ESF:BKE_ZAEK Introduction to Econometrics - Course Information
BKE_ZAEK Introduction to Econometrics
Faculty of Economics and AdministrationAutumn 2023
- Extent and Intensity
- 26/0/0. 8 credit(s). Type of Completion: zk (examination).
- Teacher(s)
- doc. Ing. Daniel Němec, Ph.D. (lecturer)
- Guaranteed by
- doc. Ing. Daniel Němec, Ph.D.
Department of Economics – Faculty of Economics and Administration
Contact Person: Mgr. Jarmila Šveňhová
Supplier department: Department of Economics – Faculty of Economics and Administration - Timetable
- Sat 14. 10. 12:00–15:50 P302b, Sat 25. 11. 12:00–15:50 P302b, Fri 15. 12. 16:00–19:50 P302b
- Prerequisites
- FORMA(K)
elementary probability and mathematical statistics - Course Enrolment Limitations
- The course is only offered to the students of the study fields the course is directly associated with.
- fields of study / plans the course is directly associated with
- Course objectives
- The course is designed to give students experience of using econometric methods important in economics, finance and other business subjects. It provides skills in regression essential for understanding much of the literature of economics, finance, and empirical studies in other areas of business.
We begin with the simple regression and multiple regression models. They are treated in depth and in range of applications. Careful attention is given to the interpretations of regression results and hypothesis testing. A part of the course introduces various modern tools for analyzing economic time series regression. Moreover, further topics in regression analysis are presented including regression with panel data and binary dependent variable.
By the end of the course students should be able to use regression models in many different applications, and to critically examine reported regression results in empirical research in economics and other business studies. They will be able to identify and deal with a number of econometric problems in the analysis of time series and cross-section data, and will have experience of a range of basic econometric methods. - Learning outcomes
- The course is designed to give students an understanding of why econometrics is necessary and to provide them with a working knowledge of basic econometric tools so that:
They can apply these tools to modeling, estimation, inference, and forecasting in the context of real world economic problems.
They can evaluate critically the results and conclusions from others who use basic econometric tools.
They have a foundation and understanding for further study of econometrics.
They have an appreciation of the range of more advanced techniques that exists and that may be covered in later econometric courses. - Syllabus
- PART 1
- 1. Introduction to econometrics and working with data
- 2. A non-technical introduction to regression
- 3. Simple regression model
- 4. Multiple regression model
- PART 2
- 5. Freeing up the classical assumptions - heteroskedasticity
- 6. Freeing up the classical assumptions - autocorrelated errors
- 7. Instrumental variables method
- PART 3
- 8. Models for panel data
- 9. Qualitative choice and limited dependent variable models
- 10. Univariate time series analysis
- 11. Regression with time series variables
- 12. Vector autoregressive models
- 13. Other models, methods and issues
- Literature
- required literature
- KOOP, Gary. Introduction to econometrics. Chichester: John Wiley & Sons, 2008, 371 s. ISBN 9780470032701. info
- recommended literature
- HILL, R. Carter, William E. GRIFFITHS and Guay C. LIM. Principles of econometrics. Fifth edition. Hoboken: Wiley Custom, 2018, xxvi, 878. ISBN 9781119510567. info
- HEISS, Florian. Using R for introductory econometrics. 2nd edition. Düsseldorf: Florian Heiss, 2020, 368 stran. ISBN 9788648424364. info
- WOOLDRIDGE, Jeffrey M. Introductory econometrics : a modern approach. Seventh edition. Boston: Cengage Learning, 2020, xxi, 826. ISBN 9781337558860. info
- CIPRA, Tomáš. Finanční ekonometrie. 1. vyd. Praha: Ekopress, 2008, 538 s. ISBN 9788086929439. info
- HEISS, Florian and Daniel BRUNNER. Using Python for introductory econometrics. 1st edition. Düsseldorf: Florian Heiss, 2020, 418 stran. ISBN 9788648436763. info
- Teaching methods
- lectures, class discussion, computer labs practices, drills
- Assessment methods
- final project, written and oral exam
- Language of instruction
- Czech
- Further comments (probably available only in Czech)
- The course is taught last offered.
General note: Přednášky jsou dostupné online a ze záznamu.
Information on the extent and intensity of the course: tutorial 12 hodin.
- Enrolment Statistics (recent)
- Permalink: https://is.muni.cz/course/econ/autumn2023/BKE_ZAEK