ECTS - Econometrics II
Econometrics II (ECON302) Course Detail
| Course Name | Course Code | Season | Lecture Hours | Application Hours | Lab Hours | Credit | ECTS |
|---|---|---|---|---|---|---|---|
| Econometrics II | ECON302 | 6. Semester | 3 | 0 | 0 | 3 | 6 |
| Pre-requisite Course(s) |
|---|
| N/A |
| Course Language | English |
|---|---|
| Course Type | Compulsory Departmental Courses |
| Course Level | Bachelor’s Degree (First Cycle) |
| Mode of Delivery | Face To Face |
| Learning and Teaching Strategies | Lecture, Demonstration. |
| Course Lecturer(s) |
|
| Course Objectives | This course is a continuation of ECON 301, which set out the basic assumptions of the classical linear regression model (CLRM). The assumptions of the CLRM are usually not satisfied in econometric applications. This course will look at: the detection and consequences of violations of the CLRM including multicollinearity, heteroskedasticity, autocorrelation, and model misspecification, as well as a selection of further topics in econometrics including model specification, diagnostic testing. Applications to real world data are emphasized to illustrate the concepts introduced in the course |
| Course Learning Outcomes |
The students who succeeded in this course;
|
| Course Content | Review of regression and hypothesis testing; dummy variable regression models; multicollinearity; heteroskedasticity; autocorrelation; model misspecification; model selection criteria; outlier analysis. |
Weekly Subjects and Releated Preparation Studies
| Week | Subjects | Preparation |
|---|---|---|
| 1 | Review of material learned in ECON 301 | Class Handouts |
| 2 | Dummy Variable Regression Models | Gujarati, Chapter 9: pp. 297-309 |
| 3 | Special Applications of Dummy Variables | Gujarati, Chapter 9: pp. 310-323 |
| 4 | Nature and Consequences of Multicollinearity | Gujarati, Chapter 10: pp. 335-358 |
| 5 | Multicollinearity: Detection and Remedial Measures | Gujarati, Chapter 10: pp. 359-375 |
| 6 | EViews Applications | Class Handouts |
| 7 | MIDTERM EXAM | |
| 8 | Nature and Consequences of Heteroskedasticity | Gujarati, Chapter 11: pp. 387-400 |
| 9 | Heteroskedasticity: Detection and Remedial Measures | Gujarati, Chapter 11: pp. 400-428 |
| 10 | Nature and Consequences of Autocorrelation | Gujarati, Chapter 12: pp. 441-461 |
| 11 | Autocorrelation: Detection and Remedial Measures | Gujarati, Chapter 12: pp. 462-489 |
| 12 | Econometric Modeling: Model Misspecification, Model Selection Criteria | Gujarati, Chapter 13: pp. 506-529 |
| 13 | Econometric Modeling: Diagnostic Testing and Outlier Analysis | Gujarati, Chapter 13: pp. 530-547 |
| 14 | EViews Applications | Class Handouts |
| 15 | Review | |
| 16 | Final Exam |
Sources
| Course Book | 1. Gujarati, Damodar N. (2003) Basic Econometrics, 4th Edition, New York and Boston: McGraw-Hill |
|---|---|
| Other Sources | 2. Wooldridge, Jeffrey (2008) Introductory Econometrics: A Modern Approach (with Economic Applications), 4th Edition, Cengage Learning. |
| 3. Peter J. Kennedy (1998) A Guide to Econometrics, 4th Edition, MIT Press. | |
| 4. Ramanathan, R. (2002), Introductory Econometrics with Applications, 5th edition, Orlando, FL: Harcourt College Publishers. | |
| 5. Hill, R.C., Griffiths, W.E. and G. G. Judge (2001) Undergraduate Econometrics, 2nd Edition, John Wiley and Sons, Inc. | |
| 6. Hill, R.C., Griffiths, W.E. and G. G. Judge (2000) Using Eviews For Undergraduate Econometrics, 2nd Edition, Wiley. | |
| 7. Asteriou, D. (2006) Applied Econometrics: A Modern Approach using EViews and Microfit, Palgrave-Macmillan. |
Evaluation System
| Requirements | Number | Percentage of Grade |
|---|---|---|
| Attendance/Participation | 1 | 10 |
| Laboratory | - | - |
| Application | - | - |
| Field Work | - | - |
| Special Course Internship | - | - |
| Quizzes/Studio Critics | - | - |
| Homework Assignments | - | - |
| Presentation | - | - |
| Project | - | - |
| Report | - | - |
| Seminar | - | - |
| Midterms Exams/Midterms Jury | 1 | 40 |
| Final Exam/Final Jury | 1 | 50 |
| Toplam | 3 | 100 |
| Percentage of Semester Work | 70 |
|---|---|
| Percentage of Final Work | 30 |
| 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 | Acquiring the skills of understanding, explaining, and using the fundamental concepts and methods of economics | X | ||||
| 2 | Acquiring the skills of macro level economic analysis | X | ||||
| 3 | Acquiring the skills of micro level economic analysis | X | ||||
| 4 | Understanding the formulation and implementation of economic policies at the local, national, regional, and/or global level | X | ||||
| 5 | Learning different approaches on economic and related issues | X | ||||
| 6 | Acquiring the quantitative and/or qualitative techniques in economic analysis | X | ||||
| 7 | Improving the ability to use the modern software, hardware and/or technological devices | X | ||||
| 8 | Developing intra-disciplinary and inter-disciplinary team work skills | X | ||||
| 9 | Acquiring an open-minded behavior through encouraging critical analysis, discussions, and/or life-long learning | X | ||||
| 10 | Adopting work ethic and social responsibility | X | ||||
| 11 | Developing the skills of communication. | X | ||||
| 12 | Improving the ability to effectively implement the knowledge and skills in at least one of the following areas: economic policy, public policy, international economic relations, industrial relations, monetary and financial affairs. | X | ||||
ECTS/Workload Table
| Activities | Number | Duration (Hours) | Total Workload |
|---|---|---|---|
| Course Hours (Including Exam Week: 16 x Total Hours) | 16 | 3 | 48 |
| Laboratory | |||
| Application | |||
| Special Course Internship | |||
| Field Work | |||
| Study Hours Out of Class | 16 | 6 | 96 |
| Presentation/Seminar Prepration | |||
| Project | |||
| Report | |||
| Homework Assignments | |||
| Quizzes/Studio Critics | |||
| Prepration of Midterm Exams/Midterm Jury | 1 | 2 | 2 |
| Prepration of Final Exams/Final Jury | 1 | 2 | 2 |
| Total Workload | 148 | ||