157-0360/01 – Econometrics (EKON)
| 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 | Compulsory |
| Year | 2 | Semester | winter |
| | Study language | Czech |
| Year of introduction | 2004/2005 | Year of cancellation | |
| Intended for the faculties | EKF | Intended for study types | Follow-up Master |
Subject aims expressed by acquired skills and competences
The aim of the subject is to master the process of econometric modeling with a focus on economic interpretation, verification of the model and its subsequent use in practice in management and decision-making at the micro and macro level.
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:
Recommended literature:
Way of continuous check of knowledge in the course of semester
Elaboration of a semester project on econometric modeling on a selected topic by the student.
The oral exam includes the defense of the semester project and 2 questions verifying knowledge of econometrics.
E-learning
Presentations for individual lectures in LMS Moodle.
Supporting materials for exercises - presentations, examples, results.
Inserting a semester project.
Other requirements
Preparation of a semester project according to the required structure, submission in the LMS by the end of January and obtaining more than half the number of points (30-50 pages).
Prerequisities
Subject has no prerequisities.
Co-requisities
Subject has no co-requisities.
Subject syllabus:
1. Introduction to econometrics (subject of economterics, metodology 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 od 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 (exponencial regression model, semilog models, reciprocal models).
11. Dummy variable regression models.
Conditions for subject completion
Occurrence in study plans
Occurrence in special blocks
Assessment of instruction