| Course Name | Econometrics |
| Code | Semester | Theory (hour/week) | Application/Lab (hour/week) | Local Credits | ECTS |
|---|---|---|---|---|---|
| ECON 576 | Fall/Spring | 0 | 0 | 3 | 7.5 |
| Prerequisites | None | |||||
| Course Language | English | |||||
| Course Type | Elective | |||||
| Course Level | Second Cycle | |||||
| Mode of Delivery | - | |||||
| Teaching Methods and Techniques of the Course | ||||||
| Course Coordinator | ||||||
| Course Lecturer(s) | ||||||
| Assistant(s) | - | |||||
| Course Objectives | |
| Learning Outcomes | The students who succeeded in this course;
|
| Course Description | This course begins with the traditional econometric methods of matrix regression and general regression theory as well as the traditional understanding of econometric modeling. Additional topics include linear regression analysis, the least squares method, the ML estimator, univariate time series model, autoregressive moving average (ARIMA) modeling, BoxJenkins hashing, deterministic and stochastic trends, differential equations, nonstationary, seasonality, volatility, trends and transformations, multiequation timeseries models, cointegration and errorcorrection models, Logit, Probit and Tobit models, system models, and SUR, VAR, and panel data models. |
| Related Sustainable Development Goals | |
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| Core Courses | |
| Major Area Courses | ||
| Supportive Courses | ||
| Media and Managment Skills Courses | ||
| Transferable Skill Courses |
| Week | Subjects | Required Materials |
| 1 | Introduction and Mathematical background | Grene Ch. 1 |
| 2 | The Classical Multiple Linear Regression Model & Least Squares | Grene Ch. 2&3 |
| 3 | The Classical Multiple Linear Regression Model & Least Squares | Grene Ch. 2&3 |
| 4 | Functional Form and Structural Change | Grene Ch. 7 |
| 5 | Generalized regression model: heteroskedasticity | Grene Ch. 11 |
| 6 | Generalized regression model: serial correlation | Grene Ch. 12 |
| 7 | Models for Panel Data | Grene Ch. 13 |
| 8 | Systems of Regression Equations & Simultaneous-Equations Models | Grene Ch. 14&15 |
| 9 | Systems of Regression Equations & Simultaneous-Equations Models | Grene Ch. 14&15 |
| 10 | Time Series Models | Grene Ch. 20 |
| 11 | Time Series Models: Nonstationarity and Cointegration | Grene Ch. 20 |
| 12 | Time Series Models: Nonstationarity and Cointegration | Grene Ch. 20 |
| 13 | Models for Discrete Choice | Grene Ch. 21 |
| 14 | Models for Discrete Choice | Grene Ch. 21 |
| 15 | Review of the Semester | |
| 16 | Review of the Semester |
| Course Notes/Textbooks | Greene Econometrics |
| Suggested Readings/Materials |
| Semester Activities | Number | Weigthing |
| Participation | ||
| Laboratory / Application | ||
| Field Work | ||
| Quizzes / Studio Critiques | ||
| Portfolio | ||
| Homework / Assignments | 1 | 40 |
| Presentation / Jury | 1 | 30 |
| Project | ||
| Seminar / Workshop | ||
| Oral Exam | ||
| Midterm | 1 | 30 |
| Final Exam | ||
| Total |
| Weighting of Semester Activities on the Final Grade | 3 | 100 |
| Weighting of End-of-Semester Activities on the Final Grade | ||
| Total |
| Semester Activities | Number | Duration (Hours) | Workload |
|---|---|---|---|
| Course Hours (Including exam week: 16 x total hours) | 16 | 3 | 48 |
| Laboratory / Application Hours (Including exam week: 16 x total hours) | 16 | ||
| Study Hours Out of Class | 16 | 6 | 96 |
| Field Work | |||
| Quizzes / Studio Critiques | |||
| Portfolio | |||
| Homework / Assignments | 1 | 30 | |
| Presentation / Jury | 1 | 20 | |
| Project | |||
| Seminar / Workshop | |||
| Oral Exam | |||
| Midterms | 1 | 20 | |
| Final Exams | |||
| Total | 214 |
| # | Program Competencies/Outcomes | * Contribution Level | ||||
1 | 2 | 3 | 4 | 5 | ||
| 1 | To improve and deepen expertise in economics and finance. | X | ||||
| 2 | To be able to comprehend the interaction between economics, finance and related fields. | X | ||||
| 3 | To be able to apply the advanced level knowledge acquired in economics and finance. | X | ||||
| 4 | To be able to create new knowledge by combining the knowledge of finance and economics with the knowledge coming from other disciplines and be able to solve problems which requires expert knowledge by applying scientific methods. | X | ||||
| 5 | To be able to use computer programs needed in the fields of economics and finance as well as information and communication technologies in advanced levels. | X | ||||
| 6 | To be able to think analytically to identify problems in finance and economics and to be able to make policy recommendations in economics and finance based on scientific analysis of issues and problems. | X | ||||
| 7 | To be able to develop new strategic approaches for unexpected, complicated situations in finance and economics and take responsibility in solving it. | X | ||||
| 8 | To protect the social, scientific and ethical values at the data collection, interpretation and dissemination stages and to be able to institute and observe these values. | X | ||||
| 9 | To be able to critically evaluate the knowledge in finance and economics, to lead learning and carry out advanced level research independently. | X | ||||
| 10 | To be able to use a foreign language for both following scientific progress and for written and oral communication. | X | ||||
*1 Lowest, 2 Low, 3 Average, 4 High, 5 Highest
