1. SECOND CYCLE - MASTER'S DEGREE
  2. THE GRADUATE SCHOOL OF SOCIAL SCIENCES
  3. ECONOMICS DEPARTMENT
  4. 2201 ECONOMICS
Course Information Course Learning Outcomes Course's Contribution To Program ECTS Workload Course Details
Print

COURSE INFORMATION
Course CodeCourse TitleL+P HourSemesterECTS
IKT 507EKONOMETRICS3 + 01st Semester7,5

COURSE DESCRIPTION
Course Level Master's Degree
Course Type Elective
Course Objective The aim of this course is to present sufficienct theoretical background related to basic econometrics techniques and to be able to prepare independent research Project.
Course Content A review of some statistical concepts, classical regression model, finite sample properties and large sample properties of least square estimator, maximum likelihood estimation, hypothesis tests for regression models, autocorrelation, heteroscedasticity, instrumental variable estimation, GMM estimation, panel data, dynamic panel data model, systems of regression equations.
Prerequisites No the prerequisite of lesson.
Corequisite No the corequisite of lesson.
Mode of Delivery Face to Face

COURSE LEARNING OUTCOMES
1To be able to familiar with quidelines for econometric techniques.
2Developing proficiency in the use of packages for econometric modelling.

COURSE'S CONTRIBUTION TO PROGRAM
PO 01PO 02PO 03PO 04PO 05PO 06PO 07PO 08PO 09PO 10PO 11PO 12
LO 001555555555555
LO 002555555555555
Sub Total101010101010101010101010
Contribution555555555555

ECTS ALLOCATED BASED ON STUDENT WORKLOAD BY THE COURSE DESCRIPTION
ActivitiesQuantityDuration (Hour)Total Work Load (Hour)
Course Duration (14 weeks/theoric+practical)13565
Hours for off-the-classroom study (Pre-study, practice)13565
Assignments21326
Mid-terms11313
Final examination12626
Total Work Load

ECTS Credit of the Course





195

7,5
COURSE DETAILS
 Select Year   


 Course TermNoInstructors
Details 2020-2021 Fall1MEHMET İVRENDİ


Print

Course Details
Course Code Course Title L+P Hour Course Code Language Of Instruction Course Semester
IKT 507 EKONOMETRICS 3 + 0 1 Turkish 2020-2021 Fall
Course Coordinator  E-Mail  Phone Number  Course Location Attendance
Prof. Dr. MEHMET İVRENDİ mivrendi@pau.edu.tr İİBF A0201 %70
Goals The aim of this course is to present sufficienct theoretical background related to basic econometrics techniques and to be able to prepare independent research Project.
Content A review of some statistical concepts, classical regression model, finite sample properties and large sample properties of least square estimator, maximum likelihood estimation, hypothesis tests for regression models, autocorrelation, heteroscedasticity, instrumental variable estimation, GMM estimation, panel data, dynamic panel data model, systems of regression equations.
Topics
WeeksTopics
1
2
3
4
5
6
7
8
9
10
11
12
13
14
Materials
Materials are not specified.
Resources
ResourcesResources Language
1- R. Carter Hill, William E. Griffiths, Guay C. Lim (2018) Principles of Econometrics, 5th Edition. English
2- Jeffrey M. Wooldridge (2019) Ekonometriye Giriş , Nobel Akademik Yayıncılık Türkçe
3- Christopher F. Baum(2006) An Introduction to Modern Econometrics Using StataTürkçe
Course Assessment
Assesment MethodsPercentage (%)Assesment Methods Title
Final Exam50Final Exam
Midterm Exam50Midterm Exam
L+P: Lecture and Practice
PQ: Program Learning Outcomes
LO: Course Learning Outcomes