COURSE INFORMATION
Course CodeCourse TitleL+P HourSemesterECTS
EKNM 309ECONOMETRICS - I4 + 05th Semester5

COURSE DESCRIPTION
Course Level Bachelor's Degree
Course Type Compulsory
Course Objective The aim of the course is to measure quantitatively the relations between economic variables , to estimate parameters of the underlying model, to test hypotheses and to make forecast.
Course Content Simple regression model and OLS Estimate, Assumptions of Classical Linear Regression model, Interval estimate and hypothesis testing, Alternative Functional forms of regression models, Multivariate regression model and inference, Maximum likelihood method, structural stability tests , matrix approach to regression model
Prerequisites No prerequisites.
Corequisite No corequisites.
Mode of Delivery Face to face

COURSE LEARNING OUTCOMES
1-

COURSE'S CONTRIBUTION TO PROGRAM
PO 01PO 02PO 03PO 04PO 05PO 06PO 07PO 08PO 09PO 10PO 11PO 12
LO 01444444444444
Sub Total444444444444
Contribution444444444444

ECTS ALLOCATED BASED ON STUDENT WORKLOAD BY THE COURSE DESCRIPTION
ActivitiesQuantityDuration (Hour)Total Work Load (Hour)
Course Duration13339
Hours for off-the-classroom study (Pre-study, practice)13339
Assignments21326
Mid-terms11313
Final examination11313
Total Work Load

ECTS Credit of the Course






130

5

COURSE DETAILS
 Select Year   


 Course TermNoInstructors
Details 2019-2020 Fall1AYGÜL ANAVATAN
Details 2019-2020 Fall2AYGÜL ANAVATAN

Course Details
Course Code:  EKNM 309 Course Title:  ECONOMETRICS - I
L+P Hour : 4 + 0   Course Code : 1   Language Of Instruction: English Course Semester :  2019-2020 Fall
Course Coordinator :  ASSISTANT PROFESSOR AYGÜL ANAVATAN E-Mail:  , Phone Number :  296 2762,
Course Location İİBF B0213,
Goals : The aim of the course is to measure quantitatively the relations between economic variables , to estimate parameters of the underlying model, to test hypotheses and to make forecast.
Content : Simple regression model and OLS Estimate, Assumptions of Classical Linear Regression model, Interval estimate and hypothesis testing, Alternative Functional forms of regression models, Multivariate regression model and inference, Maximum likelihood method, structural stability tests , matrix approach to regression model
Attendance : %70
Topics
WeeksTopics
1 Single Equation Regression Models
2 Two variable regression analysis: some basic ideas
3 Two variable regression analysis: the problem of estimation
4 Classical Normal Linear Regression Model:Normality asumption
5 Maximum Likelihood Estimation and Method of Moment
6 Two-variable regression: Interval Estimation and Hypothesis Testing
7 Extensions of the two-variable Linear Regression Model
8 Econometric Applications
9 Multiple Regression Analysis: The Problem of Estimation
10 Multiple Regression Analysis: The Problem of Inference
11 Multiple Regression Analysis: The Problem of Inference
12 Matrice Method of Linear Regression Model
13 Relaxing the assumptions of the Classical Model
14 Multicollinearity
Materials
Materials are not specified.
Resources
ResourcesResources Language
Basic Econometrics, GujaratiEnglish
Principles of Econometrics, Hill, Griffiths and LimEnglish
Basic Econometrics, GujaratiEnglish
Principles of Econometrics, Hill, Griffiths and LimEnglish
Course Assessment
Assesment MethodsPercentage (%)Assesment Methods Title
Final Exam50Final Exam
Midterm Exam30Midterm Exam
Quiz20Quiz
L+P: Lecture and Practice
PQ: Program Learning Outcomes
LO: Course Learning Outcomes