157-0588/02 – Introduction to Econometrics (INECON)

Gurantor departmentDepartment of Systems EngineeringCredits5
Subject guarantorprof. Ing. Jana Hančlová, CSc.Subject version guarantorprof. Ing. Jana Hančlová, CSc.
Study levelundergraduate or graduate
Study languageEnglish
Year of introduction2015/2016Year of cancellation
Intended for the facultiesEKFIntended for study typesBachelor
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 Examination 1+2

Subject aims expressed by acquired skills and competences

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.

Teaching methods

Lectures
Individual consultations
Tutorials
Project work

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.

Compulsory literature:

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 literature:

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.

Way of continuous check of knowledge in the course of semester

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)

E-learning

Other requirements

The conditions for completing the course are to obtain at least 23 points from the credit project, participation in the exercises at least 80%, oral exam at least 28 points out of 55, ie to obtain 51 points out of 100.

Prerequisities

Subject has no prerequisities.

Co-requisities

Subject has no co-requisities.

Subject syllabus:

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).

Conditions for subject completion

Full-time form (validity from: 2017/2018 Winter semester)
Task nameType of taskMax. 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
Mandatory attendence parzicipation: The conditions for completing the course are to obtain at least 23 points from the credit project, participation in the exercises at least 80%, oral exam at least 28 points out of 55, ie to obtain 51 points out of 100.

Show history

Occurrence in study plans

Academic yearProgrammeField of studySpec.ZaměřeníFormStudy language Tut. centreYearWSType of duty
2020/2021 (B6208) Economics and Management (6208R174) European Business Studies P English Ostrava 3 Choice-compulsory study plan
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

Occurrence in special blocks

Block nameAcademic yearForm of studyStudy language YearWSType of blockBlock owner
Incoming students 2021/2022 Full-time English Choice-compulsory 163 - International Office stu. block
Incoming students - bachelor study 2020/2021 Full-time English Choice-compulsory 163 - International Office stu. block
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