COURSE UNIT TITLE

: MARITIME ECONOMETRICS I

DEGREE PROGRAMMES

Description of Individual Course Units

Course Unit Code Course Unit Title Type Of Course D U L ECTS
DIY 5055 MARITIME ECONOMETRICS I ELECTIVE 3 0 0 6

Offered By

Maritime Business Administration (English)

Level of Course Unit

Second Cycle Programmes (Master's Degree)

Course Coordinator

PROFESSOR DOCTOR SADIK ÖZLEN BAŞER

Offered to

Maritime Business Administration (English)

Course Objective

This lecture concerns with formulating and understanding an econometric model suitable to theory of economics for marine industries, especially in the concept of costs.

Learning Outcomes of the Course Unit

1   To be able to distinguish the difference between time and section data.
2   To learn how to form a suitable model with the suitable econometric method considering the maritime industry dynamics.
3   To be able to make econometrical estimates with economic maritime data.
4   To gain the ability to use econometric packaged software
5   To be able to identify the basic errors and to gain the ability to remove them

Mode of Delivery

Face -to- Face

Prerequisites and Co-requisites

None

Recomended Optional Programme Components

None

Course Contents

Week Subject Description
1 Usage of econometrics in maritime industry Presentation
2 Simple Linear Regression Model (Bivariate Regression Model) using maritime transportation data Presentation
3 Least Square Regression Model and its assumptions Presentation
4 Multivariate Regression Model Presentation
5 Hypothesis tests, Regression and analysis of Variance in maritime cases Presentation
6 Applications regarding Regression Models Presentation
7 Midterm exam
8 The other tests for econometrics models with single equation, selection of models criteria Presentation
9 Multicollinearity, estimations of Least Square Regression in case Multicollinearity, detecting and removing Multicollinearity, assumption of normality of errors Presentation
10 Heteroscedasticity, detecting Heteroscedasticity, estimations of Least Square Regression in case of Heteroscedasticity and consequences after Heteroscedasticity Presentation
11 Removing Heteroscedasticity Presentation
12 Autocorrelation, detecting Autocorrelation, estimations of Least Square Regression in case Autocorrelation and consequences after Autocorrelation Presentation
13 Removing Autocorrelation Presentation
14 Term Paper Presentations

Recomended or Required Reading

Washington, S., Karlaftis, M. and Mannering, F. Statistical and Economic Methods For Transportation Data Analysis 1st Ed, CRC Press, London 2003
Washington, S., Karlaftis, M. and Mannering, F. Statistical and Economic Methods For Transportation Data Analysis 2nd Ed, CRC Press, London 2011
Karakitsos, E. and Varnavides, L. Maritime Economics A Macroeconomic Approach 1st Ed. Palgrave Macmillan, UK 2014
Goodwin, E. and Kemp, J. Marine Statistics Theory and Practice 1st Ed, London 1979
Barda, Süleyman. Ulaştırma Ekonomisi Dersleri. Menteş Kitabevi : Istanbul 1982
Berg-Andreassen, Jan A. (1966) Some Properties of International Maritime Statistics. Maritime Policy and Management, 23 (4)
Buxton, I.L. Engineering Economics and Ship Design. The British Shipping Research Association : Wallsend 1971
Evans, J.J. ve Marlow, Peter. Quantative Methods in Maritime Economics. Fairplay Publications : London 1990

Planned Learning Activities and Teaching Methods

A number of applications and methods will be presented in the class that have broad applications to a variety of data-analysis in maritime economics and beyond. The material covered goes well beyond the techniques typically covered in statistics courses. While, the course will emphasize model estimation and application, the underlying theory and limitations will be discussed to ensure that the methods are properly applied and understood. The students will be able to apply the concepts learned in the class using real world data and will also learn econometric model development in softwares such as R, Matlab, Stata, Biogeme, Eviews, Limdep and SPSS.

Assessment Methods

SORTING NUMBER SHORT CODE LONG CODE FORMULA
1 MTE MIDTERM EXAM
2 STT TERM WORK (SEMESTER)
3 FCGR FINAL COURSE GRADE
4 FCGR FINAL COURSE GRADE (RESIT) MTE * 0.20 + STT * 0.20 + FN* 0.60
5 RST RESIT
6 FCGR FINAL COURSE GRADE (RESIT) MTE * 0.20 + STT * 0.20 + RST* 0.60


Further Notes About Assessment Methods

None

Assessment Criteria

Knowledge, skills and competencies in research, examination, critics, application and presentation of econometrics using maritime industry data.

Language of Instruction

English

Course Policies and Rules

To be announced.

Contact Details for the Lecturer(s)

Assoc.Prof.Dr. Sadık Özlen Başer

Office Hours

To be announced.

Work Placement(s)

None

Workload Calculation

Activities Number Time (hours) Total Work Load (hours)
Lectures 13 2 26
Tutorials 13 2 26
Preparations before/after weekly lectures 13 2 26
Preparation for midterm exam 1 15 15
Preparation for final exam 1 25 25
Preparing presentations 1 30 30
Final 1 1 1
Midterm 1 1 1
TOTAL WORKLOAD (hours) 150

Contribution of Learning Outcomes to Programme Outcomes

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LO.24554445444444
LO.34455454445444
LO.44545444444444
LO.54445444554445

CONTACT INFORMATION
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Phone: +90(232) 412 12 12 - Fax: +90 (232) 464 81 35

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