PAÜ .:. Eğitim Öğretim Bilgi Sistemi

COURSE INFORMATION

Course Code	Course Title	L+P Hour	Semester	ECTS
EKNM 404	ECONOMETRICS - IV	3 + 0	6th Semester	5

COURSE DESCRIPTION

Course Level	Bachelor's Degree
Course Type	Elective
Course Objective	In the course the students should study traditional econometric methods developed mostly for the work with cross-sections data. At the same time the students should understand essential differences between the time series and cross sections data and those specific econometric problems met in the work with these types of data.
Course Content	Proposals and notation in CLRM. CLRM Estimation using Ordinary Least Squares (OLS). Expressions for the OLS estimators of slope coefficient and intercept: derivation and interpretation. Gauss-Markov conditions and the properties of OLS estimators. Gauss-Markov theorem (formulation). Standard deviations and standard errors of regression coefficients: derivation and interpretation. Statistical significance of OLS estimators: hypotheses testing using t-tests. Derivation and interpretation of confidence intervals. The general quality of regression: determination coefficient R2. F-statistics and F-tests. Relationship of R2 with correlation coefficients. .
Prerequisites	No the prerequisite of lesson.
Corequisite	No the corequisite of lesson.
Mode of Delivery	Face to Face

COURSE LEARNING OUTCOMES

1	specification of an adequate regression model and making parameter estimate
2	Making statistical inference
3	Choosing the best model
4	Diagnostic checking of the model
5	Using the econometrics software
6	Making prediction and forecast
7	Using the model for control and policy purposes

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	5	5	5	5	5	5	5	5	5	5	5	5
LO 002	5	5	5	5	5	5	5	5	5	5	5	5
LO 003	5	5	5	5	5	5	5	5	5	5	5	5
LO 004	5	5	5	5	5	5	5	5	5	5	5	5
LO 005	5	5	5	5	5	5	5	5	5	5	5	5
LO 006	5	5	5	5	5	5	5	5	5	5	5	5
LO 007	4	4	4	4	4	4	4	4	4	4	4	4
Sub Total	34	34	34	34	34	34	34	34	34	34	34	34
Contribution	5	5	5	5	5	5	5	5	5	5	5	5

ECTS ALLOCATED BASED ON STUDENT WORKLOAD BY THE COURSE DESCRIPTION

Activities	Quantity	Duration (Hour)	Total Work Load (Hour)
Course Duration (14 weeks/theoric+practical)	14	3	42
Hours for off-the-classroom study (Pre-study, practice)	14	4	56
Mid-terms	1	15	15
Final examination	1	17	17
Total Work Load ECTS Credit of the Course			130 5

COURSE DETAILS

Select Year

	Course Term	No	Instructors
Details	2019-2020 Spring	1	AYGÜL ANAVATAN
Details	2019-2020 Spring	1	SİNEM GÜLER KANGALLI UYAR

Course Details

Course Code	Course Title	L+P Hour	Course Code	Language Of Instruction	Course Semester
EKNM 404	ECONOMETRICS - IV	3 + 0	1	Turkish	2019-2020 Spring

Course Coordinator	E-Mail	Phone Number	Course Location	Attendance
Assoc. Prof. Dr. AYGÜL ANAVATAN	aanavatan@pau.edu.tr		İİBF B0213 İİBF B0214	%70

Goals		In the course the students should study traditional econometric methods developed mostly for the work with cross-sections data. At the same time the students should understand essential differences between the time series and cross sections data and those specific econometric problems met in the work with these types of data.
Content		Proposals and notation in CLRM. CLRM Estimation using Ordinary Least Squares (OLS). Expressions for the OLS estimators of slope coefficient and intercept: derivation and interpretation. Gauss-Markov conditions and the properties of OLS estimators. Gauss-Markov theorem (formulation). Standard deviations and standard errors of regression coefficients: derivation and interpretation. Statistical significance of OLS estimators: hypotheses testing using t-tests. Derivation and interpretation of confidence intervals. The general quality of regression: determination coefficient R2. F-statistics and F-tests. Relationship of R2 with correlation coefficients. .

Topics

Weeks	Topics
1	Heteroscedasticity
2	Serial correlation
3	Introduction to time series analysis
4	Unit root analysis
5	Co-integration
6	Vector error correction model
7	Midterm exam
8	Causality analysis
9	VAR analysis
10	Endogeneity problem
11	GMM estimator
12	Introduction to panel data analysis
13	Fixed and random effects models
14	Non-stationary panel data analysis

Materials

Materials are not specified.

Resources

Resources	Resources Language
Baltagi, Panel Data Econometrics, 5th edition, 2008.	English
Johnston and Dinardo, Econometric Methods, 4th edition, 1997.	English
Baltagi, Panel Data Econometrics, 5th edition, 2008.	English
Johnston and Dinardo, Econometric Methods, 4th edition, 1997.	English

Course Assessment

Assesment Methods	Percentage (%)	Assesment Methods Title
Final Exam	60	Final Exam
Midterm Exam	40	Midterm Exam

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

Prospective Student