COURSE UNIT TITLE

: APPLIED ECONOMETRICS

DEGREE PROGRAMMES

Description of Individual Course Units

Course Unit Code Course Unit Title Type Of Course D U L ECTS
FIB 5117 APPLIED ECONOMETRICS ELECTIVE 3 0 0 6

Offered By

Financial Economics and Banking

Level of Course Unit

Second Cycle Programmes (Master's Degree)

Course Coordinator

PROFESSOR DOCTOR HAKAN KAHYAOĞLU

Offered to

Financial Economics and Banking

Course Objective

To test the economic models with the help of econometric methods whom are subject to economic theory and to make the stundet gain foresight and forecast ability that would give him/her self confidence.

Learning Outcomes of the Course Unit

1   To be able to distinguish econometric models
2   To be able to internalize and to explain the mathematical statistical techniques which is reference for econometric models in practice.
3   To be able to do hypothesis tests and to obtain parametrical predictors intended for economic models.
4   To be able to make prediction through parametrical predictors that were obtained from econometric models.
5   To be able to test the critics directed to econometric models through primary and secondary datas.

Mode of Delivery

Face -to- Face

Prerequisites and Co-requisites

None

Recomended Optional Programme Components

None

Course Contents

Week Subject Description
1 The effects of technological developments on econometrics and economics
2 Bivariate regression analysis and hypothesis tests
3 Multivariate time series analysis and interpretations
4 Basic econometric problems in multivariate analysis
5 Introduction to open access coded tools: R, Phyton, Julia
6 Practices about R, Phyton and Julia
7 Qualititive dependent variable models, practices of R, Phyton and Julia
8 Midterm
9 Dynamic econometric modelling, practices of R, Phyton and Julia
10 Simultaneous equations models,practices of R, Phyton and Julia
11 Introduction to time series analysis
12 Fundamental time series analysis (Unit root, cointegration and breaks)
13 Multivariate time series analysis (VAR and advanced time series)
14 Machine and deep learning in econometrics

Recomended or Required Reading

Main Sources / Assistant Sources:
- Gujarati, Damodar N. (1995), Basic Econometrics, 3rd Ed., Literatür Yay., Istanbul.
- Gujarati, Damodar N. (1999), Temel Ekonometri, Çev. Ümit Şenesen&Gülay Günlük Şenesen, Literatür Yay., Istanbul.
- A Koutsoyiannis, Econometrics,
-Enders, Walter (1995), Applied Econometric Time Series, John Wiley and Sons, USA.
- Uygur, Ercan (2001), Ekonometri: Yöntem ve Uygulama, Imaj Yay., Ankara.
- Ertek, Tümay (2005), Ekonometriye Giriş, 2. Baskı, Beta Yay., Istanbul.
-Tarı, Recep (2005), Ekonometri, 3. Baskı, Kocaeli Üniv. Yay. No. 172, Istanbul.
References: Economics and econometric modeling based (SSCI, Econlit vb.) publications.

Planned Learning Activities and Teaching Methods

As well as lecture and discussing about the facts, every subject will be supported by econometric applications suitable with the theoritical framework which is defined.

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

Presentations and written documents that include the learning objects mentioned above, verbal discussions during the lesson, and the evaluation of discussions about the applicable results within the group.

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)
Lecture 13 3 39
Weekly pre-class activities 13 2 26
Preparation to midterm 1 10 10
Preparation to final exam 1 15 15
Other 1 25 25
Preparing assignments 2 9 18
Mid Term 1 3 3
Final Exam 1 4 4
TOTAL WORKLOAD (hours) 140

Contribution of Learning Outcomes to Programme Outcomes

PO/LOPO.1PO.2PO.3PO.4PO.5PO.6PO.7PO.8PO.9
LO.135
LO.23445
LO.3443
LO.442
LO.5155

CONTACT INFORMATION
Dokuz Eylül Üniversitesi Cumhuriyet Bulvarı No: 144 35210 Alsancak / İZMİR
Phone: +90(232) 412 12 12 - Fax: +90 (232) 464 81 35

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