Applied econometrics

Course: Economic Cybernetics

Structural unit: Faculty of Economics

Title
Applied econometrics
Code
ОК 4
Module type
Обов’язкова дисципліна для ОП
Educational cycle
Second
Year of study when the component is delivered
2023/2024
Semester/trimester when the component is delivered
1 Semester
Number of ECTS credits allocated
7
Learning outcomes
PLO1. Articulate, analyze and synthesize solutions of scientific and practical problems. PLO8. Choose effective methods for managing economic activity, justify the proposed solutions based on relevant data, scientific and applied research. PLO10. Apply modern information technologies and specialized software in socio-economic research and in the management of socio-economic systems. PLO12. Justify management decisions for effective business development, taking into account goals, resources, constraints and risks. PLO14. Develop scenarios and strategies for the development of socio-economic systems. PLO16. Plan and perform scientific and/or applied research, make reasonable conclusions on the results of research, present the results, and reason their opinions. PLO20. Identify and critically assess the state and trends of socio-economic development and apply them to the formation of new models of economic systems and processes.
Form of study
Full-time form
Prerequisites and co-requisites
1. Successful completion of the "Econometrics" course. 2. Knowledge of the theoretical foundations of the courses "Higher mathematics for economists (basic level)" and "Probability theory for economists".
Course content
The program of the academic discipline consists of two content modules: Content module 1. "Analysis and construction of regression models", in which the model is considered multiple linear regression, nonlinear regression model, linear regression model with heteroskedastic and autocorrelated residuals, models with lag variables. Content module 2. "Econometrics of time series and microeconometrics." Models with discrete and limited dependent variables. Panel Data Models,” in which the basic concepts of time series theory, vector autoregression model, vector model are considered error correction model, models with discrete and limited dependent variables, models with panel data.
Recommended or required reading and other learning resources/tools
1. Економетрика: підручник/О.І.Черняк, О.В.Комашко, А.В.Ставицький, О.В. Баженова; за ред. О.І.Черняка. – К.: Видавничо-поліграфічний центр «Київський університет», 2010. – 359с. 2. Wooldridge J.M. Introductory Econometrics: A Modern Approach. 7edition. Cengage Learning, 2019. –816р. 3. Hill C., Griffiths W.E., Lim G.C. Principles of Econometrics. - 5th edition. - Wiley, 2018. – 918 p. 4. Stock J. H. and Watson M. W. Introduction to Econometrics. 4th edition, Addison-Wesley, 2018 - 800p. 5. Баженова О.В. Навчально-методичний комплекс з курсу «Прикладна економетрика». – К.: Видавництво «Сталь», 2013. – 116с. 6. Gujarati D. Econometrics by Example, Palgrave Macmillan, 2014 - 496p. 7. Лук’яненко І.Г., Городніченко Ю.О. Сучасні економетричні методи у фінансах. Навчальний посібник. – К.: Літера ЛТД, 2002. – 352с.
Planned learning activities and teaching methods
Lecture, laboratory class
Assessment methods and criteria
1. Questioning and solving problems (RN 1.1-1.5; 2.1-2.2; 4.1-4.2) – 20 points / 12 points; 2. Modular control work (2 MKR, 20 points max. each) (PH 1.1-1.5; 2.1-2.2; 4.1-4.2) – 40 points / 24 points; - final evaluation in the form of an exam
Language of instruction
Ukrainian

Lecturers

This discipline is taught by the following teachers

Oleh Valentynovych Komashko
Department of Economic Cybernetics
Faculty of Economics

Departments

The following departments are involved in teaching the above discipline

Department of Economic Cybernetics
Faculty of Economics