Description of Individual Course Units
Course Unit CodeCourse Unit TitleType of Course UnitYear of StudySemesterNumber of ECTS Credits
İST424ECONOMETRIC MODELSElective485
Level of Course Unit
First Cycle
Objectives of the Course
Applying the mathematics and statistics information to economic data.
Name of Lecturer(s)
Dr.Öğr.Üyesi Özge Elmastaş Gültekin
Learning Outcomes
1Having knowledge of some basic mathematics and statistics rules.
2Studying the basic and multiple linear regression.
3Setting linear, parabolic, semi-log and log-log models.
4Contructing multiple regression model, making an estimation and hypothesis tests, learning their matrix solution techniques.
5Studying the deviations of the classical linear regression model assumptions (Normality, multicollinearity, heteroscedasticity, autocorrelation, spesification errors).
6Constructing the models with dummy variables, examining the simultaneous equation models, dynamic econometric models and panel data analysis, understanding the logistic regression.
Mode of Delivery
Face to Face
Prerequisites and co-requisities
None
Recommended Optional Programme Components
None
Course Contents
Having knowledge of some basic mathematics and statistics rules, setting various econometric model forms, realizing the econometric models which involve one independent variables, contructing multiple regression model, making an estimation and hypothesis tests, learning their matrix solution techniques, studying the deviations of the classical linear regression model assumptions, constructing the models with dummy variables, examining the simultaneous equation models, dynamic econometric models and panel data analysis, understanding the logistic regression.
Weekly Detailed Course Contents
WeekTheoreticalPracticeLaboratory
1Introducing the course and explaining the content of the course.
2The subject of econometrics, some basic mathematics and statistics information, micro, macro and sectoral models.
3Basic linear regression model
4Multiple linear regression model
5Econometric model forms(Linear, parabolic, semi-logaritmic, log-log models)
6Examining the Normality assumption
7Examining the Multicollinearity assumption
8Midterm
9Examining the Heteroscedasticity assumption
10Examining the Autocorrelation assumption
11Models with dummy variables
12Logistic regression
13Simultaneous equation models
14Panel data analysis
15Dynamic econometric models
16Final examination
Recommended or Required Reading
1) Ertek, T., Ekonometriye giriş 2) Tarı,R., Ekonometri 3) Gujarati, D.N. & Dawn, C.P., Çevirenler: Şenesen, Ü., Günlük Şenesen, G., Temel Ekonometri 4) Güriş, S., Çağlayan, E., Ekonometri-Temel Kavramlar 5) Gujarati, D., Çeviren: Bolatoğlu, N., Örneklerle Ekonometri
Planned Learning Activities and Teaching Methods
Assessment Methods and Criteria
Term (or Year) Learning ActivitiesQuantityWeight
SUM0
End Of Term (or Year) Learning ActivitiesQuantityWeight
SUM0
SUM0
Language of Instruction
Turkish
Work Placement(s)
-
Workload Calculation
ActivitiesNumberTime (hours)Total Work Load (hours)
Midterm Examination122
Final Examination122
Attending Lectures14456
Practice2510
Self Study16348
Individual Study for Homework Problems16232
TOTAL WORKLOAD (hours)150
Contribution of Learning Outcomes to Programme Outcomes
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LO15444 4   4  45   4 4   4
LO2554 5 4  5  45   5 45  5
LO3554 5 4  5  45   5 45  5
LO4554 5 4  5  45   5 45  5
LO5554 5 4  5  45  45 45  5
LO6554 5 4  5  45   5 45  5
* Contribution Level : 1 Very low 2 Low 3 Medium 4 High 5 Very High
 
Ege University, Bornova - İzmir / TURKEY • Phone: +90 232 311 10 10 • e-mail: intrec@mail.ege.edu.tr