BKE_ZAEK Introduction to Econometrics
Faculty of Economics and AdministrationAutumn 2023
- Extent and Intensity
- 26/0/0. 8 credit(s). Type of Completion: zk (examination).
Taught in person. - Teacher(s)
- doc. Ing. Daniel Němec, Ph.D. (lecturer)
- Guaranteed by
- doc. Ing. Daniel Němec, Ph.D.
Department of Economics – Faculty of Economics and Administration
Contact Person: Mgr. Jarmila Šveňhová
Supplier department: Department of Economics – Faculty of Economics and Administration - Timetable
- Sat 14. 10. 12:00–15:50 P302b, Sat 25. 11. 12:00–15:50 P302b, Fri 15. 12. 16:00–19:50 P302b
- Prerequisites
- FORMA ( K )
elementary probability and mathematical statistics - Course Enrolment Limitations
- The course is only offered to the students of the study fields the course is directly associated with.
- fields of study / plans the course is directly associated with
- Course objectives
- The course is designed to give students experience of using econometric methods important in economics, finance and other business subjects. It provides skills in regression essential for understanding much of the literature of economics, finance, and empirical studies in other areas of business.
We begin with the simple regression and multiple regression models. They are treated in depth and in range of applications. Careful attention is given to the interpretations of regression results and hypothesis testing. A part of the course introduces various modern tools for analyzing economic time series regression. Moreover, further topics in regression analysis are presented including regression with panel data and binary dependent variable.
By the end of the course students should be able to use regression models in many different applications, and to critically examine reported regression results in empirical research in economics and other business studies. They will be able to identify and deal with a number of econometric problems in the analysis of time series and cross-section data, and will have experience of a range of basic econometric methods. - Learning outcomes
- The course is designed to give students an understanding of why econometrics is necessary and to provide them with a working knowledge of basic econometric tools so that:
They can apply these tools to modeling, estimation, inference, and forecasting in the context of real world economic problems.
They can evaluate critically the results and conclusions from others who use basic econometric tools.
They have a foundation and understanding for further study of econometrics.
They have an appreciation of the range of more advanced techniques that exists and that may be covered in later econometric courses. - Syllabus
- PART 1
- 1. Introduction to econometrics and working with data
- 2. A non-technical introduction to regression
- 3. Simple regression model
- 4. Multiple regression model
- PART 2
- 5. Freeing up the classical assumptions - heteroskedasticity
- 6. Freeing up the classical assumptions - autocorrelated errors
- 7. Instrumental variables method
- PART 3
- 8. Models for panel data
- 9. Qualitative choice and limited dependent variable models
- 10. Univariate time series analysis
- 11. Regression with time series variables
- 12. Vector autoregressive models
- 13. Other models, methods and issues
- Literature
- required literature
- KOOP, Gary. Introduction to econometrics. Chichester: John Wiley & Sons, 2008, 371 s. ISBN 9780470032701. info
- recommended literature
- HILL, R. Carter, William E. GRIFFITHS and Guay C. LIM. Principles of econometrics. Fifth edition. Hoboken: Wiley Custom, 2018, xxvi, 878. ISBN 9781119510567. info
- HEISS, Florian. Using R for introductory econometrics. 2nd edition. Düsseldorf: Florian Heiss, 2020, 368 stran. ISBN 9788648424364. info
- WOOLDRIDGE, Jeffrey M. Introductory econometrics : a modern approach. Seventh edition. Boston: Cengage Learning, 2020, xxi, 826. ISBN 9781337558860. info
- CIPRA, Tomáš. Finanční ekonometrie. 1. vyd. Praha: Ekopress, 2008, 538 s. ISBN 9788086929439. info
- HEISS, Florian and Daniel BRUNNER. Using Python for introductory econometrics. 1st edition. Düsseldorf: Florian Heiss, 2020, 418 stran. ISBN 9788648436763. info
- Teaching methods
- lectures, class discussion, computer labs practices, drills
- Assessment methods
- final project, written and oral exam
- Language of instruction
- Czech
- Further comments (probably available only in Czech)
- The course is taught last offered.
General note: Přednášky jsou dostupné online a ze záznamu.
Information on the extent and intensity of the course: tutorial 12 hodin.
BKE_ZAEK Introduction to Econometrics
Faculty of Economics and AdministrationAutumn 2022
- Extent and Intensity
- 26/0/0. 8 credit(s). Type of Completion: zk (examination).
Taught in person. - Teacher(s)
- doc. Ing. Daniel Němec, Ph.D. (lecturer)
- Guaranteed by
- doc. Ing. Daniel Němec, Ph.D.
Department of Economics – Faculty of Economics and Administration
Contact Person: Mgr. Jarmila Šveňhová
Supplier department: Department of Economics – Faculty of Economics and Administration - Timetable
- Sat 22. 10. 12:00–15:50 P104, Fri 11. 11. 16:00–19:50 P106, Sat 10. 12. 8:00–11:50 P103
- Prerequisites
- elementary probability and mathematical statistics
- Course Enrolment Limitations
- The course is also offered to the students of the fields other than those the course is directly associated with.
- fields of study / plans the course is directly associated with
- Course objectives
- The course is designed to give students experience of using econometric methods important in economics, finance and other business subjects. It provides skills in regression essential for understanding much of the literature of economics, finance, and empirical studies in other areas of business.
We begin with the simple regression and multiple regression models. They are treated in depth and in range of applications. Careful attention is given to the interpretations of regression results and hypothesis testing. A part of the course introduces various modern tools for analyzing economic time series regression. Moreover, further topics in regression analysis are presented including regression with panel data and binary dependent variable.
By the end of the course students should be able to use regression models in many different applications, and to critically examine reported regression results in empirical research in economics and other business studies. They will be able to identify and deal with a number of econometric problems in the analysis of time series and cross-section data, and will have experience of a range of basic econometric methods. - Learning outcomes
- The course is designed to give students an understanding of why econometrics is necessary and to provide them with a working knowledge of basic econometric tools so that:
They can apply these tools to modeling, estimation, inference, and forecasting in the context of real world economic problems.
They can evaluate critically the results and conclusions from others who use basic econometric tools.
They have a foundation and understanding for further study of econometrics.
They have an appreciation of the range of more advanced techniques that exists and that may be covered in later econometric courses. - Syllabus
- PART 1
- 1. Introduction to econometrics and working with data
- 2. A non-technical introduction to regression
- 3. Simple regression model
- 4. Multiple regression model
- PART 2
- 5. Freeing up the classical assumptions - heteroskedasticity
- 6. Freeing up the classical assumptions - autocorrelated errors
- 7. Instrumental variables method
- PART 3
- 8. Models for panel data
- 9. Qualitative choice and limited dependent variable models
- 10. Univariate time series analysis
- 11. Regression with time series variables
- 12. Vector autoregressive models
- 13. Other models, methods and issues
- Literature
- required literature
- KOOP, Gary. Introduction to econometrics. Chichester: John Wiley & Sons, 2008, 371 s. ISBN 9780470032701. info
- CIPRA, Tomáš. Finanční ekonometrie. 1. vyd. Praha: Ekopress, 2008, 538 s. ISBN 9788086929439. info
- recommended literature
- HILL, R. Carter, William E. GRIFFITHS and Guay C. LIM. Principles of econometrics. 4th ed. Hoboken: John Wiley & Sons, 2012, xxvi, 758. ISBN 9780470873724. info
- not specified
- GUJARATI, Damodar N. and Dawn C. PORTER. Basic econometrics. 5th ed. Boston: McGraw-Hill, 2009, xx, 922. ISBN 9780071276252. info
- WOOLDRIDGE, Jeffrey M. Introductory econometrics : a modern approach. 4th ed. (International stude. Canada: South-Western, 2009, xx, 865. ISBN 9780324585483. info
- KENNEDY, Peter. A guide to econometrics. 6th ed. Malden: Blackwell, 2008, xii, 585. ISBN 9781405182584. info
- Teaching methods
- lectures, class discussion, computer labs practices, drills
- Assessment methods
- final project, written and oral exam
- Language of instruction
- Czech
- Further comments (probably available only in Czech)
- The course is taught annually.
General note: Přednášky jsou dostupné online a ze záznamu.
Information on the extent and intensity of the course: tutorial 12 hodin.
BKE_ZAEK Introduction to Econometrics
Faculty of Economics and AdministrationAutumn 2021
- Extent and Intensity
- 26/0/0. 8 credit(s). Type of Completion: zk (examination).
Taught in person. - Teacher(s)
- doc. Ing. Daniel Němec, Ph.D. (lecturer)
- Guaranteed by
- doc. Ing. Daniel Němec, Ph.D.
Department of Economics – Faculty of Economics and Administration
Contact Person: Mgr. Jarmila Šveňhová
Supplier department: Department of Economics – Faculty of Economics and Administration - Timetable
- Sat 23. 10. 16:00–19:50 P106, Fri 5. 11. 16:00–19:50 P106, Sat 4. 12. 8:00–11:50 P103
- Prerequisites
- elementary probability and mathematical statistics
- Course Enrolment Limitations
- The course is also offered to the students of the fields other than those the course is directly associated with.
- fields of study / plans the course is directly associated with
- Course objectives
- The course is designed to give students experience of using econometric methods important in economics, finance and other business subjects. It provides skills in regression essential for understanding much of the literature of economics, finance, and empirical studies in other areas of business.
We begin with the simple regression and multiple regression models. They are treated in depth and in range of applications. Careful attention is given to the interpretations of regression results and hypothesis testing. A part of the course introduces various modern tools for analyzing economic time series regression. Moreover, further topics in regression analysis are presented including regression with panel data and binary dependent variable.
By the end of the course students should be able to use regression models in many different applications, and to critically examine reported regression results in empirical research in economics and other business studies. They will be able to identify and deal with a number of econometric problems in the analysis of time series and cross-section data, and will have experience of a range of basic econometric methods. - Learning outcomes
- The course is designed to give students an understanding of why econometrics is necessary and to provide them with a working knowledge of basic econometric tools so that:
They can apply these tools to modeling, estimation, inference, and forecasting in the context of real world economic problems.
They can evaluate critically the results and conclusions from others who use basic econometric tools.
They have a foundation and understanding for further study of econometrics.
They have an appreciation of the range of more advanced techniques that exists and that may be covered in later econometric courses. - Syllabus
- PART 1
- 1. Introduction to econometrics and working with data
- 2. A non-technical introduction to regression
- 3. Simple regression model
- 4. Multiple regression model
- PART 2
- 5. Freeing up the classical assumptions - heteroskedasticity
- 6. Freeing up the classical assumptions - autocorrelated errors
- 7. Instrumental variables method
- PART 3
- 8. Models for panel data
- 9. Qualitative choice and limited dependent variable models
- 10. Univariate time series analysis
- 11. Regression with time series variables
- 12. Vector autoregressive models
- 13. Other models, methods and issues
- Literature
- required literature
- KOOP, Gary. Introduction to econometrics. Chichester: John Wiley & Sons, 2008, 371 s. ISBN 9780470032701. info
- CIPRA, Tomáš. Finanční ekonometrie. 1. vyd. Praha: Ekopress, 2008, 538 s. ISBN 9788086929439. info
- recommended literature
- HILL, R. Carter, William E. GRIFFITHS and Guay C. LIM. Principles of econometrics. 4th ed. Hoboken: John Wiley & Sons, 2012, xxvi, 758. ISBN 9780470873724. info
- not specified
- GUJARATI, Damodar N. and Dawn C. PORTER. Basic econometrics. 5th ed. Boston: McGraw-Hill, 2009, xx, 922. ISBN 9780071276252. info
- WOOLDRIDGE, Jeffrey M. Introductory econometrics : a modern approach. 4th ed. (International stude. Canada: South-Western, 2009, xx, 865. ISBN 9780324585483. info
- KENNEDY, Peter. A guide to econometrics. 6th ed. Malden: Blackwell, 2008, xii, 585. ISBN 9781405182584. info
- Teaching methods
- lectures, class discussion, computer labs practices, drills
- Assessment methods
- final project, written and oral exam
- Language of instruction
- Czech
- Further comments (probably available only in Czech)
- Study Materials
The course is taught annually.
General note: Přednášky jsou dostupné online a ze záznamu.
Information on the extent and intensity of the course: tutorial 12 hodin.
BKE_ZAEK Introduction to Econometrics
Faculty of Economics and AdministrationAutumn 2020
- Extent and Intensity
- 26/0. 8 credit(s). Type of Completion: zk (examination).
Taught online. - Teacher(s)
- doc. Ing. Daniel Němec, Ph.D. (lecturer)
prof. Ing. Osvald Vašíček, CSc. (lecturer)
Mgr. Hana Fitzová, Ph.D. (lecturer) - Guaranteed by
- doc. Ing. Daniel Němec, Ph.D.
Department of Economics – Faculty of Economics and Administration
Contact Person: Mgr. Jarmila Šveňhová
Supplier department: Department of Economics – Faculty of Economics and Administration - Timetable
- Sat 14. 11. 16:00–19:50 P106, Fri 27. 11. 16:00–19:50 P106, Sat 12. 12. 8:00–11:50 P103
- Prerequisites
- elementary probability and mathematical statistics
- Course Enrolment Limitations
- The course is also offered to the students of the fields other than those the course is directly associated with.
- fields of study / plans the course is directly associated with
- Course objectives
- The course is designed to give students experience of using econometric methods important in economics, finance and other business subjects. It provides skills in regression essential for understanding much of the literature of economics, finance, and empirical studies in other areas of business.
We begin with the simple regression and multiple regression models. They are treated in depth and in range of applications. Careful attention is given to the interpretations of regression results and hypothesis testing. A part of the course introduces various modern tools for analyzing economic time series regression. Moreover, further topics in regression analysis are presented including regression with panel data and binary dependent variable.
By the end of the course students should be able to use regression models in many different applications, and to critically examine reported regression results in empirical research in economics and other business studies. They will be able to identify and deal with a number of econometric problems in the analysis of time series and cross-section data, and will have experience of a range of basic econometric methods. - Learning outcomes
- The course is designed to give students an understanding of why econometrics is necessary and to provide them with a working knowledge of basic econometric tools so that:
They can apply these tools to modeling, estimation, inference, and forecasting in the context of real world economic problems.
They can evaluate critically the results and conclusions from others who use basic econometric tools.
They have a foundation and understanding for further study of econometrics.
They have an appreciation of the range of more advanced techniques that exists and that may be covered in later econometric courses. - Syllabus
- PART 1
- 1. Introduction to econometrics and working with data
- 2. A non-technical introduction to regression
- 3. Simple regression model
- 4. Multiple regression model
- PART 2
- 5. Freeing up the classical assumptions - heteroskedasticity
- 6. Freeing up the classical assumptions - autocorrelated errors
- 7. Instrumental variables method
- PART 3
- 8. Models for panel data
- 9. Qualitative choice and limited dependent variable models
- 10. Univariate time series analysis
- 11. Regression with time series variables
- 12. Vector autoregressive models
- 13. Other models, methods and issues
- Literature
- required literature
- KOOP, Gary. Introduction to econometrics. Chichester: John Wiley & Sons, 2008, 371 s. ISBN 9780470032701. info
- CIPRA, Tomáš. Finanční ekonometrie. 1. vyd. Praha: Ekopress, 2008, 538 s. ISBN 9788086929439. info
- recommended literature
- HILL, R. Carter, William E. GRIFFITHS and Guay C. LIM. Principles of econometrics. 4th ed. Hoboken: John Wiley & Sons, 2012, xxvi, 758. ISBN 9780470873724. info
- not specified
- GUJARATI, Damodar N. and Dawn C. PORTER. Basic econometrics. 5th ed. Boston: McGraw-Hill, 2009, xx, 922. ISBN 9780071276252. info
- WOOLDRIDGE, Jeffrey M. Introductory econometrics : a modern approach. 4th ed. (International stude. Canada: South-Western, 2009, xx, 865. ISBN 9780324585483. info
- KENNEDY, Peter. A guide to econometrics. 6th ed. Malden: Blackwell, 2008, xii, 585. ISBN 9781405182584. info
- Teaching methods
- lectures, class discussion, computer labs practices, drills
- Assessment methods
- final project, written and oral exam
- Language of instruction
- Czech
- Further comments (probably available only in Czech)
- The course is taught annually.
General note: Přednášky jsou dostupné online a ze záznamu.
Information on the extent and intensity of the course: tutorial 12 hodin.
BKE_ZAEK Introduction to Econometrics
Faculty of Economics and AdministrationAutumn 2019
- Extent and Intensity
- 26/0. 8 credit(s). Type of Completion: zk (examination).
- Teacher(s)
- doc. Ing. Daniel Němec, Ph.D. (lecturer)
prof. Ing. Osvald Vašíček, CSc. (lecturer)
Mgr. Hana Fitzová, Ph.D. (lecturer) - Guaranteed by
- doc. Ing. Daniel Němec, Ph.D.
Department of Economics – Faculty of Economics and Administration
Contact Person: Mgr. Jarmila Šveňhová
Supplier department: Department of Economics – Faculty of Economics and Administration - Timetable
- Sat 19. 10. 16:00–19:50 P106, Fri 8. 11. 16:00–19:50 P106, Sat 30. 11. 8:00–11:50 P103
- Prerequisites
- elementary probability and mathematical statistics
- Course Enrolment Limitations
- The course is also offered to the students of the fields other than those the course is directly associated with.
- fields of study / plans the course is directly associated with
- Course objectives
- The course is designed to give students experience of using econometric methods important in economics, finance and other business subjects. It provides skills in regression essential for understanding much of the literature of economics, finance, and empirical studies in other areas of business.
We begin with the simple regression and multiple regression models. They are treated in depth and in range of applications. Careful attention is given to the interpretations of regression results and hypothesis testing. A part of the course introduces various modern tools for analyzing economic time series regression. Moreover, further topics in regression analysis are presented including regression with panel data and binary dependent variable.
By the end of the course students should be able to use regression models in many different applications, and to critically examine reported regression results in empirical research in economics and other business studies. They will be able to identify and deal with a number of econometric problems in the analysis of time series and cross-section data, and will have experience of a range of basic econometric methods. - Learning outcomes
- The course is designed to give students an understanding of why econometrics is necessary and to provide them with a working knowledge of basic econometric tools so that:
They can apply these tools to modeling, estimation, inference, and forecasting in the context of real world economic problems.
They can evaluate critically the results and conclusions from others who use basic econometric tools.
They have a foundation and understanding for further study of econometrics.
They have an appreciation of the range of more advanced techniques that exists and that may be covered in later econometric courses. - Syllabus
- PART 1
- 1. Introduction to econometrics and working with data
- 2. A non-technical introduction to regression
- 3. Simple regression model
- 4. Multiple regression model
- PART 2
- 5. Freeing up the classical assumptions - heteroskedasticity
- 6. Freeing up the classical assumptions - autocorrelated errors
- 7. Instrumental variables method
- PART 3
- 8. Models for panel data
- 9. Qualitative choice and limited dependent variable models
- 10. Univariate time series analysis
- 11. Regression with time series variables
- 12. Vector autoregressive models
- 13. Other models, methods and issues
- Literature
- required literature
- KOOP, Gary. Introduction to econometrics. Chichester: John Wiley & Sons, 2008, 371 s. ISBN 9780470032701. info
- CIPRA, Tomáš. Finanční ekonometrie. 1. vyd. Praha: Ekopress, 2008, 538 s. ISBN 9788086929439. info
- recommended literature
- HILL, R. Carter, William E. GRIFFITHS and Guay C. LIM. Principles of econometrics. 4th ed. Hoboken: John Wiley & Sons, 2012, xxvi, 758. ISBN 9780470873724. info
- not specified
- GUJARATI, Damodar N. and Dawn C. PORTER. Basic econometrics. 5th ed. Boston: McGraw-Hill, 2009, xx, 922. ISBN 9780071276252. info
- WOOLDRIDGE, Jeffrey M. Introductory econometrics : a modern approach. 4th ed. (International stude. Canada: South-Western, 2009, xx, 865. ISBN 9780324585483. info
- KENNEDY, Peter. A guide to econometrics. 6th ed. Malden: Blackwell, 2008, xii, 585. ISBN 9781405182584. info
- Teaching methods
- lectures, class discussion, computer labs practices, drills
- Assessment methods
- final project, written and oral exam
- Language of instruction
- Czech
- Further comments (probably available only in Czech)
- Study Materials
The course is taught annually.
General note: Přednášky jsou dostupné online a ze záznamu.
Information on the extent and intensity of the course: tutorial 12 hodin.
BKE_ZAEK Introduction to Econometrics
Faculty of Economics and AdministrationAutumn 2018
- Extent and Intensity
- 0/0. 8 credit(s). Type of Completion: zk (examination).
- Teacher(s)
- doc. Ing. Daniel Němec, Ph.D. (lecturer)
prof. Ing. Osvald Vašíček, CSc. (lecturer)
Mgr. Hana Fitzová, Ph.D. (lecturer) - Guaranteed by
- doc. Ing. Daniel Němec, Ph.D.
Department of Economics – Faculty of Economics and Administration
Contact Person: Mgr. Jarmila Šveňhová
Supplier department: Department of Economics – Faculty of Economics and Administration - Timetable
- Sat 20. 10. 16:00–19:50 P106, Fri 9. 11. 16:00–19:50 P106, Sat 1. 12. 8:00–11:50 P103
- Prerequisites
- elementary probability and mathematical statistics
- Course Enrolment Limitations
- The course is also offered to the students of the fields other than those the course is directly associated with.
- fields of study / plans the course is directly associated with
- Finance (programme ESF, B-FU)
- Course objectives
- The course is designed to give students experience of using econometric methods important in economics, finance and other business subjects. It provides skills in regression essential for understanding much of the literature of economics, finance, and empirical studies in other areas of business.
We begin with the simple regression and multiple regression models. They are treated in depth and in range of applications. Careful attention is given to the interpretations of regression results and hypothesis testing. A part of the course introduces various modern tools for analyzing economic time series regression. Moreover, further topics in regression analysis are presented including regression with panel data and binary dependent variable.
By the end of the course students should be able to use regression models in many different applications, and to critically examine reported regression results in empirical research in economics and other business studies. They will be able to identify and deal with a number of econometric problems in the analysis of time series and cross-section data, and will have experience of a range of basic econometric methods.
The course is designed to give students an understanding of why econometrics is necessary and to provide them with a working knowledge of basic econometric tools so that:
They can apply these tools to modeling, estimation, inference, and forecasting in the context of real world economic problems.
They can evaluate critically the results and conclusions from others who use basic econometric tools.
They have a foundation and understanding for further study of econometrics.
They have an appreciation of the range of more advanced techniques that exists and that may be covered in later econometric courses. - Syllabus
- PART 1
- 1. Introduction to econometrics and working with data
- 2. A non-technical introduction to regression
- 3. Simple regression model
- 4. Multiple regression model
- PART 2
- 5. Freeing up the classical assumptions - heteroskedasticity
- 6. Freeing up the classical assumptions - autocorrelated errors
- 7. Instrumental variables method
- PART 3
- 8. Models for panel data
- 9. Qualitative choice and limited dependent variable models
- 10. Univariate time series analysis
- 11. Regression with time series variables
- 12. Vector autoregressive models
- 13. Other models, methods and issues
- Literature
- required literature
- KOOP, Gary. Introduction to econometrics. Chichester: John Wiley & Sons, 2008, 371 s. ISBN 9780470032701. info
- CIPRA, Tomáš. Finanční ekonometrie. 1. vyd. Praha: Ekopress, 2008, 538 s. ISBN 9788086929439. info
- recommended literature
- HILL, R. Carter, William E. GRIFFITHS and Guay C. LIM. Principles of econometrics. 4th ed. Hoboken: John Wiley & Sons, 2012, xxvi, 758. ISBN 9780470873724. info
- not specified
- GUJARATI, Damodar N. and Dawn C. PORTER. Basic econometrics. 5th ed. Boston: McGraw-Hill, 2009, xx, 922. ISBN 9780071276252. info
- WOOLDRIDGE, Jeffrey M. Introductory econometrics : a modern approach. 4th ed. (International stude. Canada: South-Western, 2009, xx, 865. ISBN 9780324585483. info
- KENNEDY, Peter. A guide to econometrics. 6th ed. Malden: Blackwell, 2008, xii, 585. ISBN 9781405182584. info
- Teaching methods
- lectures, class discussion, computer labs practices, drills
- Assessment methods
- final project, written and oral exam
- Language of instruction
- Czech
- Further comments (probably available only in Czech)
- The course is taught annually.
BKE_ZAEK Introduction to Econometrics
Faculty of Economics and AdministrationAutumn 2017
- Extent and Intensity
- 0/0. 8 credit(s). Type of Completion: zk (examination).
- Teacher(s)
- doc. Ing. Daniel Němec, Ph.D. (lecturer)
prof. Ing. Osvald Vašíček, CSc. (lecturer)
Mgr. Hana Fitzová, Ph.D. (lecturer) - Guaranteed by
- doc. Ing. Daniel Němec, Ph.D.
Department of Economics – Faculty of Economics and Administration
Contact Person: Mgr. Jarmila Šveňhová
Supplier department: Department of Economics – Faculty of Economics and Administration - Timetable
- Sat 21. 10. 16:20–19:35 P106, Fri 3. 11. 16:20–19:35 P106, Sat 2. 12. 8:30–11:50 P103
- Prerequisites
- elementary probability and mathematical statistics
- Course Enrolment Limitations
- The course is also offered to the students of the fields other than those the course is directly associated with.
- fields of study / plans the course is directly associated with
- Finance (programme ESF, B-FU)
- Course objectives
- The course is designed to give students experience of using econometric methods important in economics, finance and other business subjects. It provides skills in regression essential for understanding much of the literature of economics, finance, and empirical studies in other areas of business.
We begin with the simple regression and multiple regression models. They are treated in depth and in range of applications. Careful attention is given to the interpretations of regression results and hypothesis testing. A part of the course introduces various modern tools for analyzing economic time series regression. Moreover, further topics in regression analysis are presented including regression with panel data and binary dependent variable.
By the end of the course students should be able to use regression models in many different applications, and to critically examine reported regression results in empirical research in economics and other business studies. They will be able to identify and deal with a number of econometric problems in the analysis of time series and cross-section data, and will have experience of a range of basic econometric methods.
The course is designed to give students an understanding of why econometrics is necessary and to provide them with a working knowledge of basic econometric tools so that:
They can apply these tools to modeling, estimation, inference, and forecasting in the context of real world economic problems.
They can evaluate critically the results and conclusions from others who use basic econometric tools.
They have a foundation and understanding for further study of econometrics.
They have an appreciation of the range of more advanced techniques that exists and that may be covered in later econometric courses. - Syllabus
- PART 1
- 1. Introduction to econometrics and working with data
- 2. A non-technical introduction to regression
- 3. Simple regression model
- 4. Multiple regression model
- PART 2
- 5. Freeing up the classical assumptions - heteroskedasticity
- 6. Freeing up the classical assumptions - autocorrelated errors
- 7. Instrumental variables method
- PART 3
- 8. Models for panel data
- 9. Qualitative choice and limited dependent variable models
- 10. Univariate time series analysis
- 11. Regression with time series variables
- 12. Vector autoregressive models
- 13. Other models, methods and issues
- Literature
- required literature
- KOOP, Gary. Introduction to econometrics. Chichester: John Wiley & Sons, 2008, 371 s. ISBN 9780470032701. info
- CIPRA, Tomáš. Finanční ekonometrie. 1. vyd. Praha: Ekopress, 2008, 538 s. ISBN 9788086929439. info
- recommended literature
- HILL, R. Carter, William E. GRIFFITHS and Guay C. LIM. Principles of econometrics. 4th ed. Hoboken: John Wiley & Sons, 2012, xxvi, 758. ISBN 9780470873724. info
- not specified
- GUJARATI, Damodar N. and Dawn C. PORTER. Basic econometrics. 5th ed. Boston: McGraw-Hill, 2009, xx, 922. ISBN 9780071276252. info
- WOOLDRIDGE, Jeffrey M. Introductory econometrics : a modern approach. 4th ed. (International stude. Canada: South-Western, 2009, xx, 865. ISBN 9780324585483. info
- KENNEDY, Peter. A guide to econometrics. 6th ed. Malden: Blackwell, 2008, xii, 585. ISBN 9781405182584. info
- Teaching methods
- lectures, class discussion, computer labs practices, drills
- Assessment methods
- final project, written and oral exam
- Language of instruction
- Czech
- Further comments (probably available only in Czech)
- Study Materials
The course is taught annually.
BKE_ZAEK Introduction to Econometrics
Faculty of Economics and AdministrationAutumn 2016
- Extent and Intensity
- 0/0. 8 credit(s). Type of Completion: zk (examination).
- Teacher(s)
- doc. Ing. Daniel Němec, Ph.D. (lecturer)
prof. Ing. Osvald Vašíček, CSc. (lecturer)
Mgr. Hana Fitzová, Ph.D. (lecturer) - Guaranteed by
- doc. Ing. Daniel Němec, Ph.D.
Department of Economics – Faculty of Economics and Administration
Contact Person: Mgr. Jarmila Šveňhová
Supplier department: Department of Economics – Faculty of Economics and Administration - Timetable
- Sat 22. 10. 16:20–19:35 P106, Fri 11. 11. 16:20–19:35 P106, Sat 3. 12. 8:30–11:50 P103
- Prerequisites
- elementary probability and mathematical statistics
- Course Enrolment Limitations
- The course is also offered to the students of the fields other than those the course is directly associated with.
- fields of study / plans the course is directly associated with
- Finance (programme ESF, B-FU)
- Course objectives
- The course is designed to give students experience of using econometric methods important in economics, finance and other business subjects. It provides skills in regression essential for understanding much of the literature of economics, finance, and empirical studies in other areas of business.
We begin with the simple regression and multiple regression models. They are treated in depth and in range of applications. Careful attention is given to the interpretations of regression results and hypothesis testing. A part of the course introduces various modern tools for analyzing economic time series regression. Moreover, further topics in regression analysis are presented including regression with panel data and binary dependent variable.
By the end of the course students should be able to use regression models in many different applications, and to critically examine reported regression results in empirical research in economics and other business studies. They will be able to identify and deal with a number of econometric problems in the analysis of time series and cross-section data, and will have experience of a range of basic econometric methods.
The course is designed to give students an understanding of why econometrics is necessary and to provide them with a working knowledge of basic econometric tools so that:
They can apply these tools to modeling, estimation, inference, and forecasting in the context of real world economic problems.
They can evaluate critically the results and conclusions from others who use basic econometric tools.
They have a foundation and understanding for further study of econometrics.
They have an appreciation of the range of more advanced techniques that exists and that may be covered in later econometric courses. - Syllabus
- PART 1
- 1. Introduction to econometrics and working with data
- 2. A non-technical introduction to regression
- 3. Simple regression model
- 4. Multiple regression model
- PART 2
- 5. Freeing up the classical assumptions - heteroskedasticity
- 6. Freeing up the classical assumptions - autocorrelated errors
- 7. Instrumental variables method
- PART 3
- 8. Models for panel data
- 9. Qualitative choice and limited dependent variable models
- 10. Univariate time series analysis
- 11. Regression with time series variables
- 12. Vector autoregressive models
- 13. Other models, methods and issues
- Literature
- required literature
- KOOP, Gary. Introduction to econometrics. Chichester: John Wiley & Sons, 2008, 371 s. ISBN 9780470032701. info
- CIPRA, Tomáš. Finanční ekonometrie. 1. vyd. Praha: Ekopress, 2008, 538 s. ISBN 9788086929439. info
- recommended literature
- HILL, R. Carter, William E. GRIFFITHS and Guay C. LIM. Principles of econometrics. 4th ed. Hoboken: John Wiley & Sons, 2012, xxvi, 758. ISBN 9780470873724. info
- not specified
- GUJARATI, Damodar N. and Dawn C. PORTER. Basic econometrics. 5th ed. Boston: McGraw-Hill, 2009, xx, 922. ISBN 9780071276252. info
- WOOLDRIDGE, Jeffrey M. Introductory econometrics : a modern approach. 4th ed. (International stude. Canada: South-Western, 2009, xx, 865. ISBN 9780324585483. info
- KENNEDY, Peter. A guide to econometrics. 6th ed. Malden: Blackwell, 2008, xii, 585. ISBN 9781405182584. info
- Teaching methods
- lectures, class discussion, computer labs practices, drills
- Assessment methods
- final project, written and oral exam
- Language of instruction
- Czech
- Further comments (probably available only in Czech)
- Study Materials
The course is taught annually. - Information about innovation of course.
- This course has been innovated under the project "Inovace studia ekonomických disciplín v souladu s požadavky znalostní ekonomiky (CZ.1.07/2.2.00/28.0227)" which is cofinanced by the European Social Fond and the national budget of the Czech Republic.
BKE_ZAEK Introduction to Econometrics
Faculty of Economics and AdministrationAutumn 2015
- Extent and Intensity
- 0/0. 8 credit(s). Type of Completion: zk (examination).
- Teacher(s)
- doc. Ing. Daniel Němec, Ph.D. (lecturer)
prof. Ing. Osvald Vašíček, CSc. (lecturer)
Mgr. Hana Fitzová, Ph.D. (lecturer) - Guaranteed by
- doc. Ing. Daniel Němec, Ph.D.
Department of Economics – Faculty of Economics and Administration
Contact Person: Lydie Pravdová
Supplier department: Department of Economics – Faculty of Economics and Administration - Timetable
- Sat 24. 10. 16:20–19:35 P106, Fri 13. 11. 16:20–19:35 P106, Sat 5. 12. 8:30–11:50 P103
- Prerequisites
- elementary probability and mathematical statistics
- Course Enrolment Limitations
- The course is also offered to the students of the fields other than those the course is directly associated with.
- fields of study / plans the course is directly associated with
- Finance (programme ESF, B-FU)
- Course objectives
- The course is designed to give students experience of using econometric methods important in economics, finance and other business subjects. It provides skills in regression essential for understanding much of the literature of economics, finance, and empirical studies in other areas of business.
We begin with the simple regression and multiple regression models. They are treated in depth and in range of applications. Careful attention is given to the interpretations of regression results and hypothesis testing. A part of the course introduces various modern tools for analyzing economic time series regression. Moreover, further topics in regression analysis are presented including regression with panel data and binary dependent variable.
By the end of the course students should be able to use regression models in many different applications, and to critically examine reported regression results in empirical research in economics and other business studies. They will be able to identify and deal with a number of econometric problems in the analysis of time series and cross-section data, and will have experience of a range of basic econometric methods.
The course is designed to give students an understanding of why econometrics is necessary and to provide them with a working knowledge of basic econometric tools so that:
They can apply these tools to modeling, estimation, inference, and forecasting in the context of real world economic problems.
They can evaluate critically the results and conclusions from others who use basic econometric tools.
They have a foundation and understanding for further study of econometrics.
They have an appreciation of the range of more advanced techniques that exists and that may be covered in later econometric courses. - Syllabus
- PART 1
- 1. Introduction to econometrics and working with data
- 2. A non-technical introduction to regression
- 3. Simple regression model
- 4. Multiple regression model
- PART 2
- 5. Freeing up the classical assumptions - heteroskedasticity
- 6. Freeing up the classical assumptions - autocorrelated errors
- 7. Instrumental variables method
- PART 3
- 8. Models for panel data
- 9. Qualitative choice and limited dependent variable models
- 10. Univariate time series analysis
- 11. Regression with time series variables
- 12. Vector autoregressive models
- 13. Other models, methods and issues
- Literature
- required literature
- KOOP, Gary. Introduction to econometrics. Chichester: John Wiley & Sons, 2008, 371 s. ISBN 9780470032701. info
- CIPRA, Tomáš. Finanční ekonometrie. 1. vyd. Praha: Ekopress, 2008, 538 s. ISBN 9788086929439. info
- recommended literature
- HILL, R. Carter, William E. GRIFFITHS and Guay C. LIM. Principles of econometrics. 4th ed. Hoboken: John Wiley & Sons, 2012, xxvi, 758. ISBN 9780470873724. info
- not specified
- GUJARATI, Damodar N. and Dawn C. PORTER. Basic econometrics. 5th ed. Boston: McGraw-Hill, 2009, xx, 922. ISBN 9780071276252. info
- WOOLDRIDGE, Jeffrey M. Introductory econometrics : a modern approach. 4th ed. (International stude. Canada: South-Western, 2009, xx, 865. ISBN 9780324585483. info
- KENNEDY, Peter. A guide to econometrics. 6th ed. Malden: Blackwell, 2008, xii, 585. ISBN 9781405182584. info
- Teaching methods
- lectures, class discussion, computer labs practices, drills
- Assessment methods
- final project, written and oral exam
- Language of instruction
- Czech
- Further comments (probably available only in Czech)
- Study Materials
The course is taught annually. - Information about innovation of course.
- This course has been innovated under the project "Inovace studia ekonomických disciplín v souladu s požadavky znalostní ekonomiky (CZ.1.07/2.2.00/28.0227)" which is cofinanced by the European Social Fond and the national budget of the Czech Republic.
BKE_ZAEK Introduction to Econometrics
Faculty of Economics and AdministrationAutumn 2014
- Extent and Intensity
- 0/0. 8 credit(s). Type of Completion: zk (examination).
- Teacher(s)
- doc. Ing. Daniel Němec, Ph.D. (lecturer)
prof. Ing. Osvald Vašíček, CSc. (lecturer)
Mgr. Hana Fitzová, Ph.D. (lecturer) - Guaranteed by
- doc. Ing. Daniel Němec, Ph.D.
Department of Economics – Faculty of Economics and Administration
Contact Person: Lydie Pravdová
Supplier department: Department of Economics – Faculty of Economics and Administration - Timetable
- Sat 25. 10. 16:20–19:35 P106, Sun 9. 11. 16:20–19:35 P106, Sat 6. 12. 8:30–11:50 P103
- Prerequisites
- elementary probability and mathematical statistics
- Course Enrolment Limitations
- The course is also offered to the students of the fields other than those the course is directly associated with.
- fields of study / plans the course is directly associated with
- Finance (programme ESF, B-FU)
- Course objectives
- The course is designed to give students experience of using econometric methods important in economics, finance and other business subjects. It provides skills in regression essential for understanding much of the literature of economics, finance, and empirical studies in other areas of business.
We begin with the simple regression and multiple regression models. They are treated in depth and in range of applications. Careful attention is given to the interpretations of regression results and hypothesis testing. A part of the course introduces various modern tools for analyzing economic time series regression. Moreover, further topics in regression analysis are presented including regression with panel data and binary dependent variable.
By the end of the course students should be able to use regression models in many different applications, and to critically examine reported regression results in empirical research in economics and other business studies. They will be able to identify and deal with a number of econometric problems in the analysis of time series and cross-section data, and will have experience of a range of basic econometric methods.
The course is designed to give students an understanding of why econometrics is necessary and to provide them with a working knowledge of basic econometric tools so that:
They can apply these tools to modeling, estimation, inference, and forecasting in the context of real world economic problems.
They can evaluate critically the results and conclusions from others who use basic econometric tools.
They have a foundation and understanding for further study of econometrics.
They have an appreciation of the range of more advanced techniques that exists and that may be covered in later econometric courses. - Syllabus
- PART 1
- 1. Introduction to econometrics and working with data
- 2. A non-technical introduction to regression
- 3. Simple regression model
- 4. Multiple regression model
- PART 2
- 5. Freeing up the classical assumptions - heteroskedasticity
- 6. Freeing up the classical assumptions - autocorrelated errors
- 7. Instrumental variables method
- PART 3
- 8. Models for panel data
- 9. Qualitative choice and limited dependent variable models
- 10. Univariate time series analysis
- 11. Regression with time series variables
- 12. Vector autoregressive models
- 13. Other models, methods and issues
- Literature
- required literature
- KOOP, Gary. Introduction to econometrics. Chichester: John Wiley & Sons, 2008, 371 s. ISBN 9780470032701. info
- CIPRA, Tomáš. Finanční ekonometrie. 1. vyd. Praha: Ekopress, 2008, 538 s. ISBN 9788086929439. info
- recommended literature
- HILL, R. Carter, William E. GRIFFITHS and Guay C. LIM. Principles of econometrics. 3rd ed. Hoboken: John Wiley & Sons, 2008, xxvii, 579. ISBN 9780471723608. info
- not specified
- GUJARATI, Damodar N. and Dawn C. PORTER. Basic econometrics. 5th ed. Boston: McGraw-Hill, 2009, xx, 922. ISBN 9780071276252. info
- WOOLDRIDGE, Jeffrey M. Introductory econometrics : a modern approach. 4th ed. (International stude. Canada: South-Western, 2009, xx, 865. ISBN 9780324585483. info
- STOCK, James H. and Mark W. WATSON. Introduction to econometrics. Brief ed. Boston: Pearson/Addison Wesley, 2008, xxvi, 379. ISBN 9780321432513. info
- KENNEDY, Peter. A guide to econometrics. 6th ed. Malden: Blackwell, 2008, xii, 585. ISBN 9781405182584. info
- Teaching methods
- lectures, class discussion, computer labs practices, drills
- Assessment methods
- final project, written and oral exam
- Language of instruction
- Czech
- Further comments (probably available only in Czech)
- The course is taught annually.
- Information about innovation of course.
- This course has been innovated under the project "Inovace studia ekonomických disciplín v souladu s požadavky znalostní ekonomiky (CZ.1.07/2.2.00/28.0227)" which is cofinanced by the European Social Fond and the national budget of the Czech Republic.
BKE_ZAEK Introduction to Econometrics
Faculty of Economics and AdministrationAutumn 2013
- Extent and Intensity
- 0/0. 8 credit(s). Type of Completion: zk (examination).
- Teacher(s)
- RNDr. Dalibor Moravanský, CSc. (lecturer)
prof. Ing. Osvald Vašíček, CSc. (lecturer)
doc. Ing. Daniel Němec, Ph.D. (alternate examiner) - Guaranteed by
- doc. Ing. Daniel Němec, Ph.D.
Department of Economics – Faculty of Economics and Administration
Contact Person: Lydie Pravdová
Supplier department: Department of Economics – Faculty of Economics and Administration - Timetable
- Sat 26. 10. 16:20–19:35 P106, Sun 10. 11. 16:20–19:35 P106, Sat 7. 12. 8:30–11:50 P103
- Prerequisites
- elementary probability and mathematical statistics
- Course Enrolment Limitations
- The course is also offered to the students of the fields other than those the course is directly associated with.
- fields of study / plans the course is directly associated with
- Finance (programme ESF, B-FU)
- Course objectives
- The course is designed to give students experience of using econometric methods important in economics, finance and other business subjects. It provides skills in regression essential for understanding much of the literature of economics, finance, and empirical studies in other areas of business.
We begin with the simple regression and multiple regression models. They are treated in depth and in range of applications. Careful attention is given to the interpretations of regression results and hypothesis testing. A part of the course introduces various modern tools for analyzing economic time series regression. Moreover, further topics in regression analysis are presented including regression with panel data and binary dependent variable.
By the end of the course students should be able to use regression models in many different applications, and to critically examine reported regression results in empirical research in economics and other business studies. They will be able to identify and deal with a number of econometric problems in the analysis of time series and cross-section data, and will have experience of a range of basic econometric methods.
The course is designed to give students an understanding of why econometrics is necessary and to provide them with a working knowledge of basic econometric tools so that:
They can apply these tools to modeling, estimation, inference, and forecasting in the context of real world economic problems.
They can evaluate critically the results and conclusions from others who use basic econometric tools.
They have a foundation and understanding for further study of econometrics.
They have an appreciation of the range of more advanced techniques that exists and that may be covered in later econometric courses. - Syllabus
- PART 1
- 1. Introduction to econometrics and working with data
- 2. A non-technical introduction to regression
- 3. Simple regression model
- 4. Multiple regression model
- PART 2
- 5. Freeing up the classical assumptions - heteroskedasticity
- 6. Freeing up the classical assumptions - autocorrelated errors
- 7. Instrumental variables method
- PART 3
- 8. Models for panel data
- 9. Qualitative choice and limited dependent variable models
- 10. Univariate time series analysis
- 11. Regression with time series variables
- 12. Vector autoregressive models
- 13. Other models, methods and issues
- Literature
- required literature
- KOOP, Gary. Introduction to econometrics. Chichester: John Wiley & Sons, 2008, 371 s. ISBN 9780470032701. info
- CIPRA, Tomáš. Finanční ekonometrie. 1. vyd. Praha: Ekopress, 2008, 538 s. ISBN 9788086929439. info
- recommended literature
- HILL, R. Carter, William E. GRIFFITHS and Guay C. LIM. Principles of econometrics. 3rd ed. Hoboken: John Wiley & Sons, 2008, xxvii, 579. ISBN 9780471723608. info
- not specified
- GUJARATI, Damodar N. and Dawn C. PORTER. Basic econometrics. 5th ed. Boston: McGraw-Hill, 2009, xx, 922. ISBN 9780071276252. info
- WOOLDRIDGE, Jeffrey M. Introductory econometrics : a modern approach. 4th ed. (International stude. Canada: South-Western, 2009, xx, 865. ISBN 9780324585483. info
- STOCK, James H. and Mark W. WATSON. Introduction to econometrics. Brief ed. Boston: Pearson/Addison Wesley, 2008, xxvi, 379. ISBN 9780321432513. info
- KENNEDY, Peter. A guide to econometrics. 6th ed. Malden: Blackwell, 2008, xii, 585. ISBN 9781405182584. info
- Teaching methods
- lectures, class discussion, computer labs practices, drills
- Assessment methods
- final project, written and oral exam
- Language of instruction
- Czech
- Further comments (probably available only in Czech)
- The course is taught annually.
- Information about innovation of course.
- This course has been innovated under the project "Inovace studia ekonomických disciplín v souladu s požadavky znalostní ekonomiky (CZ.1.07/2.2.00/28.0227)" which is cofinanced by the European Social Fond and the national budget of the Czech Republic.
BKE_ZAEK Introduction to Econometrics
Faculty of Economics and AdministrationAutumn 2012
- Extent and Intensity
- 0/0. 8 credit(s). Type of Completion: zk (examination).
- Teacher(s)
- RNDr. Dalibor Moravanský, CSc. (lecturer)
prof. Ing. Osvald Vašíček, CSc. (lecturer)
doc. Ing. Daniel Němec, Ph.D. (alternate examiner) - Guaranteed by
- doc. Ing. Daniel Němec, Ph.D.
Department of Economics – Faculty of Economics and Administration
Contact Person: Lydie Pravdová
Supplier department: Department of Economics – Faculty of Economics and Administration - Timetable
- Sat 20. 10. 16:20–19:35 P106, Sun 11. 11. 16:20–19:35 P106, Sat 1. 12. 8:30–11:50 P103
- Prerequisites
- elementary probability and mathematical statistics
- Course Enrolment Limitations
- The course is also offered to the students of the fields other than those the course is directly associated with.
- fields of study / plans the course is directly associated with
- Finance (programme ESF, B-FU)
- Course objectives
- The course is designed to give students experience of using econometric methods important in economics, finance and other business subjects. It provides skills in regression essential for understanding much of the literature of economics, finance, and empirical studies in other areas of business.
We begin with the simple regression and multiple regression models. They are treated in depth and in range of applications. Careful attention is given to the interpretations of regression results and hypothesis testing. A part of the course introduces various modern tools for analyzing economic time series regression. Moreover, further topics in regression analysis are presented including regression with panel data and binary dependent variable.
By the end of the course students should be able to use regression models in many different applications, and to critically examine reported regression results in empirical research in economics and other business studies. They will be able to identify and deal with a number of econometric problems in the analysis of time series and cross-section data, and will have experience of a range of basic econometric methods.
The course is designed to give students an understanding of why econometrics is necessary and to provide them with a working knowledge of basic econometric tools so that:
They can apply these tools to modeling, estimation, inference, and forecasting in the context of real world economic problems.
They can evaluate critically the results and conclusions from others who use basic econometric tools.
They have a foundation and understanding for further study of econometrics.
They have an appreciation of the range of more advanced techniques that exists and that may be covered in later econometric courses. - Syllabus
- PART 1
- 1. Introduction to econometrics and working with data
- 2. A non-technical introduction to regression
- 3. Simple regression model
- 4. Multiple regression model
- PART 2
- 5. Freeing up the classical assumptions - heteroskedasticity
- 6. Freeing up the classical assumptions - autocorrelated errors
- 7. Instrumental variables method
- PART 3
- 8. Models for panel data
- 9. Qualitative choice and limited dependent variable models
- 10. Univariate time series analysis
- 11. Regression with time series variables
- 12. Vector autoregressive models
- 13. Other models, methods and issues
- Literature
- required literature
- KOOP, Gary. Introduction to econometrics. Chichester: John Wiley & Sons, 2008, 371 s. ISBN 9780470032701. info
- CIPRA, Tomáš. Finanční ekonometrie. 1. vyd. Praha: Ekopress, 2008, 538 s. ISBN 9788086929439. info
- recommended literature
- HILL, R. Carter, William E. GRIFFITHS and Guay C. LIM. Principles of econometrics. 3rd ed. Hoboken: John Wiley & Sons, 2008, xxvii, 579. ISBN 9780471723608. info
- not specified
- GUJARATI, Damodar N. and Dawn C. PORTER. Basic econometrics. 5th ed. Boston: McGraw-Hill, 2009, xx, 922. ISBN 9780071276252. info
- WOOLDRIDGE, Jeffrey M. Introductory econometrics : a modern approach. 4th ed. (International stude. Canada: South-Western, 2009, xx, 865. ISBN 9780324585483. info
- STOCK, James H. and Mark W. WATSON. Introduction to econometrics. Brief ed. Boston: Pearson/Addison Wesley, 2008, xxvi, 379. ISBN 9780321432513. info
- KENNEDY, Peter. A guide to econometrics. 6th ed. Malden: Blackwell, 2008, xii, 585. ISBN 9781405182584. info
- Teaching methods
- lectures, class discussion, computer labs practices, drills
- Assessment methods
- final project, written and oral exam
- Language of instruction
- Czech
- Further comments (probably available only in Czech)
- Study Materials
The course is taught annually.
BKE_ZAEK Introduction to Econometrics
Faculty of Economics and AdministrationAutumn 2011
- Extent and Intensity
- 0/0. 8 credit(s). Type of Completion: zk (examination).
- Teacher(s)
- RNDr. Dalibor Moravanský, CSc. (lecturer)
prof. Ing. Osvald Vašíček, CSc. (lecturer)
doc. Ing. Daniel Němec, Ph.D. (alternate examiner) - Guaranteed by
- doc. Ing. Daniel Němec, Ph.D.
Department of Economics – Faculty of Economics and Administration
Contact Person: Lydie Pravdová - Timetable
- Sat 22. 10. 16:20–19:35 P104, Sun 13. 11. 16:20–19:35 P104, Sat 3. 12. 8:30–11:50 P103
- Prerequisites
- elementary probability and mathematical statistics
- Course Enrolment Limitations
- The course is also offered to the students of the fields other than those the course is directly associated with.
- fields of study / plans the course is directly associated with
- Finance (programme ESF, B-FU)
- Course objectives
- The course is designed to give students experience of using econometric methods important in economics, finance and other business subjects. It provides skills in regression essential for understanding much of the literature of economics, finance, and empirical studies in other areas of business.
We begin with the simple regression and multiple regression models. They are treated in depth and in range of applications. Careful attention is given to the interpretations of regression results and hypothesis testing. A part of the course introduces various modern tools for analyzing economic time series regression. Moreover, further topics in regression analysis are presented including regression with panel data and binary dependent variable.
By the end of the course students should be able to use regression models in many different applications, and to critically examine reported regression results in empirical research in economics and other business studies. They will be able to identify and deal with a number of econometric problems in the analysis of time series and cross-section data, and will have experience of a range of basic econometric methods.
The course is designed to give students an understanding of why econometrics is necessary and to provide them with a working knowledge of basic econometric tools so that:
They can apply these tools to modeling, estimation, inference, and forecasting in the context of real world economic problems.
They can evaluate critically the results and conclusions from others who use basic econometric tools.
They have a foundation and understanding for further study of econometrics.
They have an appreciation of the range of more advanced techniques that exists and that may be covered in later econometric courses. - Syllabus
- PART 1
- 1. Introduction to econometrics and working with data
- 2. A non-technical introduction to regression
- 3. Simple regression model
- 4. Multiple regression model
- PART 2
- 5. Freeing up the classical assumptions - heteroskedasticity
- 6. Freeing up the classical assumptions - autocorrelated errors
- 7. Instrumental variables method
- PART 3
- 8. Models for panel data
- 9. Qualitative choice and limited dependent variable models
- 10. Univariate time series analysis
- 11. Regression with time series variables
- 12. Vector autoregressive models
- 13. Other models, methods and issues
- Literature
- required literature
- KOOP, Gary. Introduction to econometrics. Chichester: John Wiley & Sons, 2008, 371 s. ISBN 9780470032701. info
- CIPRA, Tomáš. Finanční ekonometrie. 1. vyd. Praha: Ekopress, 2008, 538 s. ISBN 9788086929439. info
- not specified
- HILL, R. Carter, William E. GRIFFITHS and Guay C. LIM. Principles of econometrics. 3rd ed. Hoboken: John Wiley & Sons, 2008, xxvii, 579. ISBN 9780471723608. info
- GUJARATI, Damodar N. and Dawn C. PORTER. Basic econometrics. 5th ed. Boston: McGraw-Hill, 2009, xx, 922. ISBN 9780071276252. info
- WOOLDRIDGE, Jeffrey M. Introductory econometrics : a modern approach. 4th ed. (International stude. Canada: South-Western, 2009, xx, 865. ISBN 9780324585483. info
- STOCK, James H. and Mark W. WATSON. Introduction to econometrics. Brief ed. Boston: Pearson/Addison Wesley, 2008, xxvi, 379. ISBN 9780321432513. info
- KENNEDY, Peter. A guide to econometrics. 6th ed. Malden: Blackwell, 2008, xii, 585. ISBN 9781405182584. info
- Teaching methods
- lectures, class discussion, computer labs practices, drills
- Assessment methods
- final project, written and oral exam
- Language of instruction
- Czech
- Further Comments
- Study Materials
The course is taught annually.
BKE_ZAEK Introduction to Econometrics
Faculty of Economics and AdministrationAutumn 2010
- Extent and Intensity
- 0/0. 8 credit(s). Type of Completion: zk (examination).
- Teacher(s)
- RNDr. Dalibor Moravanský, CSc. (lecturer)
prof. Ing. Osvald Vašíček, CSc. (lecturer)
doc. Ing. Daniel Němec, Ph.D. (alternate examiner) - Guaranteed by
- doc. Ing. Daniel Němec, Ph.D.
Department of Economics – Faculty of Economics and Administration
Contact Person: Lydie Pravdová - Timetable
- Sat 23. 10. 16:20–19:35 P104, Sun 14. 11. 16:20–19:35 P104, Sat 4. 12. 8:30–11:50 P103
- Prerequisites
- elementary probability and mathematical statistics
- Course Enrolment Limitations
- The course is also offered to the students of the fields other than those the course is directly associated with.
- fields of study / plans the course is directly associated with
- Finance (programme ESF, B-FU)
- Course objectives
- The course is designed to give students experience of using econometric methods important in economics, finance and other business subjects. It provides skills in regression essential for understanding much of the literature of economics, finance, and empirical studies in other areas of business.
We begin with the simple regression and multiple regression models. They are treated in depth and in range of applications. Careful attention is given to the interpretations of regression results and hypothesis testing. A part of the course introduces various modern tools for analyzing economic time series regression. Moreover, further topics in regression analysis are presented including regression with panel data and binary dependent variable.
By the end of the course students should be able to use regression models in many different applications, and to critically examine reported regression results in empirical research in economics and other business studies. They will be able to identify and deal with a number of econometric problems in the analysis of time series and cross-section data, and will have experience of a range of basic econometric methods.
The course is designed to give students an understanding of why econometrics is necessary and to provide them with a working knowledge of basic econometric tools so that:
They can apply these tools to modeling, estimation, inference, and forecasting in the context of real world economic problems.
They can evaluate critically the results and conclusions from others who use basic econometric tools.
They have a foundation and understanding for further study of econometrics.
They have an appreciation of the range of more advanced techniques that exists and that may be covered in later econometric courses. - Syllabus
- PART 1
- 1. Introduction to econometrics and working with data
- 2. A non-technical introduction to regression
- 3. Simple regression model
- 4. Multiple regression model
- PART 2
- 5. Freeing up the classical assumptions - heteroskedasticity
- 6. Freeing up the classical assumptions - autocorrelated errors
- 7. Instrumental variables method
- PART 3
- 8. Models for panel data
- 9. Qualitative choice and limited dependent variable models
- 10. Univariate time series analysis
- 11. Regression with time series variables
- 12. Vector autoregressive models
- 13. Other models, methods and issues
- Literature
- required literature
- KOOP, Gary. Introduction to econometrics. Chichester: John Wiley & Sons, 2008, 371 s. ISBN 9780470032701. info
- CIPRA, Tomáš. Finanční ekonometrie. 1. vyd. Praha: Ekopress, 2008, 538 s. ISBN 9788086929439. info
- not specified
- HILL, R. Carter, William E. GRIFFITHS and Guay C. LIM. Principles of econometrics. 3rd ed. Hoboken: John Wiley & Sons, 2008, xxvii, 579. ISBN 9780471723608. info
- GUJARATI, Damodar N. and Dawn C. PORTER. Basic econometrics. 5th ed. Boston: McGraw-Hill, 2009, xx, 922. ISBN 9780071276252. info
- WOOLDRIDGE, Jeffrey M. Introductory econometrics : a modern approach. 4th ed. (International stude. Canada: South-Western, 2009, xx, 865. ISBN 9780324585483. info
- STOCK, James H. and Mark W. WATSON. Introduction to econometrics. Brief ed. Boston: Pearson/Addison Wesley, 2008, xxvi, 379. ISBN 9780321432513. info
- KENNEDY, Peter. A guide to econometrics. 6th ed. Malden: Blackwell, 2008, xii, 585. ISBN 9781405182584. info
- Teaching methods
- lectures, class discussion, computer labs practices, drills
- Assessment methods
- final project, written and oral exam
- Language of instruction
- Czech
- Further Comments
- The course is taught annually.
BKE_ZAEK Introduction to Econometrics
Faculty of Economics and AdministrationAutumn 2009
- Extent and Intensity
- 0/0. 8 credit(s). Type of Completion: zk (examination).
- Teacher(s)
- RNDr. Dalibor Moravanský, CSc. (lecturer)
prof. Ing. Osvald Vašíček, CSc. (lecturer)
doc. Ing. Daniel Němec, Ph.D. (alternate examiner) - Guaranteed by
- doc. Ing. Daniel Němec, Ph.D.
Department of Economics – Faculty of Economics and Administration - Timetable
- Sat 24. 10. 16:20–19:35 VT203, Sun 15. 11. 12:50–16:15 VT203, Sat 5. 12. 8:30–11:50 VT203
- Prerequisites
- BKM_STA2 Statistics || KMSTII Statistics II
elementary probability and mathematical statistics - Course Enrolment Limitations
- The course is also offered to the students of the fields other than those the course is directly associated with.
- fields of study / plans the course is directly associated with
- Finance (programme ESF, B-FU)
- Course objectives
- The course is designed to give students experience of using econometric methods important in economics, finance and other business subjects. It provides skills in regression essential for understanding much of the literature of economics, finance, and empirical studies in other areas of business.
We begin with the simple regression and multiple regression models. They are treated in depth and in range of applications. Careful attention is given to the interpretations of regression results and hypothesis testing. A part of the course introduces various modern tools for analyzing economic time series regression. Moreover, further topics in regression analysis are presented including regression with panel data and binary dependent variable.
By the end of the course students should be able to use regression models in many different applications, and to critically examine reported regression results in empirical research in economics and other business studies. They will be able to identify and deal with a number of econometric problems in the analysis of time series and cross-section data, and will have experience of a range of basic econometric methods.
The course is designed to give students an understanding of why econometrics is necessary and to provide them with a working knowledge of basic econometric tools so that:
They can apply these tools to modeling, estimation, inference, and forecasting in the context of real world economic problems.
They can evaluate critically the results and conclusions from others who use basic econometric tools.
They have a foundation and understanding for further study of econometrics.
They have an appreciation of the range of more advanced techniques that exists and that may be covered in later econometric courses. - Syllabus
- PART 1
- 1. Introduction to econometrics and working with data
- 2. A non-technical introduction to regression
- 3. Simple regression model
- 4. Multiple regression model
- PART 2
- 5. Freeing up the classical assumptions - heteroskedasticity
- 6. Freeing up the classical assumptions - autocorrelated errors
- 7. Instrumental variables method
- PART 3
- 8. Models for panel data
- 9. Qualitative choice and limited dependent variable models
- 10. Univariate time series analysis
- 11. Regression with time series variables
- 12. Vector autoregressive models
- 13. Other models, methods and issues
- Literature
- CIPRA, Tomáš. Finanční ekonometrie. 1. vyd. Praha: Ekopress, 2008, 538 s. ISBN 9788086929439. info
- WOOLDRIDGE, Jeffrey M. Introductory econometrics : a modern approach. 4th ed. (International stude. Canada: South-Western, 2009, xx, 865. ISBN 9780324585483. info
- HILL, R. Carter, William E. GRIFFITHS and Guay C. LIM. Principles of econometrics. 3rd ed. Hoboken: John Wiley & Sons, 2008, xxvii, 579. ISBN 9780471723608. info
- KOOP, Gary. Introduction to econometrics. Chichester: John Wiley & Sons, 2008, 371 s. ISBN 9780470032701. info
- GUJARATI, Damodar N. and Dawn C. PORTER. Basic econometrics. 5th ed. Boston: McGraw-Hill, 2009, xx, 922. ISBN 9780071276252. info
- STOCK, James H. and Mark W. WATSON. Introduction to econometrics. Brief ed. Boston: Pearson/Addison Wesley, 2008, xxvi, 379. ISBN 9780321432513. info
- KENNEDY, Peter. A guide to econometrics. 6th ed. Malden: Blackwell, 2008, xii, 585. ISBN 9781405182584. info
- VERBEEK, Marno. A guide to modern econometrics. 2nd ed. Chichester: John Wiley & Sons, 2004, xv, 429. ISBN 0470857730. info
- Teaching methods
- lectures, class discussion, computer labs practices, drills
- Assessment methods
- final project, written and oral exam
- Language of instruction
- Czech
- Further comments (probably available only in Czech)
- The course is taught annually.
General note: ekvivalent předmětu KMEM2A, KMEM2B, KMEMMI.
- Enrolment Statistics (recent)