N_Em Econometrics

University of Finance and Administration
Winter 2025
Extent and Intensity
2/2/0. 6 credit(s). Type of Completion: zk (examination).
Teacher(s)
doc. Ing. Lubomír Lízal, Ph.D. (seminar tutor)
Guaranteed by
doc. Ing. Lubomír Lízal, Ph.D.
Department of Finance – Departments – University of Finance and Administration
Contact Person: Ivana Plačková
Timetable of Seminar Groups
N_Em/cFPH: Wed 10:30–11:14 S24, Wed 11:15–12:00 S24, except Wed 22. 10. ; and Fri 17. 10. 10:30–12:00 S24, L. Lízal
N_Em/pFPH: Wed 8:45–9:29 S24, Wed 9:30–10:15 S24, except Wed 22. 10. ; and Fri 17. 10. 8:45–10:15 S24, L. Lízal
Prerequisites
The subject has no formal prerequisites. Knowledge of the basics of statistics is advantageous. The course will begin with a summary of the necessary knowledge of statistics.
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 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. Introduction to statistics – overview 2. Introduction to econometrics – data, principles, research methods 3. Pairwise regression – single variable regression model 4. Multiple variable regression model – multiple regression – introduction, heteroscedasticity 5. Multiple regression - cross-sectional data, correlation analysis, significance, multicollinearity 6. Multiple regression - specification, RESET tests, linear and quadratic form 7. Multiple regression - indicator variables and changes 8. Probit, logit 9. Time series - introduction 10. Time series - autocorrelation, heteroscedasticity 11. Time series - dynamic models, unit root 12. Panel data: combination of cross-sectional and time series data, examples
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 lectures involving all students of the given teaching group. Exercises will be devoted to training in the practical mastery of econometric techniques. Seminar papers will be assigned for pairs of students.
Assessment methods
In order to successfully complete the course, students must obtain a credit and pass the subsequent exam. To be awarded a credit, students must have sufficient attendance and activity and must also defend their seminar paper. The exam will consist of a discussion of the seminar paper and answering one or two summary questions.
Language of instruction
Czech
Further Comments
The course can also be completed outside the examination period.
The course is also listed under the following terms Winter 2019, Winter 2020, Winter 2021, Winter 2022, Winter 2023, Winter 2024, Winter 2026.
  • Enrolment Statistics (Winter 2025, recent)
  • Permalink: https://is.vsfs.cz/course/vsfs/winter2025/N_Em