| Course Name | Applied Economic Topics |
| Code | Semester | Theory (hour/week) | Application/Lab (hour/week) | Local Credits | ECTS |
|---|---|---|---|---|---|
| ECON 407 | Fall/Spring | 3 | 0 | 3 | 6 |
| Prerequisites |
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| 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 | This course designed to help students move from the traditional and comparative static analysis of economic models to a modern and dynamic computational study. The ability to equate an economic problem, to formulate it into a mathematical model and to solve it computationally is becoming a crucial and distinctive competence for most economists. Therefore this course is organised around static and dynamic models, covering both macro- and microeconomic topics, exploring the numerical techniques required to solve those models. A key aim of the course is to enable students to develop the ability to modify the models themselves so that, using the MATLAB/Dynare codes, they can demonstrate a complete understanding of computational methods. This course aims to equip the student with powerful tools to write a microeconomic and macroeconomic model, to define an equilibrium, to approximate the equilibrium using computational methods, and calibrate and simulate the model so that the model can be used to answer economic questions. |
| Learning Outcomes | The students who succeeded in this course;
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| Course Description | The course starts with an introduction to quantitative macroeconomics. We then discuss the benchmark deterministic model and competitive equilibrium. We then discuss steady state. The course continues with introduction to Matlab and Dynare programs in the Lab. It concludes with the discussion of calibration and simulation of a simple real business cycle (RBC) model. |
| Related Sustainable Development Goals | |
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| Core Courses | |
| Major Area Courses | ||
| Supportive Courses | X | |
| Media and Managment Skills Courses | ||
| Transferable Skill Courses |
| Week | Subjects | Required Materials |
| 1 | Introduction to Matlab | A&V: Chp 1 |
| 2 | Matlab for economics | |
| 3 | Supply and demand model and Matlab: Numerical results and simulations | A&V: Chp 1 |
| 4 | Economic model with international-trade policy: Numerical results | A&V: Chp 1 |
| 5 | IS–LM model in a closed economy: Matlab Program | A&V: Chp 1 |
| 6 | IS–LM model in an open economy: Matlab Program | A&V: Chp 1 |
| 7 | AD–AS model:Matlab Program and Numerical results and simulation | A&V: Chp 1 |
| 8 | Midterm | |
| 9 | Utility Maximization and Matlab | Fan Wng: Chp 9 |
| 10 | Profit Maximization and Matlab | Fan Wng: Chp 10 |
| 11 | Introduction to Dynare | Torres Chp 1-2 |
| 12 | Solow Model and Matlab/Dynare | Torres Chp 2 |
| 13 | Ramsey Cass Koopmans Mosel and Matlab/Dynare | A&V: Chp 12 |
| 14 | Real Business Cycle (RBC) Model and Matlab/Dynare | Junior Chp 1-2 |
| 15 | Calibrating and simulating a Basic Real Business Cycle | Junior Chp 1-2 |
| 16 | Project Presentations |
| Course Notes/Textbooks | Afonso and Vasconcelos Computational Economics: A concise introduction (2016) |
| Suggested Readings/Materials | Junior Understanding DSGE Models_ Theory and Applications-Vernon Press (2016) Torres Introduction to Dynamic Macroeconomic General Equilibrium Models-Vernon Press (2016) Fan Wang: Introductory-Mathematics-for-Economists-with-Matlab (2020) |
| Semester Activities | Number | Weigthing |
| Participation | 15 | 10 |
| Laboratory / Application | ||
| Field Work | ||
| Quizzes / Studio Critiques | ||
| Portfolio | ||
| Homework / Assignments | 2 | 30 |
| Presentation / Jury | ||
| Project | ||
| Seminar / Workshop | ||
| Oral Exam | ||
| Midterm | 2 | 40 |
| Final Exam | 1 | 20 |
| Total |
| Weighting of Semester Activities on the Final Grade | 19 | 80 |
| Weighting of End-of-Semester Activities on the Final Grade | 1 | 20 |
| 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 | 1 | |
| Study Hours Out of Class | 16 | 1 | 16 |
| Field Work | |||
| Quizzes / Studio Critiques | |||
| Portfolio | |||
| Homework / Assignments | 2 | 20 | |
| Presentation / Jury | |||
| Project | |||
| Seminar / Workshop | |||
| Oral Exam | |||
| Midterms | 2 | 25 | |
| Final Exams | 1 | 10 | |
| Total | 180 |
| # | Program Competencies/Outcomes | * Contribution Level | ||||
1 | 2 | 3 | 4 | 5 | ||
| 1 | To be able to have a grasp of basic mathematics, applied mathematics or theories and applications of statistics. | |||||
| 2 | To be able to use advanced theoretical and applied knowledge, interpret and evaluate data, define and analyze problems, develop solutions based on research and proofs by using acquired advanced knowledge and skills within the fields of mathematics or statistics. | |||||
| 3 | To be able to apply mathematics or statistics in real life phenomena with interdisciplinary approach and discover their potentials. | X | ||||
| 4 | To be able to evaluate the knowledge and skills acquired at an advanced level in the field with a critical approach and develop positive attitude towards lifelong learning. | |||||
| 5 | To be able to share the ideas and solution proposals to problems on issues in the field with professionals, non-professionals. | |||||
| 6 | To be able to take responsibility both as a team member or individual in order to solve unexpected complex problems faced within the implementations in the field, planning and managing activities towards the development of subordinates in the framework of a project. | |||||
| 7 | To be able to use informatics and communication technologies with at least a minimum level of European Computer Driving License Advanced Level software knowledge. | |||||
| 8 | To be able to act in accordance with social, scientific, cultural and ethical values on the stages of gathering, implementation and release of the results of data related to the field. | |||||
| 9 | To be able to possess sufficient consciousness about the issues of universality of social rights, social justice, quality, cultural values and also environmental protection, worker's health and security. | |||||
| 10 | To be able to connect concrete events and transfer solutions, collect data, analyze and interpret results using scientific methods and having a way of abstract thinking. | X | ||||
| 11 | To be able to collect data in the areas of Mathematics or Statistics and communicate with colleagues in a foreign language. | |||||
| 12 | To be able to speak a second foreign language at a medium level of fluency efficiently. | |||||
| 13 | To be able to relate the knowledge accumulated throughout the human history to their field of expertise. | |||||
*1 Lowest, 2 Low, 3 Average, 4 High, 5 Highest
