ECTS - Advance Data Modeling
Advance Data Modeling (ECON552) Course Detail
| Course Name | Course Code | Season | Lecture Hours | Application Hours | Lab Hours | Credit | ECTS |
|---|---|---|---|---|---|---|---|
| Advance Data Modeling | ECON552 | Area Elective | 3 | 0 | 0 | 3 | 5 |
| Pre-requisite Course(s) |
|---|
| N/A |
| Course Language | English |
|---|---|
| Course Type | Elective Courses |
| Course Level | Social Sciences Master's Degree |
| Mode of Delivery | Face To Face |
| Learning and Teaching Strategies | Lecture. |
| Course Lecturer(s) |
|
| Course Objectives | This course provides an understanding of the application of software technologies that enables users to make better and faster decisions based on various data. This course covers the statistical tools needed to understand empirical research and to plan and execute independent research projects. |
| Course Learning Outcomes |
The students who succeeded in this course;
|
| Course Content | Statistical inference, regression, generalized least squares, instrumental variables, simultaneous equations models, and evaluation of policies and programs. |
Weekly Subjects and Releated Preparation Studies
| Week | Subjects | Preparation |
|---|---|---|
| 1 | Single-Equation Regression Models Two-Variable Regression Model: The Problem of Estimation | DG and DCP Chp 1. |
| 2 | Classical Normal Linear Regression Model (CNLRM) | DG and DCP Chp 2-3. |
| 3 | Multiple Regression Analysis: The Problem of Inference | DG and DCP Chp 3-8. |
| 4 | The Matrix Approach to Linear Regression Model | JJ and JD Chp 3. |
| 5 | Relaxing the Assumptions of the Classical Model MIDTERM EXAM I | DG and DCP Chp 10-13. JJ and JD Chp 6. |
| 6 | Nonlinear Regression Models | DG and DCP Chp 14. |
| 7 | Qualitative Response Regression Models | DG and DCP Chp 15. JJ and JD Chp 13. |
| 8 | Panel Data Regression Models | DG and DCP Chp 16. JJ and JD Chp 12. |
| 9 | Dynamic Econometric Models: Autoregressive and Distributed-Lag Models | DG and DCP Chp 17. JJ and JD Chp 8. |
| 10 | Simultaneous-Equation Models | DG and DCP Chp 18-20. |
| 11 | Time Series Analysis | DG and DCP Chp 21-22. JJ and JD Chp 8-9. |
| 12 | Panel Time Series Models | SRP and AM |
| 13 | Nonlinear Modelling in Time and Panel data analysis | TT and GCEJ |
| 14 | FINAL EXAM |
Sources
| Course Book | 1. Domador Gujarati, Dawn C. Porter (2015) Introduction to Econometrics McGraw Hill Higher Education; 5th edition |
|---|---|
| 2. Jack Johnston and John Dinardo Econometric Methods. McGraw Hill Higher Education; 4th edition | |
| 3. Terasvirta T. and Granger C.E.J Modelling Nonlinear Economic Time Series | |
| 4. Smith R.P. and Fuertes A.M. Panel Time Series (2012) |
Evaluation System
| Requirements | Number | Percentage of Grade |
|---|---|---|
| Attendance/Participation | 14 | 10 |
| Laboratory | - | - |
| Application | - | - |
| Field Work | - | - |
| Special Course Internship | - | - |
| Quizzes/Studio Critics | - | - |
| Homework Assignments | - | - |
| Presentation | 2 | 20 |
| Project | - | - |
| Report | - | - |
| Seminar | - | - |
| Midterms Exams/Midterms Jury | 1 | 20 |
| Final Exam/Final Jury | 1 | 50 |
| Toplam | 18 | 100 |
| Percentage of Semester Work | |
|---|---|
| Percentage of Final Work | 100 |
| Total | 100 |
Course Category
| Core Courses | X |
|---|---|
| Major Area Courses | |
| Supportive Courses | |
| Media and Managment Skills Courses | |
| Transferable Skill Courses |
The Relation Between Course Learning Competencies and Program Qualifications
| # | Program Qualifications / Competencies | Level of Contribution | ||||
|---|---|---|---|---|---|---|
| 1 | 2 | 3 | 4 | 5 | ||
| 1 | To compare main microeconomic theories, approaches and make a critical evaluation of each | X | ||||
| 2 | To compare main macroeconomic theories, approaches and make a critical evaluation of each | X | ||||
| 3 | To apply mathematical modeling | X | ||||
| 4 | To employ statistical and econometric tools in analyzing an economic phenomena | X | ||||
| 5 | To analyze the main economic indicators and comment on them | X | ||||
| 6 | To acquire theoretical knowledge through literature survey and derive empirically confirmable hypothesis | X | ||||
| 7 | To make a research design and carry it out within predetermined time frames | X | ||||
| 8 | To be able to develop new approaches for complex problems in applied economics and/or apply statistical/econometric tools to new areas/problems | X | ||||
| 9 | To formulate and present policy recommendations based on academic research | X | ||||
| 10 | To combine economic knowledge with other disciplines in order to solve problems requiring scientific expertise | X | ||||
| 11 | To use information technology effectively | X | ||||
| 12 | To continue learning and undertake advanced research independently | X | ||||
ECTS/Workload Table
| Activities | Number | Duration (Hours) | Total Workload |
|---|---|---|---|
| Course Hours (Including Exam Week: 16 x Total Hours) | 14 | 3 | 42 |
| Laboratory | |||
| Application | |||
| Special Course Internship | |||
| Field Work | |||
| Study Hours Out of Class | 14 | 3 | 42 |
| Presentation/Seminar Prepration | 1 | 21 | 21 |
| Project | |||
| Report | |||
| Homework Assignments | |||
| Quizzes/Studio Critics | |||
| Prepration of Midterm Exams/Midterm Jury | 1 | 20 | 20 |
| Prepration of Final Exams/Final Jury | 1 | 25 | 25 |
| Total Workload | 150 | ||