MPE_ECNM Econometrics

Faculty of Economics and Administration
Spring 2020
Extent and Intensity
2/2/0. 8 credit(s). Type of Completion: zk (examination).
Teacher(s)
Ketevani Kapanadze (lecturer)
Ing. Daniel Němec, Ph.D. (lecturer)
prof. Ing. Osvald Vašíček, CSc. (lecturer)
Ketevani Kapanadze (seminar tutor)
Ing. Daniel Němec, Ph.D. (seminar tutor)
Guaranteed by
prof. Ing. Osvald Vašíček, CSc.
Department of Economics - Faculty of Economics and Administration
Contact Person: Mgr. Jarmila Šveňhová
Supplier department: Department of Economics - Faculty of Economics and Administration
Timetable
Fri 12:00–13:50 VT206
  • Timetable of Seminar Groups:
MPE_ECNM/01: Fri 14:00–15:50 VT206, D. Němec
Prerequisites
(! MPE_AECM Econometrics ) && (! MPE_EKON Econometrics ) && (! NOWANY ( MPE_AECM Econometrics , MPE_EKON Econometrics ))
basic matrix algebra, elementary probability and mathematical statistics, passing the course Introduction to econometrics (BPE_INEC or BPE_ZAEK) (recommended)
Course Enrolment Limitations
The course is only offered to the students of the study fields the course is directly associated with.

The capacity limit for the course is 15 student(s).
Current registration and enrolment status: enrolled: 14/15, only registered: 0/15
fields of study / plans the course is directly associated with
Course objectives
The course is designed to give students experience of using basic and advanced 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. Topics of introductory econometrics (covered in "Introduction to Econometrics") will be reviewed and expanded into more advanced level. Advanced econometric topics include non-linear least squares, instrumental variable estimators, maximum likelihood method, and generalised method of moments.
We start with a short review of linear regression model and least squares method. Careful attention is given to the interpretation of regression results, hypothesis testing and to diagnostic tests. Moreover, further topics in regression analysis are presented including time series econometrics, 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, cross-sectional and panel data, and will have experience of a range of basic and advanced econometric methods.
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 modelling, estimation, inference, and forecasting in the context of real 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. Linear regression model, least squares method and classical assumption
  • 2. Modelling issues and further inference in the multiple regression model
  • 3. Freeing up the classical assumptions (heteroskedasticity and autocorrelation)
  • 4. Introduction to non-linear methods (non-linear least square, maximum likelihood estimation, generalised method of moments)
  • 5. Endogenous regressors and instrumental variables
  • 6. Qualitative and limited dependent variable models
  • 7. Regression with time series data (stationary variables)
  • 8. Regression with time series data (nonstationary variables)
  • 9. Panel data models
  • 10. Vector error correction and vector autoregressive models
Literature
    required literature
  • HILL, R. Carter, William E. GRIFFITHS and Guay C. LIM. Principles of econometrics. 4th ed. Hoboken: John Wiley & Sons, 2012. xxvi, 758. ISBN 9780470873724. info
  • HEIJ, Christiaan. Econometric methods with applications in business and economics. 1st ed. Oxford: Oxford University Press, 2004. xxv, 787. ISBN 9780199268016. info
    recommended literature
  • GUJARATI, Damodar N. and Dawn C. PORTER. Basic econometrics. 5th ed. Boston: McGraw-Hill, 2009. xx, 922. ISBN 9780071276252. info
  • KENNEDY, Peter. A guide to econometrics. 6th ed. Malden: Blackwell, 2008. xii, 585. ISBN 9781405182584. info
  • KOOP, Gary. Introduction to econometrics. Chichester: John Wiley & Sons, 2008. 371 s. ISBN 9780470032701. info
Teaching methods
tutorials, class discussion, computer labs practices, drills
Assessment methods
final project, written and oral exam
Language of instruction
English
Further comments (probably available only in Czech)
Study Materials
The course is taught annually.
General note: Tento kurz je ekvivalentní českému MPE_EKON a může být za něj uznán. Také je ekvivalentem MPE_AECM.This course is an equivalent to MPE_EKON and MPE_AECM.
Listed among pre-requisites of other courses
The course is also listed under the following terms Spring 2016, Spring 2017, Spring 2018, Spring 2019, Spring 2021.
  • Enrolment Statistics (recent)
  • Permalink: https://is.muni.cz/course/econ/spring2020/MPE_ECNM