Course Information
SemesterCourse Unit CodeCourse Unit TitleT+P+LCreditNumber of ECTS Credits
1ECON 501Research Methods and Publication Ethics3+0+038

Course Details
Language of Instruction English
Level of Course Unit Master's Degree
Department / Program MA Program in Economics (Thesis) (English)
Type of Program Formal Education
Type of Course Unit Compulsory
Course Delivery Method Face To Face
Objectives of the Course The course will guide the students to develop and write a research project proposal and then carry out a research project independently. It will also help them to develop a solid conceptual, philosophical and theoretical background in econometrics. Moreover, the students will be taught how to differentiate between different modelling strategies and estimation procedures, and which is the better one for a particular economic problem.
Course Content It is an introductory course focusing on basics of research and carrying out a research project in Economics. The main focus is on statistical and econometric techniques used for analysis of cross-sectional data. This course covers empirical analysis techniques used to investigate the relationships between financial and economic variables. Under this context, topics such as simple linear regression, multiple regression, dummy variables, heteroscedasticity, hypothesis testing, omitted variables and misspecification, asymptotic theory, measurement error and instrumental variables will be explained through empirical examples. In the content of the course, the model selection will be taught to make the best guess for the structure of the given data. Software programs, namely MS Excel, EViews and Stata, will be used during the course work.
Course Methods and Techniques
Prerequisites and co-requisities None
Course Coordinator Asist Prof.Dr. Asad ul Islam KHAN
Name of Lecturers Asist Prof.Dr. ASAD UL ISLAM KHAN
Assistants None
Work Placement(s) No

Recommended or Required Reading
Resources [CN]: Class Notes and Handouts
[IE]: Jeffrey M. Wooldridge, Introductory Econometrics: A Modern Approach, 6th ed., South Western, 2016.
Brooks, C. Introductory Econometrics for Finance, 3rd ed., 2014.
Brennan, N. M. (2019). 100 Research rules of the game: how to make your research world class; how to successfully publish in top international refereed journals. Accounting, Auditing & Accountability Journal, 32(2), 691-706.
Software programs, namely E-views and Stata, will be used during the course work.

Course Category
Mathematics and Basic Sciences %60
Social Sciences %20
Field %20

Planned Learning Activities and Teaching Methods
Activities are given in detail in the section of "Assessment Methods and Criteria" and "Workload Calculation"

Assessment Methods and Criteria
In-Term Studies Quantity Percentage
Mid-terms 1 % 30
Project 1 % 30
Final examination 1 % 40
Total
3
% 100

 
ECTS Allocated Based on Student Workload
Activities Quantity Duration Total Work Load
Course Duration 14 3 42
Hours for off-the-c.r.stud 14 6 84
Assignments 1 22 22
Mid-terms 1 3 3
Laboratory 14 3 42
Project 1 44 44
Final examination 1 3 3
Total Work Load   Number of ECTS Credits 8 240

Course Learning Outcomes: Upon the successful completion of this course, students will be able to:
NoLearning Outcomes
1 To provide tools that help to learn the characteristics of research methods and its usage in economic modelling
2 To construct the differences between alternative statistical models and conventional econometric models based on causal relationships
3 To improve competency in selecting the most appropriate modeling approach and to interpret basic econometric models based on economic theory
4 To develop and write a complete research project proposal and carry out a complete research project


Weekly Detailed Course Contents
WeekTopicsStudy MaterialsMaterials
1 Basics of Research & Steps in carrying out a Research Project-I IE Ch 1 & 19, CN
2 Basics of Research & Steps in carrying out a Research Project-II IE Ch 1 & 19, CN
3 Simple Linear Regression Model IE Ch 2, CN
4 Multiple Regression Analysis: Estimation IE Ch 3, CN
5 Multiple Regression Analysis: Inference IE Ch 4, CN
6 Multiple Regression Analysis: OLS Asymptotics IE Ch 5, CN
7 Multiple Regression Analysis: Further Issues IE Ch 6, CN
8 Mid Term Exam Lec #1 to Lec#7
9 Multiple Regression Analysis: Qualitative Information IE Ch 7, CN
10 Heteroskedasticity & More on Specification (Model Selection) and Data Issues IE Ch 8-9, CN
11 Instrumental Variables Estimation and Two Stage Least Squares IE Ch 15, CN
12 Simultaneous Equations Models-I IE Ch 16, CN
13 Simultaneous Equations Models-II IE Ch 16, CN
14 Limited Dependent Variable Models IE Ch 17, CN


Contribution of Learning Outcomes to Programme Outcomes
P1 P2 P3 P4 P5 P6 P7 P8
All 5 4 5 4 5 3 5
C1 5 4 5 5 5 5
C2 5 4 5 5 5 3 5
C3 5 4 5 5 5 2 5
C4 5 4 5 5 5 3 5

Contribution: 1: Very Slight 2:Slight 3:Moderate 4:Significant 5:Very Significant


https://obs.ihu.edu.tr/oibs/bologna/progCourseDetails.aspx?curCourse=248707&lang=en