Gurantor department | Department of Systems Engineering | Credits | 5 |

Subject guarantor | prof. Ing. Jana Hančlová, CSc. | Subject version guarantor | prof. Ing. Jana Hančlová, CSc. |

Study level | undergraduate or graduate | Requirement | Choice-compulsory |

Year | 3 | Semester | winter |

Study language | English | ||

Year of introduction | 2015/2016 | Year of cancellation | |

Intended for the faculties | EKF | Intended for study types | Bachelor |

Instruction secured by | |||
---|---|---|---|

Login | Name | Tuitor | Teacher giving lectures |

CHY0034 | Mgr. Ing. Lucie Chytilová, Ph.D. | ||

HAN60 | prof. Ing. Jana Hančlová, CSc. |

Extent of instruction for forms of study | ||
---|---|---|

Form of study | Way of compl. | Extent |

Full-time | Examination | 1+2 |

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.

Lectures

Individual consultations

Tutorials

1. Time series analysis (the basic characteristics, graphical time series analysis, time series transformation, decomposition of time series)
2. Linear regression models (model formulation, estimation, specification, assumptions, OLS methods)
3. Verification of the estimated regression model (statistical verification, autocorrelation, heteroscedasticity, multicollinearity, economic verification).
4.Forecasting (prediction typology, point and interval prediction, prediction of ex-post and ex ante, forecasting accuracy rate).
5.Testing of residual normality (graphical tests, sophisticated tests).

1. GUJARATI, D.N. Basic Econometrics. 4th Ed., Singapore: Mc Graw-Hill, 2003. ISBN 0-07-233542-4.
2. LMCS Moodle: http://moodle.vsb.cz/vyuka
3. WOOLDRIDGE, J. Introductory Econometrics: A Modern Approach (with Economic Applications Online, Econometrics Data Sets with Solutions Manual, Web Site Printed Access Card), Student Solutions Manual Printed Access Card.). 4th ed. Mason. Ohio: South Western Cengage Learning, 2008. ISBN 9780324581621.

1. BROOKS, CH.: Introductory econometrics for finance. Cambridge: Cambridge University Press, 2002. ISBN 0-521-79018-2.
2. HEIJ, CH. et al: Econometrics Methods with Applications in Business and Economics. Oxford: Oxford University Press, 2004. ISBN 0-19-926801-0.
3. RAMANATHAN, R. Introductory Econometrics with Applications. 5th edition. Harcourt College Publishers, 2002. ISBN-13: 978-0030343421.

Course Requirement Summary
Attendance
• lectures – 60 %
• exercises – 80 %
Project
• submission - printed version to teacher + electronic version into LMS (until January 31, 2019 to obtain 23-45 points
• maximum point is 45, required number of points to pass credit is 23.
Final oral exam
• student will be asked to present his/her project, to justify the choice of the project and explain the procedure and his/her results,
• additional questions from the course outline will be asked,
• minimum number of points to pass the final examination is 28, maximum points of project presentation and the oral exam is 55.
Minimum number of points to pass Econometrics course is 51, maximum is 100.
The term econometrics project - passing term project is compulsory in order to get to the examination stage and obtaining the final grade. Submitting the individual term project in the required structure 1 week before exam to LMS.
The structure of the project:
1. Introduction, contents, goal of your project. (max 2 points)
2. Statement of theory or hypothesis for economic model. (max 2 points)
3. Data sources, data analysis, data graph and description of the development. (max 4 points)
4. Estimation of the econometric model using example data. (max 3 points)
5. Statistical verification of the parameters and model. (max 5 points)
6. Econometric verification of the model (checking the underlying assumptions autocorrelation (max 5 points), heteroscedasticity (max 5 points), multicollinearity (max 3 points), normality (max 3 points).
7. Specification of the econometric model. (max 4 points).
8. Economic verification and interpretation. (max 4 points)

Course Requirement Summary
Attendance
• lectures – 60 % recommended
• exercises – 80 %
Project
• submission - printed version to teacher + electronic version into LMS (until January 31, 2019 to obtain 23-45 points
• maximum point is 45, required number of points to pass credit is 23.
Final oral exam
• student will be asked to present his/her project, to justify the choice of the project and explain the procedure and his/her results,
• additional questions from the course outline will be asked,
• minimum number of points to pass the final examination is 28, maximum points of project presentation and the oral exam is 55.
Minimum number of points to pass Econometrics course is 51, maximum is 100.

Subject has no prerequisities.

Subject has no co-requisities.

The goal of INECON is to:
• be able to describe and apply the process of analysing of economic time series,
• understand the process of modelling the behaviour of economic system based on regression analysis,
• select and use appropriate econometrics methodology - the formulation, estimation, prediction and verification of modelled systems,
• explain the context of the theoretical behaviour of economic systems modelled with empirical results and make appropriate modification of your model,
• use the estimated regression models for forecasting.
1. Time series analysis (the basic characteristics, graphical time series analysis, time series transformation, decomposition of time series)
2. Linear regression models (model formulation, estimation, specification, assumptions, OLS methods)
3. Verification of the estimated regression model (statistical verification, autocorrelation, heteroscedasticity, multicollinearity, normality, specification, economic verification).
4. Forecasting (prediction typology, point and interval prediction, prediction of ex-post and ex ante, forecasting accuracy rate).

Task name | Type of task | Max. number of points
(act. for subtasks) | Min. number of points |
---|---|---|---|

Examination | Examination | 100 (100) | 51 |

Individual term project | Semestral project | 45 | 23 |

examination | Oral examination | 55 | 28 |

Show history

Academic year | Programme | Field of study | Spec. | Zaměření | Form | Study language | Tut. centre | Year | W | S | Type of duty | |
---|---|---|---|---|---|---|---|---|---|---|---|---|

2019/2020 | (B6208) Economics and Management | (6208R174) European Business Studies | P | English | Ostrava | 3 | Choice-compulsory | study plan | ||||

2017/2018 | (B6208) Economics and Management | (6208R174) European Business Studies | P | English | Ostrava | 3 | Choice-compulsory | study plan | ||||

2016/2017 | (B6208) Economics and Management | (6208R174) European Business Studies | P | English | Ostrava | 3 | Choice-compulsory | study plan | ||||

2015/2016 | (B6208) Economics and Management | (6208R174) European Business Studies | P | English | Ostrava | 3 | Choice-compulsory | study plan |

Block name | Academic year | Form of study | Study language | Year | W | S | Type of block | Block owner | |
---|---|---|---|---|---|---|---|---|---|

Incoming students - bachelor study | 2019/2020 | Full-time | English | Choice-compulsory | 163 - International Office | stu. block | |||

Incoming students - bachelor study | 2018/2019 | Full-time | English | Choice-compulsory | 163 - International Office | stu. block | |||

Incoming Students | 2017/2018 | Full-time | English | Choice-compulsory | 163 - International Office | stu. block | |||

Incoming Students | 2016/2017 | Full-time | English | Choice-compulsory | 163 - International Office | stu. block | |||

Incoming Students | 2015/2016 | Full-time | English | Choice-compulsory | 163 - International Office | stu. block |