PAÜ .:. Eğitim Öğretim Bilgi Sistemi

COURSE INFORMATION

Course Code	Course Title	L+P Hour	Semester	ECTS
EKNM 309	ECONOMETRICS - I	4 + 0	5th Semester	5

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 the prerequisite of lesson.
Corequisite	No the corequisite of lesson.
Mode of Delivery	Face to Face

COURSE LEARNING OUTCOMES

COURSE'S CONTRIBUTION TO PROGRAM

	PO 01	PO 02	PO 03	PO 04	PO 05	PO 06	PO 07	PO 08	PO 09	PO 10	PO 11	PO 12
LO 001	4	4	4	4	4	4	4	4	4	4	4	4
Sub Total	4	4	4	4	4	4	4	4	4	4	4	4
Contribution	4	4	4	4	4	4	4	4	4	4	4	4

ECTS ALLOCATED BASED ON STUDENT WORKLOAD BY THE COURSE DESCRIPTION

Activities	Quantity	Duration (Hour)	Total Work Load (Hour)
Course Duration (14 weeks/theoric+practical)	13	3	39
Hours for off-the-classroom study (Pre-study, practice)	13	3	39
Assignments	2	13	26
Mid-terms	1	13	13
Final examination	1	13	13
Total Work Load ECTS Credit of the Course			130 5

COURSE DETAILS

Select Year

	Course Term	No	Instructors
Details	2020-2021 Fall	1	MEHMET İVRENDİ
Details	2020-2021 Fall	2	MEHMET İVRENDİ

Course Details

Course Code	Course Title	L+P Hour	Course Code	Language Of Instruction	Course Semester
EKNM 309	ECONOMETRICS - I	4 + 0	1	English	2020-2021 Fall

Course Coordinator	E-Mail	Phone Number	Course Location	Attendance
Prof. Dr. MEHMET İVRENDİ	mivrendi@pau.edu.tr		İİBF C0017	%

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

Topics

Weeks	Topics
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

Resources	Resources Language
Principles of Econometrics, Hill, Griffiths and Lim	English

Course Assessment

L+P: Lecture and Practice
PQ: Program Learning Outcomes
LO: Course Learning Outcomes

Prospective Student