ISTINYE UNIVERSITY BİLGİ PAKETİ / DERS KATALOĞU
Course Introduction and Application Information
| Course Code: | ECO208 | ||||
| Course Name: | Econometrics | ||||
| Semester: | Fall | ||||
| Course Credits: |
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| Language of instruction: | English | ||||
| Course Condition: | |||||
| Does the Course Require Work Experience?: | No | ||||
| Type of course: | Compulsory Courses | ||||
| Course Level: |
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| Mode of Delivery: | Face to face | ||||
| Course Coordinator: | Dr. Öğr. Üy. İLAYDA İSABETLİ FİDAN | ||||
| Course Lecturer(s): | İlayda İsabetli Fidan | ||||
| Course Assistants: |
Course Objective and Content
| Course Objectives: | 1) Providing students to understand economic relations with econometric techniques using different types of datasets. 2) Teaching how to use econometric methods to create answers for problems in various research agendas. 3) Teaching to be critical while approaching to economic problems. 4) Teaching to make theoretical knowledge an econometric model. |
| Course Content: | As an introduction to econometrics, this course includes theoretical and applied exercises. The course will begin with an introduction to econometrics with the background of statistical and mathematical methods, and continue with regression analysis, hypothesis testing, time series and panel data models. All steps will be shown with econometrics softwares, Eviews and Stata. Additionally, latest articles on econometrics will be followed and discussed in this course. |
Learning Outcomes
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The students who have succeeded in this course;
1) Make the data suitable for statistical and econometric analyses. 2) Build econometric models that explain the mechanisms forming the relations between variables. 3) Interpret the results obtained through econometric analyses. 4) Use E-views and Stata softwares for statistical and econometric analysis. |
Course Flow Plan
| Week | Subject | Related Preparation |
| 1) | Introduction to Econometrics | |
| 2) | Mathematical and Statistical Methods | |
| 3) | Introduction to Econometrics Softwares (Eviews, Stata, SPSS) | |
| 4) | Regression Analysis and OLS | |
| 5) | Using Regression Analysis-Applied | |
| 6) | Classical Model and Assumptions | |
| 7) | MIDTERM | |
| 8) | Hypothesis Testing | |
| 9) | Choosing the Independent Variable | |
| 10) | Choosing the Functional Form | |
| 11) | Multicollinearity | |
| 12) | Serial Correlation | |
| 13) | Project 1 (Time Series) | |
| 14) | Project 2 (Time Series) |
Sources
| Course Notes / Textbooks: | • Using Econometrics a Practical Guide, A.H. Studendmund - Sixth Edition 2014, Pearson |
| References: | • Örneklerle Ekonometri, Domadar Gujarati - 2015 Macmillan • Ekonometri – Stata Uygulamalı, Ferda Yerdelen Tatoğlu, 2020, Beta |
Course - Program Learning Outcome Relationship
| Course Learning Outcomes | 1 |
2 |
3 |
4 |
|---|---|---|---|---|
| Program Outcomes |
Course - Learning Outcome Relationship
| No Effect | 1 Lowest | 2 Average | 3 Highest |
| Program Outcomes | Level of Contribution |
Assessment & Grading
| Semester Requirements | Number of Activities | Level of Contribution |
| Homework Assignments | 6 | % 30 |
| Midterms | 1 | % 30 |
| Final | 1 | % 40 |
| total | % 100 | |
| PERCENTAGE OF SEMESTER WORK | % 60 | |
| PERCENTAGE OF FINAL WORK | % 40 | |
| total | % 100 | |
Workload and ECTS Credit Calculation
| Activities | Number of Activities | Preparation for the Activity | Spent for the Activity Itself | Completing the Activity Requirements | Workload | ||
| Course Hours | 14 | 1 | 3 | 56 | |||
| Application | 14 | 1 | 1 | 28 | |||
| Homework Assignments | 6 | 5 | 1 | 36 | |||
| Midterms | 1 | 15 | 1 | 16 | |||
| Final | 1 | 20 | 1 | 21 | |||
| Total Workload | 157 | ||||||