Economic and mathematical modelling of the world economic processes
Course: International Economic Relations (with compulsory study of two foreign languages)
Structural unit: Educational and scientific institute of international relations
            Title
        
        
            Economic and mathematical modelling of the world economic processes
        
    
            Code
        
        
            ОК22
        
    
            Module type 
        
        
            Обов’язкова дисципліна для ОП
        
    
            Educational cycle
        
        
            First
        
    
            Year of study when the component is delivered
        
        
            2021/2022
        
    
            Semester/trimester when the component is delivered
        
        
            5 Semester
        
    
            Number of ECTS credits allocated
        
        
            4
        
    
            Learning outcomes
        
        
            To know basic methodological principles of economic and mathematical research of social and economic systems; types of economic and mathematical models and levels of their use; methods of correlation, regression and factor analysis; optimization models and linear programming methods; limitations and assumptions of economic and mathematical modelling.
To be able to do quantitative and qualitative assessment of phenomena and relations in the world economic processes, model their dynamics, determine trends and forecast world economic development, solve problems on international logistics with linear programming methods, to use software for economic and mathematical modeling, interpret results of economic and mathematical modeling, consider limitations of the methods, adjust algorithms of research.
Communication for determining algorithm of research and interpreting results of economic and mathematical modeling.
        
    
            Form of study
        
        
            Full-time form
        
    
            Prerequisites and co-requisites
        
        
            - To know indicators of state and development of the world economy.
- To be able to apply mathematical tools for describing economic processes.
- To have basic skills in modern information technologies.
- To know English or other foreign languages for better opportunities for study of  examples of modern research on economic and mathematical modeling and using special software.
        
    
            Course content
        
        
            Module 1. Basic theoretical knowledge about economic and mathematical modeling of world economic processes.
1.Conceptual aspects of mathematical modelling of economy.
2.Creating  and analysis of dynamic economic models.
3.Linear optimization economic and mathematical models and methods.
4.Transportation problem: specification of input data, methods of solving and analysis.
5.Nonlinear optimization economic and mathematical models and methods.
6.Introduction into game theory.
7.Theoretical aspects of regression and correlation analysis. Factor analysis.
Module 2. Computer workshop on economic and mathematical modeling. Empirical examples of modelling world economic processes.
8.Special software for economic and mathematical modelling.
9. Correlation analysis methods.
10.Agrorithm of regression modelling.
11.Economic development models.
12. Examples of empirical models of world economic processes.
        
    
            Recommended or required reading and other learning resources/tools
        
        
            1.	Голиков А.П. Економіко-математичне моделювання світогосподарських процесів. Х., 2006.
2.	Грисенко М.В., Чугаєв, О.А. Кількісні методи аналізу міжнародних  економічних  відносин:.  К., 2012.
3.	Грисенко М.В., Шворак Л.О. Економіко-математичне моделювання світогосподарських процесів. К. 2016.
4.	Altshuler C., Holland D., Hong P., Li H.-Y. The World Economic Forecasting Model at the United Nations. United Nations, 2016. 
5.	Chugaiev O. Research Methods and Methodology: Distant Course. Chu Hai College of Higher Education (Honkong, China), 2020.
6.	Excel Easy. Data Analysis (https://www.excel-easy.com/data-analysis.html).
7.	Microsoft. Excel help & learning (https://support.office.com/en-us/excel).
8.	Pereguda O.V., Rusina A.V. Approximate synthesis of distributed optimal control for hyperbolic equations with rapidly oscillating coefficients. – Journal of Mathematical Sciences, 2018. – V.228. – p.306-313.
9.	The General Algebraic Modelling System (https://www.gams.com/).
        
    
            Planned learning activities and teaching methods
        
        
            Lectures, workshops, case study
        
    
            Assessment methods and criteria
        
        
            1. Oral answers, comments, blitz poll – up to 20 points.
2. Problems – up to 20 points.
3. Module control work (test) – up to 10 points.
3. Case study – up to 10 points.
3.Exam – up to 40 points.
        
    
            Language of instruction
        
        
            Ukrainian 
        
    Lecturers
This discipline is taught by the following teachers
                    Oleksii
                    
                    Chugaiev
                
                
                    Chair of World Economy and International Economic Relations 
Educational and scientific institute of international relations
            Educational and scientific institute of international relations
                    Oleh 
                    V. 
                    Perehuda
                
                
                    The Department of General Mathematics 
Faculty of Mechanics and Mathematics of Taras Shevchenko National University of Kyiv
            Faculty of Mechanics and Mathematics of Taras Shevchenko National University of Kyiv
Departments
The following departments are involved in teaching the above discipline
                        Chair of World Economy and International Economic Relations
                    
                    
                        Educational and scientific institute of international relations
                    
                
                        The Department of General Mathematics
                    
                    
                        Faculty of Mechanics and Mathematics of Taras Shevchenko National University of Kyiv