Course Unit Code | 157-0588/02 |
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Number of ECTS Credits Allocated | 5 ECTS credits |
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Type of Course Unit * | Choice-compulsory |
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Level of Course Unit * | First Cycle |
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Year of Study * | |
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Semester when the Course Unit is delivered | Winter Semester |
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Mode of Delivery | Face-to-face |
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Language of Instruction | English |
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Prerequisites and Co-Requisites | Course succeeds to compulsory courses of previous semester |
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Name of Lecturer(s) | Personal ID | Name |
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| HAN60 | prof. Ing. Jana Hančlová, CSc. |
| CHY0034 | Mgr. Ing. Lucie Chytilová, Ph.D. |
Summary |
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The aim of the course is to understand and master the process of econometric analysis of economic behavior of individual entities (eg companies) using cross-sectional resp. panel econometric modeling. |
Learning Outcomes of the Course Unit |
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The goal is to:
- be able to describe and apply the process of analyzing of economic time series,
- understand the process of modeling the behavior of economic system based on regression analysis,
- select and use appropriate econometrics methodology - the formulation, estimation, prediction and verification of modeled systems,
- explain the context of the theoretical behavior of economic systems modeled with empirical results and make appropriate modification of your model,
- use the estimated regression models for forecasting.
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Course Contents |
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1. Time series analysis (basic characteristics, graphical analysis, time series transformation, time series decomposition).
2. Linear regression model (formulation, estimation, specification, assumptions, MNC)
3. Verification of the estimated model (statistical verification, autocorrelation, heteroskedasticity, multicollinearity, economic verification).
4. Prediction (classification of forecasts, point and interval prediction, ex-post and ex-ante prediction, prediction accuracy).
5. Testing the normality of the residual component (graphical assessment, sophisticated statistical tests). |
Recommended or Required Reading |
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Required Reading: |
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1. WOOLDRIDGE, Jeffrey M. Introductory Econometrics: A Modern Approach. South-Western: College Publishers, 2018. 816 s. ISBN-13: 978-1-111-53104-1.
2. STOCK, James H. a WATSON, Mark W. Introduction to Econometrics. Addison-Wesley Longman, 2018. 800 s. ISBN-13: 978-0134461991.
3. GREENE, William H. Econometric Analysis. Upper Saddle River, N.J: Prentice Hall, 2017. 1176 s. ISBN-13: 978-0134461366.
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1. WOOLDRIDGE, Jeffrey M. Introductory Econometrics: A Modern Approach. South-Western: College Publishers, 2018. 816 s. ISBN-13: 978-1-111-53104-1.
2. STOCK, James H. a WATSON, Mark W. Introduction to Econometrics. Addison-Wesley Longman, 2018. 800 s. ISBN-13: 978-0134461991.
3. GREENE, William H. Econometric Analysis. Upper Saddle River, N.J: Prentice Hall, 2017. 1176 s. ISBN-13: 978-0134461366.
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Recommended Reading: |
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1. KOOP, Gary, ed. Bayesian Econometric Methods (Econometric Exercises). Cambridge University Press, 2019. 376 s. ISBN-13: 978-1108437493.
2. HEISS, Florian. Using R for Introductory Econometrics. CreateSpace Independent Publishing Platform, 2020, 378 s. ISBN-13: 978-1523285136.
3. HEISS, Florian. Using Python for Introductory Econometrics. CreateSpace Independent Publishing Platform, 2020. 428 s. ISBN-13: 979-8648436763. |
1. KOOP, Gary, ed. Bayesian Econometric Methods (Econometric Exercises). Cambridge University Press, 2019. 376 s. ISBN-13: 978-1108437493.
2. HEISS, Florian. Using R for Introductory Econometrics. CreateSpace Independent Publishing Platform, 2020, 378 s. ISBN-13: 978-1523285136.
3. HEISS, Florian. Using Python for Introductory Econometrics. CreateSpace Independent Publishing Platform, 2020. 428 s. ISBN-13: 979-8648436763. |
Planned learning activities and teaching methods |
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Lectures, Individual consultations, Tutorials, Project work |
Assesment methods and criteria |
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Tasks are not Defined |