ESF:DXE_EMTR Econometrics - Course Information
DXE_EMTR EconometricsFaculty of Economics and Administration
- Extent and Intensity
- 24/0/0. 12 credit(s). Type of Completion: zk (examination).
- Prof. Dr. Peter Hackl (lecturer)
prof. Ing. Osvald Vašíček, CSc. (lecturer)
doc. Ing. Daniel Němec, Ph.D. (assistant)
- Guaranteed by
- prof. Ing. Osvald Vašíček, CSc.
Department of Economics - Faculty of Economics and Administration
Contact Person: Mgr. Lucie Přikrylová
Supplier department: Department of Economics - Faculty of Economics and Administration
- Fri 9. 10. 13:00–14:00 S307, Fri 16. 10. 10:00–14:00 S307, Fri 23. 10. 10:00–14:00 S307, Fri 30. 10. 10:00–14:00 S307, Fri 6. 11. 10:00–14:00 S307, Fri 13. 11. 10:00–14:00 S307, Fri 20. 11. 10:00–14:00 S307, Fri 27. 11. 10:00–14:00 S307, Fri 4. 12. 10:00–14:00 S307, Fri 11. 12. 10:00–14:00 S307, Fri 18. 12. 10:00–14:00 S307
- Participants should be familiar with the following topics:
*Linear algebra – linear equations, matrices, vectors (basic operations and properties).
*Descriptive statistics – measures of central tendency, measures of dispersion, measures of association, histogram, frequency tables, scatterplot, quantiles
*Theory of probability – probability and its properties, random variables and distribution functions in one and several dimensions, moments, convergence of random variables, limit theorems, law of large numbers.
*Mathematical statistics – point estimation, confidence intervals for parameters of normal distribution, hypothesis testing, p-value, significance level.
These topics correspond to the appendices of Verbeek’s book, in particular, to the sections: A1, A2, A3, A4, A6, A8, B1, B2, B3 (excluding Jensen's inequality), B4, B5, B6 and B7 (excluding some properties of the chi-squared distribution and the F-distribution)
- 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
- there are 26 fields of study the course is directly associated with, display
- Course objectives
- The course introduces students to common used econometric tools and techniques. Students shall gain sufficient knowledge and experience for his/her independent and qualified work with empirical data. The student should be able to formulate correctly, to identify economic models and to interpret the results accordingly.
- Learning outcomes
- Students shall gain sufficient knowledge and experience to:
- independently work with empirical data;
- formulate economic and econometric model correctly;
- identify econometric models;
- interpret the results accordingly;
- understand actual academic papers using econometric techniques;
- apply obtained knowledge of econometric theory for further study of advanced fields of econometrics.
- 1. Introduction to linear regression model (Verbeek, Ch. 2) – normal linear regression model, least squares method, properties of OLS estimators;
- 2. Introduction to linear regression model (Verbeek, Ch. 2) – goodness of fit, hypotheses testing, multicollinearity;
- 3. Interpreting and comparing regression models (Verbeek, Ch.3) – interpretation of the fitted model, selection of regressors, testing the functional form;
- 4. Heteroskedascity and autocorrelation (Verbeek, Ch. 4) – causes, consequences, testing, alternatives for inference;
- 5. Endogeneity, instrumental variables and GMM (Verbeek, Ch. 5) – the instrumental variables estimator, the generalized instrumental variables estimator, the Generalized Method of Moments (principles and examples of use);
- 6. The practice of econometric modeling
- required literature
- VERBEEK, Marno. A guide to modern econometrics. Fifrh edition. Hoboken: Wiley Custom, 2017. xii, 508. ISBN 9781119472117. info
- recommended literature
- KENNEDY, Peter. A guide to econometrics. 6th ed. Malden: Blackwell, 2008. xii, 585. ISBN 9781405182584. info
- Teaching methods
- 6 lectures á 3 hours (i.e., 24 teaching hours, 45 minutes each), class discussion, homeworks (computer exercises using Gretl) and presentation of homeworks by participants
- Assessment methods
- For grading, written homework, presentation of homework in class and a final written exam will be of relevance. The weights are as follows: homework with 40%, final exam (consisting of theoretical and practical part) with 60%. The presentation of homework in class means that students must be prepared to be called at random. Minimal requirements to pass final exam are as follows: 60%.
- Language of instruction
- Further Comments
- The course can also be completed outside the examination period.
The course is taught annually.
- Enrolment Statistics (recent)
- Permalink: https://is.muni.cz/course/econ/autumn2020/DXE_EMTR