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ECTS Course Overview



Introduction to Econometrics

* Exchange students do not have to consider this information when selecting suitable courses for an exchange stay.

Course Unit Code157-0588/02
Number of ECTS Credits Allocated5 ECTS credits
Type of Course Unit *Choice-compulsory
Level of Course Unit *First Cycle
Year of Study *
Semester when the Course Unit is deliveredSummer Semester
Mode of DeliveryFace-to-face
Language of InstructionEnglish
Prerequisites and Co-Requisites Course succeeds to compulsory courses of previous semester
Name of Lecturer(s)Personal IDName
HAN60prof. Ing. Jana Hančlová, CSc.
CHY0034Mgr. Ing. Lucie Chytilová, Ph.D.
Summary
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
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.
Course Contents
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
Required Reading:
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.


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.

Recommended Reading:
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
Lectures, Individual consultations, Tutorials, Project work
Assesment methods and criteria
Tasks are not Defined