157-0360/03 – Econometrics (EKON)

Gurantor departmentDepartment of System EngineeringCredits4
Subject guarantorprof. Ing. Jana Hančlová, CSc.Subject version guarantorprof. Ing. Jana Hančlová, CSc.
Study levelundergraduate or graduateRequirementCompulsory
Year1Semestersummer
Study languageCzech
Year of introduction2014/2015Year of cancellation
Intended for the facultiesEKFIntended for study typesFollow-up Master
Instruction secured by
LoginNameTuitorTeacher giving lectures
CHY0034 Mgr. Ing. Lucie Chytilová, Ph.D.
HAN60 prof. Ing. Jana Hančlová, CSc.
Extent of instruction for forms of study
Form of studyWay of compl.Extent
Full-time Credit 2+2

Subject aims expressed by acquired skills and competences

AAAAA Cílem předmětu je zvládnutí postupu ekonometrického modelování se zaměřením na ekonomickou interpretaci, verifikaci modelu a jeho následné využití v praxi při řízení a rozhodování na mikro i makroúrovni.

Teaching methods

Lectures
Tutorials
Project work

Summary

1 Introduction to econometrics (subject of econometrics, methodology of econometrics) 2. Simple linear regression function (the nature of regression analysis, the concept of population and sample regression function (deterministic and stochastic version), the method of ordinary least squares, coefficient of determination) 3. Statistical verification (testing of regression coefficients, the overall of sample regression model) 4. Autocorrelation (the nature, the consequences of autocorrelation, detection, removing). 5. Heteroscedasticity (the nature, its consequences, detection, removing, WOLS) 7. Multicollinearity (the nature, its consequences, detection, removing). 8. Model specification (model selection criteria, types of specification errors, consequences, tests) 9. Prediction (ex-post and ex-ante, mean and individual prediction, point and interval prediction). 10. Functional form of regression models (exponential regression model, semi log models and reciprocal models). 11. Dummy variable regression models.

Compulsory literature:

GUJARATI, Damodar N. Basic Econometrics. 4th ed. Singapore: Mc Graw-Hill, 2003, 1002 s. ISBN 0-07-233542-4. WOOLDRIDGE, Jeffrey M. Introductory Econometrics: A Modern Approach. 4th ed. Mason. Ohio: South Western Cengage Learning, 2008. 912 pp. ISBN 978-0-324-58162-1. RAMANATHAN, Ramu. Introductory Econometrics with Applications. 5th edition. Harcourt College Publishers, 2002. ISBN-13: 978-0030343421.

Recommended literature:

GREENE, William.H. Econometric Analysis. Pearson Education, 2008. ISBN 9780135137406. HEIJ, CH. et al: Econometrics Methods with Applications in Business and Economics. Oxford: Oxford University Press, 2004. ISBN 0-19-926801-0. WONNACOTT, R. J. and WONNACOTT, T.H. Econometrics. Florence Taylor and Francis Ann Arbor, Michigan ProQuest 2014.

Way of continuous check of knowledge in the course of semester

E-learning

Další požadavky na studenta

- Elaboration and defense of project with respect to the required structure. - Inserting of this project into the LMS and obtaining a simple majority of the number of points.

Prerequisities

Subject has no prerequisities.

Co-requisities

Subject has no co-requisities.

Subject syllabus:

1. Introduction to econometrics (subject of econometrics, methodology of econometrics). 2. Simple linear regression function (the nature of regression analysis, the concept of population and sample regression function (deterministic and stochastic version), the method of ordinary least squares, coefficient of determination). 3. Statistical verification (testing of regression coefficients, the overall of sample regression model). 4. Autocorrelation (the nature, the consequences of autocorrelation, detection, removing). 5. Heteroscedasticity (the nature, its consequences, detection, removing, WOLS). 7. Multicollinearity (the nature, its consequences, detection, removing). 8. Model specification (model selection criteria, types of specification errors, consequences, tests). 9. Prediction (ex-post and ex-ante, mean and individual prediction, point and interval prediction). 10. Functional form of regression models (exponential regression model, semi log models and reciprocal models). 11. Dummy variable regression models.

Conditions for subject completion

Full-time form (validity from: 2013/2014 Winter semester)
Task nameType of taskMax. number of points
(act. for subtasks)
Min. number of points
Exercises evaluation Credit 85  23
Mandatory attendence parzicipation:

Show history

Occurrence in study plans

Academic yearProgrammeField of studySpec.FormStudy language Tut. centreYearWSType of duty
2018/2019 (N6202) Economic Policy and Administration (6210T004) European Integration P Czech Ostrava 1 Compulsory study plan
2017/2018 (N6202) Economic Policy and Administration (6210T004) European Integration P Czech Ostrava 1 Compulsory study plan
2016/2017 (N6202) Economic Policy and Administration (6210T004) European Integration P Czech Ostrava 1 Compulsory study plan
2015/2016 (N6202) Economic Policy and Administration (6210T004) European Integration P Czech Ostrava 1 Compulsory study plan
2014/2015 (N6202) Economic Policy and Administration (6210T004) European Integration P Czech Ostrava 1 Compulsory study plan

Occurrence in special blocks

Block nameAcademic yearForm of studyStudy language YearWSType of blockBlock owner
Subject block without study plan - EKF - P - cs 2019/2020 Full-time Czech Optional EKF - Faculty of Economics stu. block