COURSE UNIT TITLE

: APPLIED ECONOMETRICS I

Description of Individual Course Units

Course Unit Code Course Unit Title Type Of Course D U L ECTS
IKT 5116 APPLIED ECONOMETRICS I ELECTIVE 3 0 0 5

Offered By

Economics

Level of Course Unit

Second Cycle Programmes (Master's Degree)

Course Coordinator

PROFESSOR DOCTOR UTKU UTKULU

Offered to

Economics

Course Objective

This course is subject to econometric modells of macroeconomic time series at the graduate level. Within this framework, this course emphasis on the primary concept of econometric modeling.

Learning Outcomes of the Course Unit

1   To be able to understand the relation between science of economics and econometrics.
2   To be able to generate econometric models on the basis of economic theory
3   To be able to make theoretic and empiric econometric models of non-stationary macro economic time series
4   To be able to establish and interpret the existence of causality
5   To be able to use the results of econometric modeling at the economic theory forecasting.
6   To be able to learn ethical rules, research techniques and academic study while submitting their seminar presentation and article format projects.

Mode of Delivery

Face -to- Face

Prerequisites and Co-requisites

None

Recomended Optional Programme Components

None

Course Contents

Week Subject Description
1 Economics and Econometric Analysis
2 Time Series Modelling
3 Stationary problem of the time series and spurious regression
4 Using econometric models for forecasting of economic policy: Lucas critique and structural change
5 Long Run, economics theory, cointegration and economic modelling of the nonstationary time sereies
6 Cointegration: Single Equation Approach and Engle-Granger Modelling Methodology
7 Causality, endogeneity problem and short run error correction mechanism
8 Application: Unit root tests without structural breaks (ADF,KPSS,PP,ERS) and seasonal unit root tests ( HEGY,DHF)
9 Application: Conintegration tests without structural breaks, Engle-Granger, Dynamic Ordinary Least Squares (DOLS) and ARDL method
10 Application: Causality tests (Granger, Toda Yamamato), Two Stage Least Squares (Midterm exam will be held in this week except the course hour)
11 Application: Unit root test with one break (Zivot-Andrews, Perron) and Cointegration test with one break ((Gregory-Hansen)
12 Application: Unit root test with two breaks (Lee-Strazicich, Lumsdaine Papell) and Cointegration test with two breaks (Hatemi-J)
13 Application: Fractional unit root test and cointegration method (GPH,Robinson,EML,McLeod)
14 Application: Nonlinearity test: Keenan test, Terasvirta test, Tsay test , Linearity LR-testi, BDS

Recomended or Required Reading

ENGLE, Robert F. and Clive W. J. GRANGER; (1987), "Co-Integration and Error Correction: Representation, Estimation and Testing",Econometrica, 55(2), ss. 251-276.
ENDERS, Walter. Applied Econometric Time Series. John Wiley, New York, 1995.
GREGORY, A.W. and B. E. HANSEN, Residual-based Tests for Cointegration in Models with Regime Shifts, Journal of Econometrics, 1996, (70), 99 126.
HATEMI-J, Abdulnasser; (2008), Tests for Cointegration with Two Unknown Regime Shifts with an Application to Financial Market Integration , Empirical Economics, 35 (3), ss. 497-505.
UTKULU, Utku. Et al. The External Debt, Private Investment And Growth: The Long-Run Evıdence With Fractional Cointegration . International Conference on Business, Economics and Management, Yasar University, Izmir Turkey, 16-18 June 2005.

Planned Learning Activities and Teaching Methods

Methods of the course consist of not only theoretical and methodological contributions at the classroom, but also applications will be done at the laboratory.

Assessment Methods

SORTING NUMBER SHORT CODE LONG CODE FORMULA
1 MTE MIDTERM EXAM
2 STT TERM WORK (SEMESTER)
3 FIN FINAL EXAM
4 FCG FINAL COURSE GRADE MTE * 0.30 + STT * 0.30 + FIN* 0.40
5 RST RESIT
6 FCGR FINAL COURSE GRADE (RESIT) MTE * 0.30 + STT * 0.30 + RST* 0.40


*** Resit Exam is Not Administered in Institutions Where Resit is not Applicable.

Further Notes About Assessment Methods

Presentation and arguing given research projects.

Assessment Criteria

Students performance in the all learning outcomes are measured with mid-term exam, final exam and presentations.

Language of Instruction

Turkish

Course Policies and Rules

Attendance is compulsory and students are expected to bring course syllabus with them.

Contact Details for the Lecturer(s)

E-mail: utku.utkulu@deu.edu.tr

Office Hours

Thursdays, 14:00-15:00

Work Placement(s)

None

Workload Calculation

Activities Number Time (hours) Total Work Load (hours)
Tutorials 3 3 9
Lectures 14 3 42
Preparations before/after weekly lectures 13 2 26
Preparation for final exam 1 30 30
Reading 1 15 15
Preparation for midterm exam 1 10 10
Midterm 1 2 2
Final 1 2 2
TOTAL WORKLOAD (hours) 136

Contribution of Learning Outcomes to Programme Outcomes

PO/LOPO.1PO.2PO.3PO.4PO.5PO.6PO.7PO.8PO.9
LO.1545
LO.243
LO.3454
LO.4344
LO.52
LO.6355