|
|
| EKO5070 | Applied Econometrics - I | 3+0+0 | ECTS:7.5 | | Year / Semester | Fall Semester | | Level of Course | Second Cycle | | Status | Elective | | Department | DEPARTMENT of ECONOMETRICS | | Prerequisites and co-requisites | None | | Mode of Delivery | | | Contact Hours | 14 weeks - 3 hours of lectures per week | | Lecturer | Prof. Dr. Zehra ABDİOĞLU | | Co-Lecturer | | | Language of instruction | Turkish | | Professional practise ( internship ) | None | | | | The aim of the course: | | The objective of this course is to introduce econometric methods and make analyses using the Eviews software package. |
| Programme Outcomes | CTPO | TOA | | Upon successful completion of the course, the students will be able to : | | | | PO - 1 : | learn what are the econometrics tools. | 5,7 | 1,3, | | PO - 2 : | learn how do econometric tools use. | 5,7 | 1,3, | | PO - 3 : | learn how do econometric tools apply to economic problems. | 5,7 | 1,3, | | PO - 4 : | learn how do economic problems analysis by using econometric tools. | 5,7 | 1,3, | | PO - 5 : | learn how does a solution find out to economic problems by using econometric tools. | 5,7 | 1,3, | | CTPO : Contribution to programme outcomes, TOA :Type of assessment (1: written exam, 2: Oral exam, 3: Homework assignment, 4: Laboratory exercise/exam, 5: Seminar / presentation, 6: Term paper), PO : Learning Outcome | | |
| Correlation analysis, simple linear regression models, multiple linear regression models, heteroscedasticity, serial correlation, multicollinearity, dummy variables, trend, distributed lag models, system equations, application of E-Views program. |
| |
| Course Syllabus | | Week | Subject | Related Notes / Files | | Week 1 | Correlation analysis | | | Week 2 | Simple linear regression equation | | | Week 3 | Multi variable linear regression equation | | | Week 4 | Significance test of regression coefficients: t-test | | | Week 5 | Determination coefficient | | | Week 6 | Group significance of regression coefficients: F-Test | | | Week 7 | Spesification and functional structure in a regression equation | | | Week 8 | Dummy variables | | | Week 9 | Mid-term exam | | | Week 10 | Interaction variables, piecewise regressions, stepwise regressions and trend | | | Week 11 | Multicollinearity | | | Week 12 | Quiz | | | Week 13 | Heteroscedasticity | | | Week 14 | Autocorrelation | | | Week 15 | Lag distributed regression models | | | Week 16 | End-of-term exam | | | |
| 1 | N Gujarati, Damodar. (2004). Basic Econometrics, The McGraw Hill Compaines, Fourth Edition, New York. | | | 2 | Stock, J. H. and Watson, M. W. (2011). Introduction to Econometrics, Pearson Education, 3rd Edition, New York. | | | |
| Method of Assessment | | Type of assessment | Week No | Date | Duration (hours) | Weight (%) | | Mid-term exam | 9 | 11/2024 | 1 | 30 | | Homework/Assignment/Term-paper | 12 | 12/2024 | 1 | 20 | | End-of-term exam | 16 | 01/2025 | 1 | 50 | | |
| Student Work Load and its Distribution | | Type of work | Duration (hours pw) | No of weeks / Number of activity | Hours in total per term | | Yüz yüze eğitim | 3 | 14 | 42 | | Sınıf dışı çalışma | 8 | 14 | 112 | | Arasınav için hazırlık | 12 | 2 | 24 | | Arasınav | 2 | 1 | 2 | | Ödev | 3 | 2 | 6 | | Kısa sınav | 1 | 1 | 1 | | Dönem sonu sınavı için hazırlık | 12 | 3 | 36 | | Dönem sonu sınavı | 2 | 1 | 2 | | Total work load | | | 225 |
|