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Lecturer(s)
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Course content
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Topics of the lectures: 1. Subject of econometrics, econometric model. 2. - 3. Classical linear regression model in economic applications - statistical assumptions, parameter estimation, properties of the estimators, goodness-of-fit measures, predictions. 4. - 5. Statistical inference in linear regression models - test of parameters and its linear combinations. 6. Asymptotical properties of the linear regression - consistency, asymptotic normality. Asymptotical inference, LM test. 7. - 8. Testing, corrections and estimation methods in case of violated assumptions - heteroskedasticity, autocorrelations, multicollinearity, specification errors. Weighted least squares method. 9. - 10. Further issues of the linear regression: residual analysis, predictions, prediction and confidence intervals. Functional forms of the dependence, modelling elasticity. Models with interactions. 11. Qualitative variables - linear probability models. 12. - 13. Introduction to multi-equation linear regression models, system of simultaneous equations, structural and reduced form, model identification, estimation procedures. 14. Applications, econometric models in practice.
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Learning activities and teaching methods
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Monologic (reading, lecture, briefing), Dialogic (discussion, interview, brainstorming), Work with multi-media resources (texts, internet, IT technologies), Blended learning
- Preparation for classes
- 50 hours per semester
- Class attendance
- 18 hours per semester
- Semestral paper
- 42 hours per semester
- Preparation for credit
- 14 hours per semester
- Preparation for exam
- 28 hours per semester
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Learning outcomes
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The main objective of the course is to introduce basic econometric models, principles and tools instrumental to quantitative analysis and estimation in macroeconomic and microeconomic models.
Students understand the basic principles of econometrics and are able to perform basic quantitative analysis and estimate in macroeconomic and microeconomic models.
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Prerequisites
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Prerequisites: Theory of Probability and Statistics 2 (TPS2, TPS2A), Mathematics 2 (MATII, MAIIA)
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Assessment methods and criteria
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Student performance assessment, Test
Credit Requirements: Solving ordered problems and successful accomplishment of the following credit test. Examination Requirements: Written and oral examination: knowledge of the methods, their assumptions and principles, application on a simple example.
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Recommended literature
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Cipra, T. Finanční ekonometrie. Praha: Ekopress, 2014. ISBN 978-80-86929-93-4.
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Hušek, R. Ekonometrická analýza.. Praha: Oeconomica, 2007. ISBN 978-80-245-1300-3.
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Tvrdoň, J. Ekonometrie. Praha: ČZU, 2015. ISBN 978-80-213-0819-0.
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Wooldridge, Jeffrey M. Introductory econometrics : a modern approach. Sixth edition, student edition. Boston : Cengage Learning, 2016. ISBN 978-1-305-27010-7.
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