Course: Mathematical Models in Econometrics

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Course title Mathematical Models in Econometrics
Course code KMA/MME-A
Organizational form of instruction Lecture + Tutorial
Level of course Master
Year of study not specified
Semester Winter
Number of ECTS credits 5
Language of instruction English
Status of course unspecified
Form of instruction Face-to-face
Work placements This is not an internship
Recommended optional programme components None
Course availability The course is available to visiting students
Lecturer(s)
  • Šedivá Blanka, RNDr. Ph.D.
  • Tomiczková Světlana, RNDr. Ph.D.
Course content
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.

Learning activities and teaching methods
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
prerequisite
professional knowledge
Students should have a basic knowledge of differential and integral one variable functions calculus, basic knowledge of matrix theory and basic knowledge of probability and statistics.
learning outcomes
On completion of this module the student will be able to: - understand and apply the least-squares method to estimate linear regression, - analyse regression models with dummy variables, - analyse and use some special economic regression models, - analyse and use probit and logit regression models, - use and understand econometrics methods for modeling of interest rates, - use and understand methods for quantitative risk management.
teaching methods
Interactive lecture
Students' self-study
Individual study
Students' portfolio
Lecture with practical applications
assessment methods
Combined exam
Individual presentation at a seminar
Quality of a written report
Recommended literature
  • Anděl, Jiří. Matematika náhody. Vyd. 2. Praha : Matfyzpress, 2003. ISBN 80-86732-07-X.
  • ARLT, J. Moderní metody modelování ekonomických časových řad. Vyd. 1. Praha : Grada, 1999. ISBN 80-7169-539-4.
  • Cipra, Tomáš. Analýza časových řad s aplikacemi v ekonomii. SNTL Praha, 1986.
  • Cipra, Tomáš. Ekonometrie. SPN Praha, 1984.
  • G. Judge a spol. Theory and Practice of Econometrics.
  • HUŠEK, R. Ekonometrická analýza. Praha : Ekopress, 1999. ISBN 80-86119-19-X.
  • HUŠEK R. Základy ekonometrické analýzy II. Speciální postupy a techniky. VŠE, Praha 1998. 1998.
  • Hušek, Roman. Základy ekonometrické analýzy I : modely a metody. 1. vyd. Praha : VŠE, 1996. ISBN 80-7079-102-0.
  • Zvára, K. Regresní analýza. Academia Praha, 1989.


Study plans that include the course
Faculty Study plan (Version) Branch of study Category Recommended year of study Recommended semester