ECTS - Econometrics I
Econometrics I (ECON301) Course Detail
| Course Name | Course Code | Season | Lecture Hours | Application Hours | Lab Hours | Credit | ECTS |
|---|---|---|---|---|---|---|---|
| Econometrics I | ECON301 | 5. 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 | The aim of this course is to introduce students to the study of econometrics, which deals with the application of statistical methods to test economic theory. Econometrics uses observational data to estimate economic relationships, test hypotheses about economic behaviour, and predict future values of economic variables. Software applications are introduced during the course in order to provide hands-on experience with data collection, analysis and interpretation. |
| Course Learning Outcomes |
The students who succeeded in this course;
|
| Course Content | Review of basic statistics; simple regression, tests of hypothesis; prediction; assessing goodness of fit; assumptions of the classical linear regression model; transformation of variables; estimation and inference in the multiple regression model. |
Weekly Subjects and Releated Preparation Studies
| Week | Subjects | Preparation |
|---|---|---|
| 1 | Review of Basic Statistics - Descriptive Statistics, Probability and Random variables; Introduction – The Methodology of Economics | Gujarati, Introduction: pp. 1-13 |
| 2 | The Nature of Regression Analysis – Causation, Correlation and Types of Data | Gujarati, Chapter 1: pp. 15-32 |
| 3 | Two Variable Regression Model: Some Basic Ideas | Gujarati, Chapter 2: ss. 37-52 |
| 4 | Two Variable Regression Model: The Problem of Estimation | Gujarati, Chapter 3: pp. 58-105 |
| 5 | Two Variable Regression Model: The Problem of Estimation | Gujarati, Chapter 3: pp. 58-105 |
| 6 | The Normality Assumption: Classical Normal Linear Regression Model | Gujarati, Chapter 4: pp. 107-113 |
| 7 | Two-Variable Regression Model: Interval Estimation and Hypothesis Testing | Gujarati, Chapter 5: pp. 119-133 |
| 8 | Two-Variable Regression Model: Interval Estimation and Hypothesis Testing | Gujarati, Chapter 5: pp. 134-150 |
| 9 | MIDTERM EXAM | |
| 10 | Introduction to Eviews | Class Handouts |
| 11 | Extensions of the Two-Variable Regression Model: Scaling, Functional Forms | Gujarati, Chapter 6: pp. 164-193 |
| 12 | Multiple Regression Model: The Problem of Estimation | Gujarati, Chapter 7: pp. 202-232 |
| 13 | Multiple Regression Model: The Problem of Inference | Gujarati, Chapter 8: pp. 248-263 |
| 14 | Multiple Regression Model: The Problem of Inference | Gujarati, Chapter 8: pp. 264-280 |
| 15 | General 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 | 30 |
| Final Exam/Final Jury | 1 | 45 |
| Toplam | 3 | 85 |
| Percentage of Semester Work | 55 |
|---|---|
| Percentage of Final Work | 45 |
| 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 | They acquire the skills to understand, explain, and use the basic concepts and methods of economics. | X | ||||
| 2 | Acquires macro-economic analysis skills. | X | ||||
| 3 | Acquire microeconomic analysis skills. | X | ||||
| 4 | Understands the formulation and implementation of economic policies at local, national, regional and/or global levels. | X | ||||
| 5 | Learn different approaches to the economy and economic issues. | X | ||||
| 6 | Learn qualitative and quantitative research techniques in economic analysis. | X | ||||
| 7 | Improving the ability to use modern software, hardware and/or other technological tools. | X | ||||
| 8 | Develops intra-disciplinary and inter-disciplinary team work skills. | X | ||||
| 9 | Contributes to open-mindedness by encouraging critical analysis, discussion, and/or lifelong learning. | X | ||||
| 10 | Develops a sense of work ethics and social responsibility. | X | ||||
| 11 | Develops communication skills. | X | ||||
| 12 | Improving the ability to effectively apply knowledge and skills in at least one of the following areas: Economic policy, public policy, international economic relations, industrial relations, monetary and financial relations | 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 | ||