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Lecturer(s)
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Boháčová Hana, Mgr. Ph.D.
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Course content
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Autocorrelation methods for univariate time series. Autocorrelation properties of time series. Box-Jenkins methodology - basic models, their construction. Predictions within the Box-Jenkins methodology. Multivariate time series. Generalization of methods for one-dimensional time series. Vector autoregression. Causality testing - Granger causality. Cointegration. Modeling Volatility in Multivariate Time Series. Kalman filter. Basics of panel data analysis - dynamic panel data models. Unit root analysis. Stochastic processes in econometrics - Markov processes, Poisson process, random walk, Brownian process. Modeling the development of financial assets. Simulation of the development of interest rates - Vašiček's model and models derived from it. Black-Scholes model.
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Learning activities and teaching methods
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Monologic (reading, lecture, briefing), Dialogic (discussion, interview, brainstorming), Work with text (with textbook, with book), Work-related activities
- Individual project
- 25 hours per semester
- Contact teaching
- 52 hours per semester
- Data/material collection
- 15 hours per semester
- Home preparation for classes
- 7 hours per semester
- Preparation for a credit (assessment)
- 16 hours per semester
- Preparation for an exam
- 35 hours per semester
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Learning outcomes
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The aim of the course is to equip students with an elementary apparatus for the elaboration of econometric analysis. Emphasis is placed on the application side and on the various pitfalls that arise in the analysis of cross-sectional data and time series in the context of one-equation models and their systems.
A student who has successfully completed the course can: read equation notations of econometric models, use the econometric apparatus in verifying economic hypotheses, characterize the position of econometrics in the methodological apparatus of economics, describe the process of formal economic and statistical verification of the econometric model. A student who has successfully completed the course will be able to: compile an econometric model describing the dependence between economic variables, assess the quality of the econometric model and its ability to capture the modeled reality, interpret the econometric model and estimated parameters, predict the development of economic variables based on simple time series models. A student who has successfully completed the course is able to: be aware of the pitfalls and basic limitations of econometric modeling, solve various analytical tasks in practice requiring formal modeling, transform economic premises and considerations into a formal testable econometric model.
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Prerequisites
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unspecified
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Assessment methods and criteria
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Written examination, Home assignment evaluation
Submission of the seminar paper and passing the final test
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Recommended literature
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ASHLEY, Richard A. Fundamentals of applied econometrics. Hoboken: New Jersey, 2012. ISBN 978-0-470-59182-6.
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CIPRA, Tomáš. Finanční ekonometrie. Praha, 2013. ISBN 978-80-86929-93-4.
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HUŠEK, Roman. Aplikovaná ekonometrie: teorie a praxe. Praha, 2009. ISBN 978-80-245-1623-3.
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MADDALA, G. S. Introduction to econometrics. Chichester, 2001. ISBN 0-471-49728-2.
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SALVATORE, Dominick a REAGLE, Derrick P. Statistics and econometrics. New York, 2011. ISBN 978-0-07-175547-4.
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