COURSE UNIT TITLE

: TRANSPORT ECONOMETRICS II

Description of Individual Course Units

Course Unit Code Course Unit Title Type Of Course D U L ECTS
DLY 5026 TRANSPORT ECONOMETRICS II ELECTIVE 3 0 0 6

Offered By

Logistics Management

Level of Course Unit

Second Cycle Programmes (Master's Degree)

Course Coordinator

PROFESSOR DOCTOR SADIK ÖZLEN BAŞER

Offered to

Logistics Management

Course Objective

The objective is to provide students with a generic background in the application of various statistical and econometric analysis techniques and to provide new ideas for analyzing data in research. The course will present a number of model-estimation methods that are used in transportation data analysis and other subject areas that deal with data analysis.

Learning Outcomes of the Course Unit

1   statistical model development,
2   multinomial regression estimation with examining various properties,
3   cross-sectional and panel data analysis,
4   ordinary least squares and maximum likelihood estimation,
5   time series analysis,
6   cluster analysis,
7   simultaneous model estimation techniques,
8   discrete choice models

Mode of Delivery

Face -to- Face

Prerequisites and Co-requisites

None

Recomended Optional Programme Components

None

Course Contents

Week Subject Description
1 Course introduction; review of data and variable type and model building Presentation
2 Model definition Presentation
3 Dummy variables Presentation
4 Models with dependent dummy variable Presentation
5 Distributed lag models Presentation
6 Simultaneous equations models Presentation
7 Solution methods of Simultaneous equations models Presentation
8 Mid-term
9 Panel data methods Presentation
10 Tobit and Probit models Presentation
11 Time Series analysis Presentation
12 Time Series analysis Presentation
13 Seemingly unrelated regression models Presentation
14 Term Paper Presentations

Recomended or Required Reading

1. Washington, S., Karlaftis, M. and Mannering, F. Statistical and Economic Methods For Transportation Data Analysis 1st Ed, CRC Press, London 2003
2. Washington, S., Karlaftis, M. and Mannering, F. Statistical and Economic Methods For Transportation Data Analysis 2nd Ed, CRC Press, London 2011
3. Karakitsos, E. and Varnavides, L. Maritime Economics A Macroeconomic Approach 1st Ed. Palgrave Macmillan, UK 2014
4. Goodwin, E. and Kemp, J. Marine Statistics Theory and Practice 1st Ed, London 1979
5. Barda, Süleyman. Ulaştırma Ekonomisi Dersleri. Menteş Kitabevi : Istanbul 1982
6. Berg-Andreassen, Jan A. (1966) Some Properties of International Maritime Statistics. Maritime Policy and Management, 23 (4)
7. Norton, Hugh S. Modern Tranportation Economics Charles E. Merill Publishing Company : Ohiom 1971
8. 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 transportation engineering 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 transportation industry data.

Language of Instruction

Turkish

Course Policies and Rules

To be announced.

Contact Details for the Lecturer(s)

Doç. Dr. Hamdi EMEÇ

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 final exam 1 25 25
Preparing presentations 1 30 30
Preparation for midterm exam 1 15 15
Midterm 1 1 1
Final 1 1 1
TOTAL WORKLOAD (hours) 150

Contribution of Learning Outcomes to Programme Outcomes

PO/LOPO.1PO.2PO.3PO.4PO.5PO.6PO.7PO.8PO.9PO.10PO.11PO.12PO.13
LO.15544544445554
LO.24554445444444
LO.34455454445445
LO.44545444444444
LO.54445544554445
LO.64444455445444
LO.75444445554444
LO.84444444445545