Course Information


Course Information
Course Title Code Semester L+U Hour Credits ECTS
ECONOMETRICS I ECO321 5. Semester 3 + 0 3.0 6.0

Prerequisites None

Language of Instruction English
Course Level Bachelor's Degree
Course Type Compulsory
Mode of delivery
Course Coordinator
Instructors Abdullah Selim ÖZTEK
Assistants
Goals This subject aims at giving students basic understanding of econometrics theories and applying econometric techniques to specific empirical economic problems. Numerous examples are examined to achieve this goal. Emphasis is placed on the classical linear model, least-squares estimation, hypothesis testing, and model building. Econometric models are then adopted to analyze practical problems and make forecasts. Furthermore, students are trained in this subject to use computer statistics software.
Course Content This subject aims at giving students basic understanding of econometrics theories and applying econometric techniques to specific empirical economic problems. Numerous examples are examined to achieve this goal. Emphasis is placed on the classical linear model, least-squares estimation, hypothesis testing, and model building. Econometric models are then adopted to analyze practical problems and make forecasts. Furthermore, students are trained in this subject to use computer statistics software.
Learning Outcomes 1) Understands the assumptions of Least Squares (OLS) and similar estimation methods.
2) To be able to determine whether the models estimated with OLS provide basic assumptions and solve problems.
3) Formulate, test and evaluate simple regression models

Weekly Topics (Content)
Week Topics Teaching and Learning Methods and Techniques Study Materials
1. Week Introduction Lecture; Question Answer
Brainstorming
Project Based Learning 		Homework
2. Week Econometric Models: Definitions, Aims and Estimation Problem Lecture; Question Answer
Brainstorming
Project Based Learning 		Homework
3. Week Explanations about statistical concepts and methods Lecture; Question Answer
Brainstorming
Project Based Learning 		Homework
4. Week The Regression Model and the Ordinary Least Squares Method Lecture; Question Answer
Brainstorming
Project Based Learning 		Homework
5. Week The Classical Regression Model: Estimation, Properties and Inference Lecture; Question Answer
Brainstorming
Project Based Learning 		Homework
6. Week Hypothesis Testing - Simple hypothesis test Lecture; Question Answer
Brainstorming
Project Based Learning 		Homework
7. Week Hypothesis Testing - Joint Hypotheses Lecture; Question Answer
Brainstorming
 Homework
8. Week Extension of The Linear Regression Model Lecture; Question Answer
Brainstorming
Project Based Learning 		Homework
9. Week The Restriction Effect, Functional Form and Specification Lecture; Question Answer
Brainstorming
Project Based Learning 		Homework
10. Week Dummy Variables Lecture; Question Answer
Brainstorming
Project Based Learning 		Homework
11. Week Autocorrelation Lecture; Question Answer
Brainstorming
Project Based Learning 		Homework
12. Week Autocorrelation Lecture; Question Answer
Brainstorming
Project Based Learning 		Homework
13. Week Heteroscedasticity Lecture; Question Answer
Brainstorming
Project Based Learning 		Homework
14. Week Simultaneous Equations Lecture; Question Answer
Brainstorming
Project Based Learning 		Homework

Sources Used in This Course
Recommended Sources
J. M. Wooldridge, (2013) Introductory Econometrics, Thomson-Southwestern Pub.; Çevirisi Ekonometriye Giriş: Modern Yaklaşım, Nobel Yayınevi, Çeviri Editörü Ebru Çağlayan D.N. Gujarati, (2004) Basic Econometrics, McGraw Hill pub. Önceki baskısının çevirisi Temel Ekonometri, Damodar N. Gujarati, Çeviri: Ümit Şenesen, Gülay Günlük Şenesen, Literatür Yayınları, İstanbul, 2001. Verbeek, M, (2000), A guide to Modern Econometrics, Wiley. C. Heij, Boer, P., Franses, P.H., Kloek, T., ve Dijk H.K. (2004) Econometric Methods with Application in Business and Economics, Oxford Uni. Press. W. Greene, (2000) Econometric Analysis, Prentice Hall. J. Johnston ve J. Dinardo, (1997) Econometric Methods, 4.ed., McGraw Hill.

Relations with Education Attainment Program Course Competencies
Program RequirementsContribution LevelDK1DK2DK3
PY15000
PY25000
PY35000
PY45555

*DK = Course's Contrubution.
0 1 2 3 4 5
Level of contribution None Very Low Low Fair High Very High
.

ECTS credits and course workload
Event Quantity Duration (Hour) Total Workload (Hour)
Course Duration (Total weeks*Hours per week) 14 3
Work Hour outside Classroom (Preparation, strengthening) 14 6
Homework 14 1
Midterm Exam 1 1
Time to prepare for Midterm Exam 1 10
Final Exam 1 1
Time to prepare for Final Exam 1 20
Total Workload
Total Workload / 30 (s)
ECTS Credit of the Course
Quick Access Hızlı Erişim Genişlet
Course Information
  • Course Information
  • Weekly Topics (Content)
  • Sources Used in This Course
  • Relations with Education Attainment Program Course Competencies
  • ECTS credits and course workload