciplines in social sciences and integrate them under the rubric of economics
3.Construct testable hypotheses to find original, practical solutions to various social ills and problems
4.Develop an analytical understanding of economic problems, and the ability to evaluate the inherent logic, assumptions and conclusions of alternative approaches
5.They can reach scientific results through econometric analysis methods
Recommended or Required Reading
1.Woodridge, Jeffrey M. (2009), Introductory Econometrics: A modern Approach, Fourth Edition, South-Western College Publishing
2.Hill, Carter R., William E. Griffiths, Guay C. Lim (2007), Principles of Econometrics, John Wiley & Sons, Inc.
Weekly Detailed Course Contents
Week 1 - Theoretical
Basic data handling
Week 2 - Theoretical
Basic data handling continued
Week 3 - Theoretical
Simple regression and its basic assumptions
Week 4 - Theoretical
Multiple regression: Estimation
Week 5 - Theoretical
Multiple regression: Hypothesis testing
Week 6 - Theoretical
Ordinary Least Squares Asymptotics
Week 7 - Theoretical
Functional form in regression analysis
Week 8 - Intermediate Exam
Midterm
Week 9 - Theoretical
Prediction and Residual analysis
Week 10 - Theoretical
Misspecification in Regression analysis
Week 11 - Theoretical
Data problems: Proxy variables, measurement error, missing data
Week 12 - Theoretical
Heteroskedasticity
Week 13 - Theoretical
Autocorrelation
Week 14 - Theoretical
General review and evaluation of the course
Week 15 - Theoretical
General review and evaluation of the course
Week 16 - Final Exam
Final Exam
Assessment Methods and Criteria
Type of AssessmentCountPercent
Midterm Examination1%40
Final Examination1%60
Workload Calculation
ActivitiesCountPreparationTimeTotal Work Load (hours)
Lecture - Theory144398
Midterm Examination110111
Final Examination120121
TOTAL WORKLOAD (hours)130
Contribution of Learning Outcomes to Programme Outcomes
PÇ-1
PÇ-2
PÇ-3
PÇ-4
PÇ-5
PÇ-6
PÇ-7
OÇ-1
4
4
4
4
4
4
4
OÇ-2
3
3
3
3
3
3
3
OÇ-3
5
5
5
5
5
5
5
OÇ-4
4
4
4
4
4
4
4
OÇ-5
4
4
4
4
5
5
4
Adnan Menderes University - Information Package / Course Catalogue
2026