Course Name | Applied Econometrics |
Code | Semester | Theory (hour/week) | Application/Lab (hour/week) | Local Credits | ECTS |
---|---|---|---|---|---|
ECON 324 | Fall/Spring | 3 | 0 | 3 | 5 |
Prerequisites |
| ||||||||
Course Language | English | ||||||||
Course Type | Elective | ||||||||
Course Level | First Cycle | ||||||||
Mode of Delivery | - | ||||||||
Teaching Methods and Techniques of the Course | |||||||||
Course Coordinator | |||||||||
Course Lecturer(s) | |||||||||
Assistant(s) |
Course Objectives | The main objective of the course is to teach students advanced econometric methods building on their knowledge of the classical regression model and its violations learned in ECON 301. Each student is required to prepare a project to show their skills developed in this course. |
Learning Outcomes | The students who succeeded in this course;
|
Course Description | The course will teach advanced techniques that are required for empirical work in economics. Emphasis will be on the use and interpretation of single equation and system estimation techniques rather than on their derivation. The purpose of the course is to help students understand how to interpret economic data and conduct empirical tests of economic theories. It will focus on issues that arise in using such data, and the methodology for solving these problems. Specific topics include limited dependent variables, simultaneous equations, time series models, nonstationarity and cointegration and panel data analysis. The regression package EVIEWS will be used for empirical work. |
Related Sustainable Development Goals | |
| Core Courses | |
Major Area Courses | ||
Supportive Courses | X | |
Media and Managment Skills Courses | ||
Transferable Skill Courses |
Week | Subjects | Required Materials |
1 | Introduction | |
2 | Time Series Models | Using Econometrics: A Practical Guide Chapter 12 |
3 | Time Series Models – cont’d. | Using Econometrics: A Practical Guide Chapter 12 |
4 | Nonstationary Data | Using Econometrics: A Practical Guide Chapter 12 |
5 | Dummy Dependent Variable Techniques | Using Econometrics: A Practical Guide Chapter 13 |
6 | Dummy Dependent Variable Techniques – cont’d | Using Econometrics: A Practical Guide Chapter 13 |
7 | Midterm Exam | |
8 | Simultaneous Equations | Using Econometrics: A Practical Guide Chapter 14 |
9 | Simultaneous Equations – cont’d | Using Econometrics: A Practical Guide Chapter 14 |
10 | Forecasting | Using Econometrics: A Practical Guide Chapter 15 |
11 | Forecasting – cont’d | Using Econometrics: A Practical Guide Chapter 15 |
12 | ARIMA Models | Using Econometrics: A Practical Guide Chapter 15 |
13 | Analysis of Panel Data | |
14 | Analysis of Panel Data | |
15 | Review of the semester | |
16 | Review of the semester |
Course Notes/Textbooks | A. H. Studenmund, Using Econometrics: A Practical Guide (Fifth Edition) |
Suggested Readings/Materials |
Semester Activities | Number | Weighting |
Participation | ||
Laboratory / Application | ||
Field Work | ||
Quizzes / Studio Critiques | ||
Portfolio | ||
Homework / Assignments | ||
Presentation / Jury | ||
Project | 2 | 40 |
Seminar / Workshop | ||
Oral Exam | ||
Midterm | 1 | 30 |
Final Exam | 1 | 30 |
Total |
Weighting of Semester Activities on the Final Grade | 3 | 70 |
Weighting of End-of-Semester Activities on the Final Grade | 1 | 30 |
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 | 2 | 32 |
Field Work | |||
Quizzes / Studio Critiques | |||
Portfolio | |||
Homework / Assignments | |||
Presentation / Jury | |||
Project | 2 | 15 | |
Seminar / Workshop | |||
Oral Exam | |||
Midterms | 1 | 20 | |
Final Exams | 1 | 20 | |
Total | 150 |
# | Program Competencies/Outcomes | * Contribution Level | ||||
1 | 2 | 3 | 4 | 5 | ||
1 | To be able to acquire a sound knowledge of fundamental concepts, theories, principles and methods of investigation specific to the economic field. | X | ||||
2 | To be able to apply adequate mathematical, econometric, statistical and data analysis models to process economic data and to implement scientific research for development of economic policies. | X | ||||
3 | To be able to participate in academic, professional, regional, and global networks and to utilize these networks efficiently. | X | ||||
4 | To be able to have adequate social responsibility with regards to the needs of the society and to organize the activities to influence social dynamics in line with social goals. | |||||
5 | To be able to integrate the knowledge and training acquired during the university education with personal education and produce a synthesis of knowledge one requires. | |||||
6 | To be able to evaluate his/her advance level educational needs and do necessary planning to fulfill those needs through the acquired capability to think analytically and critically. | X | ||||
7 | To be able to acquire necessary skills to integrate social dynamics into economic process both as an input and an output. | X | ||||
8 | To be able to link accumulated knowledge acquired during the university education with historical and cultural qualities of the society and be able to convey it to different strata of society. | X | ||||
9 | To be able to take the responsibility as an individual and as a team member. | |||||
10 | To be able to attain social, scientific and ethical values at the data collection, interpretation and dissemination stages of economic analysis. | X | ||||
11 | To be able to collect data in economics and communicate with colleagues in a foreign language ("European Language Portfolio Global Scale", Level B1) | X | ||||
12 | To be able to speak a second foreign at a medium level of fluency efficiently. | |||||
13 | To be able to relate the knowledge accumulated throughout human history to their field of economics. |
*1 Lowest, 2 Low, 3 Average, 4 High, 5 Highest