# ESF:MPE_EKON Econometrics - Course Information

## MPE_EKON Econometrics

**Faculty of Economics and Administration**

Spring 2025

**Extent and Intensity**- 2/2/0. 12 credit(s). Type of Completion: zk (examination).

In-person direct teaching **Teacher(s)**- doc. Ing. Daniel Němec, Ph.D. (lecturer)

doc. Ing. Daniel Němec, Ph.D. (seminar tutor)

Mgr. Jakub Chalmovianský, Ph.D. (lecturer)

Mgr. Jakub Chalmovianský, Ph.D. (seminar tutor)

Ing. Mgr. Vlastimil Reichel, Ph.D. (assistant) **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 **Prerequisites**- (!
**MPE_ECNM**Econometrics )&&(!**MPE_AECM**Econometrics )&&(!NOWANY(**MPE_ECNM**Econometrics ,**MPE_AECM**Econometrics ))

basic matrix algebra, elementary probability and mathematical statistics, pssing the course Introduction to econometrics (BPE_ZAEK) (recommended) **Course Enrolment Limitations**- The course is also offered to the students of the fields other than those the course is directly associated with.
**fields of study / plans the course is directly associated with**- there are 10 fields of study the course is directly associated with, display
**Course objectives**- Topics of introductory econometrics (covered in "Introduction to Econometrics") will be reviewed and expanded into more advanced level, in terms of both the econometric theory and the level of complexity of the models. Advanced econometric topics include instrumental variable estimations, maximum likelihood estimation, GMM etc.
**Learning outcomes**- The course is designed to provide students with a working knowledge of basic and advanced 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 econometric methods and tools.

They have a foundation and understanding for further study of econometric theory. **Syllabus**- 1. Introduction to linear regression model – normal linear regression model, least squares method, testing of hypothesis;
- 2. Heteroskedascity and autocorrelation – causes, consequences, testing, solution;
- 3. Other estimation tools and techniques – method of instrumental variables, GMM, maximal likelihood (principles and examples of use), tests of specifications;
- 4. Panel data models – basic principles and variations, estimation methods
- 5. Discrete choice models – probit, logit, tobit models and their alternatives (principles, use and interpretation of results of estimation);
- 6. Simultaneous equations models - structural and reduced form, 2SLS, 3SLS, LIML, FIML;

**Literature**- HEIJ, Christiaan.
*Econometric methods with applications in business and economics*. 1st ed. Oxford: Oxford University Press, 2004, xxv, 787. ISBN 9780199268016. info - HANSEN, Bruce E.
*Econometrics*. Princeton, New Jersey: Princeton University Press, 2022, xxxi, 1044. ISBN 9780691235899. info

*required literature*- BALTAGI, Badi H.
*Econometric analysis of panel data*. Sixth edition. Cham: Springer, 2021, xx, 424. ISBN 9783030539528. info - GREENE, William H.
*Econometric analysis*. Eighth edition. Harlow, England: Pearson, 2020, 1166 stran. ISBN 9781292231136. info - HEISS, Florian.
*Using R for introductory econometrics*. 2nd edition. Düsseldorf: Florian Heiss, 2020, 368 stran. ISBN 9788648424364. info - HEISS, Florian and Daniel BRUNNER.
*Using Python for introductory econometrics*. 1st edition. Düsseldorf: Florian Heiss, 2020, 418 stran. ISBN 9788648436763. info

*recommended literature*- HEIJ, Christiaan.
**Teaching methods**- lectures, class discussion, computer labs practices, drills
**Assessment methods**- homeworks assignments and seminar activity (50% of the final grade), oral exam (50 % of the final grade); details of the course completion for students going abroad are contained in the Organisational guidelines (see study materials in IS)
**Language of instruction**- Czech
**Follow-Up Courses****Further comments (probably available only in Czech)**- The course is taught annually.

The course is taught: every week.

General note: Přednášky jsou dostupné online a ze záznamu. **Listed among pre-requisites of other courses****MPE_ECNM**Econometrics

(!MPE_AECM) && (!MPE_EKON) && (!NOWANY(MPE_AECM,MPE_EKON))

- Enrolment Statistics (Spring 2025, recent)
- Permalink: https://is.muni.cz/course/econ/spring2025/MPE_EKON