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Description of Individual Course Units

Course Unit Code Course Unit Title Type Of Course D U L ECTS IKT 5131 APPLIED ECONOMETRICS I ELECTIVE 3 0 0 6

Offered By

Economics

Level of Course Unit

Second Cycle Programmes (Master's Degree)

Course Coordinator

PROFESSOR DOCTOR RECEP KÖK

Offered to

Economics

Course Objective

To enable student to learn the analytical techniques to develop ability of prediction and forecasting in terms of the theoretical planks.

Learning Outcomes of the Course Unit

1   To be able to analyze economic models and econometric models 2   To be able to learn the techniques of mathematical statistics with reference to econometric modelling 3   To be able to make hypothesis tests for the economic models and obtaining the parametric estimators. 4   To be able to predict the parametric estimators 5   To be able test the primary and secondary data of econometric models

Mode of Delivery

Face -to- Face

Prerequisites and Co-requisites

None

Recomended Optional Programme Components

None

Course Contents

Week Subject Description 1 Introduction to econometric programmes 2 Bivariate regression analysis 3 Hypothesis Tests 4 Multivariate regresson analysis 5 Multivariate regression analysis: Examining the results 6 Multiple Variance and endogeneity 7 Econometric modelling 8 Qualitative dependent variable models 9 Qualitative dependent variable models 10 Dynamic econometric modelling 11 Spontaneous equation models 12 Spontaneous equation models 13 Introduction to time series analysis 14 Introduction to time series analysis

Recomended or Required Reading

- Gujarati, Damodar, 1995, Basic Econometrics - Gujarati, Damodar, 1999, Temel Ekonometri - Koutsoyiannis, Econometrics - Enders, Walter, 1995, Applied Econometrics - Uygur, Ercan, 2001, Ekonometri: Yöntem ve Uygulama - Ertek, Tümay, 2005, Ekonometriye Giriş - Tan, Recep, 2005, Ekonometri

Planned Learning Activities and Teaching Methods

Expressions as well as classroom lessons and discussions about the cases, in accordance with the theoretical framework will be supported by each topic in computer applicatons in econometrics.

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

None

Assessment Criteria

To be announced.

Language of Instruction

Turkish

Course Policies and Rules

To be announced.

Contact Details for the Lecturer(s)

recep.kok@deu.edu.tr

Office Hours

To be announced.

Work Placement(s)

None

Workload Calculation

Activities Number Time (hours) Total Work Load (hours) Lectures 13 3 39 Weekly preparations 13 2 26 Midterm preparations 1 10 10 Final preparations 1 15 15 Preparation for the presentation 2 8 16 Readings 1 25 25 Homeworks 1 15 15 Final 1 4 4 Mid term 1 3 3 TOTAL WORKLOAD (hours) 153

Contribution of Learning Outcomes to Programme Outcomes

PO/LO PO.1 PO.2 PO.3 PO.4 PO.5 PO.6 PO.7 PO.8 PO.9 LO.1 5 LO.2 4 LO.3 5 LO.4 3 LO.5 4