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Lecturer(s)
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Dostal Rostislav, Ing. Ph.D.
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Course content
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1. Classical regression linear model with econometric applications. 2. Model selection and hypothesis tests. 3. Generalized regression model. Regression diagnosis. Weighted Least Square. 4. Special econometric models. regression models with dummy variables. Models with lagged variables. 5. Models for discrete choice. Limited dependent variables . truncation, censoring, sample selection. 6. Nonlinear regression models. 7. Systems of equations. Models for panel data. Simultaneous Equations models. 8. Models of interest rates and interest rate derivatives. 9. Quantitative risk management.
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Learning activities and teaching methods
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Interactive lecture, Lecture with practical applications, Students' portfolio, Individual study, Students' self-study
- Contact hours
- 39 hours per semester
- Undergraduate study programme term essay (20-40)
- 30 hours per semester
- Preparation for an examination (30-60)
- 40 hours per semester
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| prerequisite |
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| Knowledge |
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| describe and explain the principles of statistical inference - especially the principles of point and interval estimates and the principles of testing statistical hypotheses (within the scope of the course KMA / PSA) |
| describe and explain the basic operations of matrix calculus (within the scope of the course KMA / LA) |
| formulate and explain the definition of probability (within the scope of the subject KMA / PSA) |
| explain basic microeconomic and macroeconomic theories of mainstream economics (in the range of subjects KEM / EK1 and KEM / EK2) |
| describe and explain the basic concepts of differential and integral calculus (within the scope of subjects KMA / M1 and KMA / M2) |
| Skills |
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| use knowledge of basic statistical methods and procedures for simple data analysis |
| differentiate between different types of random variables (discrete, continuous) and different types of distributions |
| apply theoretical economic knowledge to model situations |
| Competences |
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| N/A |
| learning outcomes |
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| Knowledge |
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| explain the principle of regression models and describe various possibilities of estimating the parameters of regression models |
| describe and explain the assumptions of regression analysis and the consequence of non-compliance with the assumption on the quality of model parameter estimation |
| formulate econometric models as regression linear and nonlinear models |
| describe and interpret regression models with binary variables |
| Skills |
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| formulate a regression model suitable for specific data |
| use knowledge of the assumptions of regression models for regression diagnostics |
| estimate the parameters of linear and nonlinear regression models in at least one SW environment |
| apply the formal and content side correctly in mathematical expression, both written and oral |
| interpret econometric models of the general professional public and is able to assess the adequacy of the use of the proposed models |
| Competences |
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| N/A |
| N/A |
| teaching methods |
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| Knowledge |
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| Interactive lecture |
| Individual study |
| Skills |
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| Interactive lecture |
| Individual study |
| Competences |
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| Individual study |
| Interactive lecture |
| assessment methods |
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| Knowledge |
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| Combined exam |
| Seminar work |
| Skills |
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| Combined exam |
| Seminar work |
| Competences |
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| Combined exam |
| Seminar work |
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Recommended literature
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Anděl, Jiří. Matematika náhody. Vyd. 2. Praha : Matfyzpress, 2003. ISBN 80-86732-07-X.
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ARLT, J. Moderní metody modelování ekonomických časových řad. Vyd. 1. Praha : Grada, 1999. ISBN 80-7169-539-4.
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Cipra, Tomáš. Analýza časových řad s aplikacemi v ekonomii. SNTL Praha, 1986.
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Cipra, Tomáš. Ekonometrie. SPN Praha, 1984.
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Cipra, Tomáš. Finanční ekonometrie. 1. vyd. Praha : Ekopress, 2008. ISBN 978-80-86929-43-9.
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G. Judge a spol. Theory and Practice of Econometrics.
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Heiss. Using R for Introductiory Econometrics.
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HUŠEK, R. Ekonometrická analýza. Praha : Ekopress, 1999. ISBN 80-86119-19-X.
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HUŠEK R. Základy ekonometrické analýzy II. Speciální postupy a techniky. VŠE, Praha 1998. 1998.
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Hušek, Roman. Základy ekonometrické analýzy I : modely a metody. 1. vyd. Praha : VŠE, 1996. ISBN 80-7079-102-0.
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Zvára, K. Regresní analýza. Academia Praha, 1989.
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