N_Em Econometrics

University of Finance and Administration
Winter 2024
Extent and Intensity
2/2/0. 6 credit(s). Type of Completion: zk (examination).
Teacher(s)
Ing. Emilie Jašová, Ph.D. (seminar tutor)
Guaranteed by
doc. RNDr. Petr Budinský, CSc.
Department of Finance – Departments – University of Finance and Administration
Contact Person: Dita Egertová
Timetable of Seminar Groups
N_Em/cFPH: Wed 19:15–19:59 S23, Wed 20:00–20:45 S23, except Wed 20. 11. ; and Wed 30. 10. 15:45–17:15 S23, E. Jašová
N_Em/pFPH: Wed 17:30–18:14 S23, Wed 18:15–19:00 S23, except Wed 20. 11. ; and Wed 23. 10. 15:45–17:15 S23, E. Jašová
Prerequisites
The subject has no prerequisites. Knowledge of the basics of statistics is advantageous.
Course Enrolment Limitations
The course is offered to students of any study field.
Course objectives
Learning outcomes of the course unit The aim of the course is to teach students to use econometric procedures excellently to search for relationships between variables, preferably for processing final theses, but also in their future work. The student will master the method of econometrics, which serves to verify economic theories by observable data or to discover new quantitative relationships between economic and other processes. At the same time, the course aims to provide students with an in-depth understanding of the basic principles underlying the econometric method. In addition to theoretical knowledge, the emphasis is also on mastery of appropriate statistical programs.
Learning outcomes
tudents will be able to:
- identify data from recommended sources and adjust them to the needs of econometrics
- Student will be able to solve linear and nonlinear one or more dimensional regression and correlation problems
- Student will be able to use appropriate software
- The student will be able to interpret the achieved results
Syllabus
  • 1. Econometrics - principles, methods of investigation 2. Statistical data analysis, basic information sources 3. Correlation and correlation analysis 4. Regression model of one variable 5. Hypothesis testing, confidence intervals, p-value 6. Regression model of multiple variables 7. Analysis of one-dimensional time series; stacionarita 8. Multicollinearity, autocorrelation, heteregedasticity 9. Nonlinear regression model, Cobb-Douglas production function 10. Analysis of multidimensional time series, HP filter 11. Example of multiple regression - Sowery ratink
Literature
    required literature
  • CIPRA, Tomáš. Finanční ekonometrie. Ekopress, Praha, 2013, ISBN 978-80-86929-93-4
    recommended literature
  • HANČLOVÁ, Jana. Ekonometrické modelování. Edition Kamil Mařík-Professional publishing, Praha, 2012, ISBN 978-80-7431-088-1
Teaching methods
Teaching will take the form of interactive lectures involving all students of the given teaching group. Exercises will be devoted exclusively to mastering specialized publicly available software. Seminar papers will be assigned for pairs of students.
Assessment methods
Teaching will take the form of interactive lectures involving all students of the given teaching group. Exercises will be devoted exclusively to mastering specialized publicly available software. Seminar papers will be assigned for pairs of students.
Language of instruction
Czech
Further comments (probably available only in Czech)
The course can also be completed outside the examination period.
Information on the extent and intensity of the course: 12 hodin KS/semestr.
The course is also listed under the following terms Winter 2019, Winter 2020, Winter 2021, Winter 2022, Winter 2023.
  • Enrolment Statistics (recent)
  • Permalink: https://is.vsfs.cz/course/vsfs/winter2024/N_Em