BPE_ZAEK Introduction to Econometrics

Faculty of Economics and Administration
Autumn 2024
Extent and Intensity
2/2/0. 6 credit(s). Type of Completion: zk (examination).
Taught in person.
Teacher(s)
doc. Ing. Daniel Němec, Ph.D. (lecturer)
Mgr. Hana Fitzová, Ph.D. (seminar tutor)
Mgr. Jakub Chalmovianský, Ph.D. (seminar tutor)
Ing. Jakub Moučka (seminar tutor)
doc. Ing. Daniel Němec, Ph.D. (seminar tutor)
Ing. Mgr. Vlastimil Reichel, Ph.D. (seminar tutor)
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
Prerequisites
knowledge of the elementary probability and mathematical statistics may be an advantage, but even without it, all the necessary basic knowledge will be discussed and mastered during the course
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
there are 11 fields of study the course is directly associated with, display
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
  • 1. Introduction to econometrics and working with data
  • 2. A non-technical introduction to regression
  • 3. Simple regression model
  • 4. Multiple regression model
  • 5. Freeing up the classical assumptions - heteroskedasticity
  • 6. Freeing up the classical assumptions - autocorrelated errors
  • 7. Instrumental variables method
  • 8. Qualitative choice and limited dependent variable models
  • 9. Univariate time series analysis
  • 10. Regression with time series variables
  • 11. Vector autoregressive models
  • 12. Models for panel data
  • 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
  • BÉKÉS, Gábor and Gábor KÉZDI. Data analysis for business, economics, and policy. First published. Cambridge: Cambridge University Press, 2021, xxiii, 714. ISBN 9781108483018. info
  • BROOKS, Chris. Introductory econometrics for finance. Fourth edition. Cambridge: Cambridge University Press, 2019, xxxi, 696. ISBN 9781108422536. 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
homeworks assignments and seminar activity (30% of the final grade), final project and its oral defense (oral exam, 40 % of the final grade), written exam (30 % of the final grade); details of the course completion for students going abroad are contained in the Organisational guidelines (see study materials in IS)
Language of instruction
Czech
Follow-Up Courses
Further comments (probably available only in Czech)
The course is taught annually.
The course is taught: every week.
General note: Přednášky jsou dostupné online a ze záznamu.
Listed among pre-requisites of other courses
Teacher's information
Any copying, recording or leaking tests, use of unauthorized tools, aids and communication devices, or other disruptions of objectivity of exams (credit tests) will be considered non-compliance with the conditions for course completion as well as a severe violation of the study rules. Consequently, the teacher will finish the exam (credit test) by awarding grade "F" in the Information System, and the Dean will initiate disciplinary proceedings that may result in study termination.
The course is also listed under the following terms Autumn 2009, Autumn 2010, Autumn 2011, Autumn 2012, Autumn 2013, Autumn 2014, Autumn 2015, Autumn 2016, Autumn 2017, Autumn 2018, Autumn 2019, Autumn 2020, Autumn 2021, Autumn 2022, Autumn 2023.

BPE_ZAEK Introduction to Econometrics

Faculty of Economics and Administration
Autumn 2023
Extent and Intensity
2/2/0. 8 credit(s). Type of Completion: zk (examination).
Taught in person.
Teacher(s)
doc. Ing. Daniel Němec, Ph.D. (lecturer)
Mgr. Hana Fitzová, Ph.D. (seminar tutor)
Mgr. Jakub Chalmovianský, Ph.D. (seminar tutor)
Ing. Jakub Moučka (seminar tutor)
doc. Ing. Daniel Němec, Ph.D. (seminar tutor)
Ing. Mgr. Vlastimil Reichel, Ph.D. (seminar tutor)
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
Wed 16:00–17:50 P101, except Wed 20. 9., except Wed 8. 11.
  • Timetable of Seminar Groups:
BPE_ZAEK/01: Wed 18:00–19:50 VT204, except Wed 20. 9., except Wed 8. 11., D. Němec
BPE_ZAEK/02: Wed 8:00–9:50 VT206, except Wed 20. 9., except Wed 8. 11., J. Moučka
BPE_ZAEK/03: Wed 10:00–11:50 VT206, except Wed 20. 9., except Wed 8. 11., J. Moučka
BPE_ZAEK/04: Tue 16:00–17:50 VT202, except Tue 19. 9., except Tue 7. 11., J. Chalmovianský
BPE_ZAEK/05: Tue 12:00–13:50 VT204, except Tue 19. 9., except Tue 7. 11., J. Chalmovianský
BPE_ZAEK/06: Tue 14:00–15:50 VT206, except Tue 19. 9., except Tue 7. 11., H. Fitzová
BPE_ZAEK/07: Tue 10:00–11:50 VT202, except Tue 19. 9., except Tue 7. 11., H. Fitzová
BPE_ZAEK/08: Wed 12:00–13:50 VT314, except Wed 20. 9., except Wed 8. 11., V. Reichel
Prerequisites
knowledge of the elementary probability and mathematical statistics may be an advantage, but even without it, all the necessary basic knowledge will be discussed and mastered during the course
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
there are 9 fields of study the course is directly associated with, display
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
  • 1. Introduction to econometrics and working with data
  • 2. A non-technical introduction to regression
  • 3. Simple regression model
  • 4. Multiple regression model
  • 5. Freeing up the classical assumptions - heteroskedasticity
  • 6. Freeing up the classical assumptions - autocorrelated errors
  • 7. Instrumental variables method
  • 8. Qualitative choice and limited dependent variable models
  • 9. Univariate time series analysis
  • 10. Regression with time series variables
  • 11. Vector autoregressive models
  • 12. Models for panel data
  • 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
  • BÉKÉS, Gábor and Gábor KÉZDI. Data analysis for business, economics, and policy. First published. Cambridge: Cambridge University Press, 2021, xxiii, 714. ISBN 9781108483018. info
  • BROOKS, Chris. Introductory econometrics for finance. Fourth edition. Cambridge: Cambridge University Press, 2019, xxxi, 696. ISBN 9781108422536. 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
homeworks assignments and seminar activity (30% of the final grade), final project and its oral defense (oral exam, 40 % of the final grade), written exam (30 % of the final grade); details of the course completion for students going abroad are contained in the Organisational guidelines (see study materials in IS)
Language of instruction
Czech
Follow-Up Courses
Further comments (probably available only in Czech)
The course is taught annually.
General note: Přednášky jsou dostupné online a ze záznamu.
Listed among pre-requisites of other courses
Teacher's information
Any copying, recording or leaking tests, use of unauthorized tools, aids and communication devices, or other disruptions of objectivity of exams (credit tests) will be considered non-compliance with the conditions for course completion as well as a severe violation of the study rules. Consequently, the teacher will finish the exam (credit test) by awarding grade "F" in the Information System, and the Dean will initiate disciplinary proceedings that may result in study termination.
The course is also listed under the following terms Autumn 2009, Autumn 2010, Autumn 2011, Autumn 2012, Autumn 2013, Autumn 2014, Autumn 2015, Autumn 2016, Autumn 2017, Autumn 2018, Autumn 2019, Autumn 2020, Autumn 2021, Autumn 2022, Autumn 2024.

BPE_ZAEK Introduction to Econometrics

Faculty of Economics and Administration
Autumn 2022
Extent and Intensity
2/2/0. 8 credit(s). Type of Completion: zk (examination).
Taught in person.
Teacher(s)
doc. Ing. Daniel Němec, Ph.D. (lecturer)
Mgr. Hana Fitzová, Ph.D. (seminar tutor)
Mgr. Jakub Chalmovianský, Ph.D. (seminar tutor)
Ing. Jakub Moučka (seminar tutor)
doc. Ing. Daniel Němec, Ph.D. (seminar tutor)
prof. Ing. Zdeněk Tomeš, Ph.D. (seminar tutor)
Ing. Mgr. Vlastimil Reichel, Ph.D. (assistant)
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
Wed 16:00–17:50 P101, except Wed 14. 9., except Wed 2. 11.
  • Timetable of Seminar Groups:
BPE_ZAEK/01: Wed 18:00–19:50 VT204, except Wed 14. 9., except Wed 2. 11., D. Němec
BPE_ZAEK/02: Wed 8:00–9:50 VT206, except Wed 14. 9., except Wed 2. 11., Z. Tomeš
BPE_ZAEK/03: Wed 10:00–11:50 VT206, except Wed 14. 9., except Wed 2. 11., Z. Tomeš
BPE_ZAEK/04: Tue 16:00–17:50 VT204, except Tue 13. 9., except Tue 1. 11., J. Chalmovianský
BPE_ZAEK/05: Tue 12:00–13:50 VT204, except Tue 13. 9., except Tue 1. 11., J. Chalmovianský
BPE_ZAEK/06: Tue 14:00–15:50 VT206, except Tue 13. 9., except Tue 1. 11., H. Fitzová
BPE_ZAEK/07: Tue 10:00–11:50 VT202, except Tue 13. 9., except Tue 1. 11., H. Fitzová
BPE_ZAEK/08: Tue 18:00–19:50 VT314, except Tue 13. 9., except Tue 1. 11., J. Moučka
Prerequisites
knowledge of the elementary probability and mathematical statistics may be an advantage, but even without it, all the necessary basic knowledge will be discussed and mastered during the course
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
there are 22 fields of study the course is directly associated with, display
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
  • 1. Introduction to econometrics and working with data
  • 2. A non-technical introduction to regression
  • 3. Simple regression model
  • 4. Multiple regression model
  • 5. Freeing up the classical assumptions - heteroskedasticity
  • 6. Freeing up the classical assumptions - autocorrelated errors
  • 7. Instrumental variables method
  • 8. Qualitative choice and limited dependent variable models
  • 9. Univariate time series analysis
  • 10. Regression with time series variables
  • 11. Vector autoregressive models
  • 12. Models for panel data
  • 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
  • WOOLDRIDGE, Jeffrey M. Introductory econometrics : a modern approach. 4th ed. (International stude. Canada: South-Western, 2009, xx, 865. ISBN 9780324585483. 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
Teaching methods
lectures, class discussion, computer labs practices, drills
Assessment methods
homeworks, final project, written and oral exam
Language of instruction
Czech
Follow-Up Courses
Further comments (probably available only in Czech)
The course is taught annually.
General note: Přednášky jsou dostupné online a ze záznamu.
Listed among pre-requisites of other courses
The course is also listed under the following terms Autumn 2009, Autumn 2010, Autumn 2011, Autumn 2012, Autumn 2013, Autumn 2014, Autumn 2015, Autumn 2016, Autumn 2017, Autumn 2018, Autumn 2019, Autumn 2020, Autumn 2021, Autumn 2023, Autumn 2024.

BPE_ZAEK Introduction to Econometrics

Faculty of Economics and Administration
Autumn 2021
Extent and Intensity
2/2/0. 8 credit(s). Type of Completion: zk (examination).
Taught in person.
Teacher(s)
doc. Ing. Daniel Němec, Ph.D. (lecturer)
Ing. Tomáš Dvořák (seminar tutor)
Mgr. Hana Fitzová, Ph.D. (seminar tutor)
Mgr. Jakub Chalmovianský, Ph.D. (seminar tutor)
doc. Ing. Daniel Němec, Ph.D. (seminar tutor)
Ing. Mgr. Vlastimil Reichel, Ph.D. (seminar tutor)
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
Wed 16:00–17:50 P101, except Wed 15. 9., except Wed 3. 11.
  • Timetable of Seminar Groups:
BPE_ZAEK/01: Wed 18:00–19:50 VT204, except Wed 15. 9., except Wed 3. 11., D. Němec
BPE_ZAEK/02: Wed 8:00–9:50 VT206, except Wed 15. 9., except Wed 3. 11., V. Reichel
BPE_ZAEK/03: Wed 10:00–11:50 VT206, except Wed 15. 9., except Wed 3. 11., V. Reichel
BPE_ZAEK/04: Tue 16:00–17:50 VT204, except Tue 14. 9., except Tue 2. 11., T. Dvořák
BPE_ZAEK/05: Tue 12:00–13:50 VT204, except Tue 14. 9., except Tue 2. 11., H. Fitzová
BPE_ZAEK/06: Tue 14:00–15:50 VT206, except Tue 14. 9., except Tue 2. 11., H. Fitzová
BPE_ZAEK/07: Tue 10:00–11:50 VT202, except Tue 14. 9., except Tue 2. 11., H. Fitzová
BPE_ZAEK/08: Tue 18:00–19:50 VT105, except Tue 14. 9., except Tue 2. 11., T. Dvořák
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
there are 26 fields of study the course is directly associated with, display
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
  • 1. Introduction to econometrics and working with data
  • 2. A non-technical introduction to regression
  • 3. Simple regression model
  • 4. Multiple regression model
  • 5. Freeing up the classical assumptions - heteroskedasticity
  • 6. Freeing up the classical assumptions - autocorrelated errors
  • 7. Instrumental variables method
  • 8. Qualitative choice and limited dependent variable models
  • 9. Univariate time series analysis
  • 10. Regression with time series variables
  • 11. Vector autoregressive models
  • 12. Models for panel data
  • 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
  • WOOLDRIDGE, Jeffrey M. Introductory econometrics : a modern approach. 4th ed. (International stude. Canada: South-Western, 2009, xx, 865. ISBN 9780324585483. 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
Teaching methods
lectures, class discussion, computer labs practices, drills
Assessment methods
homeworks, final project, written and oral exam
Language of instruction
Czech
Follow-Up Courses
Further comments (probably available only in Czech)
Study Materials
The course is taught annually.
General note: Přednášky jsou dostupné online a ze záznamu.
Listed among pre-requisites of other courses
The course is also listed under the following terms Autumn 2009, Autumn 2010, Autumn 2011, Autumn 2012, Autumn 2013, Autumn 2014, Autumn 2015, Autumn 2016, Autumn 2017, Autumn 2018, Autumn 2019, Autumn 2020, Autumn 2022, Autumn 2023, Autumn 2024.

BPE_ZAEK Introduction to Econometrics

Faculty of Economics and Administration
Autumn 2020
Extent and Intensity
2/2/0. 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. (seminar tutor)
Mgr. Jakub Chalmovianský, Ph.D. (seminar tutor)
doc. Ing. Daniel Němec, Ph.D. (seminar tutor)
Ing. Mgr. Vlastimil Reichel, Ph.D. (seminar tutor)
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
Wed 16:00–17:50 P101
  • Timetable of Seminar Groups:
BPE_ZAEK/01: Wed 18:00–19:50 VT204, D. Němec
BPE_ZAEK/02: Wed 8:00–9:50 VT206, V. Reichel
BPE_ZAEK/03: Wed 10:00–11:50 VT206, V. Reichel
BPE_ZAEK/04: Tue 16:00–17:50 VT204, J. Chalmovianský
BPE_ZAEK/05: Tue 12:00–13:50 VT204, H. Fitzová
BPE_ZAEK/06: Tue 14:00–15:50 VT206, J. Chalmovianský
BPE_ZAEK/07: Tue 10:00–11:50 VT202, H. Fitzová
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
there are 26 fields of study the course is directly associated with, display
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
  • 1. Introduction to econometrics and working with data
  • 2. A non-technical introduction to regression
  • 3. Simple regression model
  • 4. Multiple regression model
  • 5. Freeing up the classical assumptions - heteroskedasticity
  • 6. Freeing up the classical assumptions - autocorrelated errors
  • 7. Instrumental variables method
  • 8. Qualitative choice and limited dependent variable models
  • 9. Univariate time series analysis
  • 10. Regression with time series variables
  • 11. Vector autoregressive models
  • 12. Models for panel data
  • 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
  • WOOLDRIDGE, Jeffrey M. Introductory econometrics : a modern approach. 4th ed. (International stude. Canada: South-Western, 2009, xx, 865. ISBN 9780324585483. 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
Teaching methods
lectures, class discussion, computer labs practices, drills
Assessment methods
homeworks, final project, written and oral exam
Language of instruction
Czech
Follow-Up Courses
Further comments (probably available only in Czech)
The course is taught annually.
General note: Přednášky jsou dostupné online a ze záznamu.
Listed among pre-requisites of other courses
The course is also listed under the following terms Autumn 2009, Autumn 2010, Autumn 2011, Autumn 2012, Autumn 2013, Autumn 2014, Autumn 2015, Autumn 2016, Autumn 2017, Autumn 2018, Autumn 2019, Autumn 2021, Autumn 2022, Autumn 2023, Autumn 2024.

BPE_ZAEK Introduction to Econometrics

Faculty of Economics and Administration
Autumn 2019
Extent and Intensity
2/2/0. 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. (seminar tutor)
doc. Ing. Daniel Němec, Ph.D. (seminar tutor)
Ing. Mgr. Vlastimil Reichel, Ph.D. (seminar tutor)
Ing. Mgr. Jakub Buček (assistant)
Mgr. Jakub Chalmovianský, Ph.D. (assistant)
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
Wed 16:00–17:50 P101
  • Timetable of Seminar Groups:
BPE_ZAEK/01: Wed 18:00–19:50 VT204, D. Němec
BPE_ZAEK/02: Wed 8:00–9:50 VT206, V. Reichel
BPE_ZAEK/03: Wed 10:00–11:50 VT206, H. Fitzová
BPE_ZAEK/04: Tue 16:00–17:50 VT204, V. Reichel
BPE_ZAEK/05: Tue 12:00–13:50 VT204, H. Fitzová
BPE_ZAEK/06: Tue 14:00–15:50 VT206, V. Reichel
BPE_ZAEK/07: Tue 10:00–11:50 VT202, H. Fitzová
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
there are 26 fields of study the course is directly associated with, display
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
  • 1. Introduction to econometrics and working with data
  • 2. A non-technical introduction to regression
  • 3. Simple regression model
  • 4. Multiple regression model
  • 5. Freeing up the classical assumptions - heteroskedasticity
  • 6. Freeing up the classical assumptions - autocorrelated errors
  • 7. Instrumental variables method
  • 8. Qualitative choice and limited dependent variable models
  • 9. Univariate time series analysis
  • 10. Regression with time series variables
  • 11. Vector autoregressive models
  • 12. Models for panel data
  • 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
  • WOOLDRIDGE, Jeffrey M. Introductory econometrics : a modern approach. 4th ed. (International stude. Canada: South-Western, 2009, xx, 865. ISBN 9780324585483. 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
Teaching methods
lectures, class discussion, computer labs practices, drills
Assessment methods
homeworks, final project, written and oral exam
Language of instruction
Czech
Follow-Up Courses
Further comments (probably available only in Czech)
Study Materials
The course is taught annually.
General note: Přednášky jsou dostupné online a ze záznamu.
Listed among pre-requisites of other courses
The course is also listed under the following terms Autumn 2009, Autumn 2010, Autumn 2011, Autumn 2012, Autumn 2013, Autumn 2014, Autumn 2015, Autumn 2016, Autumn 2017, Autumn 2018, Autumn 2020, Autumn 2021, Autumn 2022, Autumn 2023, Autumn 2024.

BPE_ZAEK Introduction to Econometrics

Faculty of Economics and Administration
Autumn 2018
Extent and Intensity
2/2/0. 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. (seminar tutor)
Mgr. Jakub Chalmovianský, Ph.D. (seminar tutor)
doc. Ing. Daniel Němec, Ph.D. (seminar tutor)
Ing. Mgr. Vlastimil Reichel, Ph.D. (seminar tutor)
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
Wed 16:00–17:50 P101
  • Timetable of Seminar Groups:
BPE_ZAEK/01: Wed 18:00–19:50 VT204, D. Němec
BPE_ZAEK/02: Wed 8:00–9:50 VT206, V. Reichel
BPE_ZAEK/03: Wed 10:00–11:50 VT206, V. Reichel
BPE_ZAEK/04: Tue 16:00–17:50 VT204, J. Chalmovianský
BPE_ZAEK/05: Tue 12:00–13:50 VT204, H. Fitzová
BPE_ZAEK/06: Tue 14:00–15:50 VT202, J. Chalmovianský
BPE_ZAEK/07: Tue 10:00–11:50 VT206, H. Fitzová
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
there are 18 fields of study the course is directly associated with, display
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
  • 1. Introduction to econometrics and working with data
  • 2. A non-technical introduction to regression
  • 3. Simple regression model
  • 4. Multiple regression model
  • 5. Freeing up the classical assumptions - heteroskedasticity
  • 6. Freeing up the classical assumptions - autocorrelated errors
  • 7. Instrumental variables method
  • 8. Qualitative choice and limited dependent variable models
  • 9. Univariate time series analysis
  • 10. Regression with time series variables
  • 11. Vector autoregressive models
  • 12. Models for panel data
  • 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
  • WOOLDRIDGE, Jeffrey M. Introductory econometrics : a modern approach. 4th ed. (International stude. Canada: South-Western, 2009, xx, 865. ISBN 9780324585483. 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
Teaching methods
lectures, class discussion, computer labs practices, drills
Assessment methods
homeworks, final project, written and oral exam
Language of instruction
Czech
Follow-Up Courses
Further comments (probably available only in Czech)
The course is taught annually.
General note: Přednášky jsou dostupné online a ze záznamu.
Listed among pre-requisites of other courses
The course is also listed under the following terms Autumn 2009, Autumn 2010, Autumn 2011, Autumn 2012, Autumn 2013, Autumn 2014, Autumn 2015, Autumn 2016, Autumn 2017, Autumn 2019, Autumn 2020, Autumn 2021, Autumn 2022, Autumn 2023, Autumn 2024.

BPE_ZAEK Introduction to Econometrics

Faculty of Economics and Administration
Autumn 2017
Extent and Intensity
2/2/0. 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. (seminar tutor)
Mgr. Jakub Chalmovianský, Ph.D. (seminar tutor)
doc. Ing. Daniel Němec, Ph.D. (seminar tutor)
Mgr. Zlatica Peňáková, Ph.D. (seminar tutor)
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
Wed 16:20–17:55 P101
  • Timetable of Seminar Groups:
BPE_ZAEK/T01: Thu 21. 9. to Fri 22. 12. Thu 13:00–14:35 106, Z. Peňáková, Nepřihlašuje se. Určeno pro studenty se zdravotním postižením.
BPE_ZAEK/01: Wed 18:00–19:35 VT204, D. Němec
BPE_ZAEK/02: Wed 9:20–11:00 VT105, D. Němec
BPE_ZAEK/03: Wed 11:05–12:45 VT204, H. Fitzová
BPE_ZAEK/04: Tue 16:20–17:55 VT204, J. Chalmovianský
BPE_ZAEK/06: Tue 12:50–14:30 VT204, H. Fitzová
BPE_ZAEK/08: Tue 14:35–16:15 VT204, J. Chalmovianský
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
there are 18 fields of study the course is directly associated with, display
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
  • 1. Introduction to econometrics and working with data
  • 2. A non-technical introduction to regression
  • 3. Simple regression model
  • 4. Multiple regression model
  • 5. Freeing up the classical assumptions - heteroskedasticity
  • 6. Freeing up the classical assumptions - autocorrelated errors
  • 7. Instrumental variables method
  • 8. Qualitative choice and limited dependent variable models
  • 9. Univariate time series analysis
  • 10. Regression with time series variables
  • 11. Vector autoregressive models
  • 12. Models for panel data
  • 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
  • WOOLDRIDGE, Jeffrey M. Introductory econometrics : a modern approach. 4th ed. (International stude. Canada: South-Western, 2009, xx, 865. ISBN 9780324585483. 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
Teaching methods
lectures, class discussion, computer labs practices, drills
Assessment methods
homeworks, final project, written and oral exam
Language of instruction
Czech
Follow-Up Courses
Further comments (probably available only in Czech)
Study Materials
The course is taught annually.
General note: Přednášky jsou dostupné online a ze záznamu.
Listed among pre-requisites of other courses
The course is also listed under the following terms Autumn 2009, Autumn 2010, Autumn 2011, Autumn 2012, Autumn 2013, Autumn 2014, Autumn 2015, Autumn 2016, Autumn 2018, Autumn 2019, Autumn 2020, Autumn 2021, Autumn 2022, Autumn 2023, Autumn 2024.

BPE_ZAEK Introduction to Econometrics

Faculty of Economics and Administration
Autumn 2016
Extent and Intensity
2/2/0. 8 credit(s). Type of Completion: zk (examination).
Teacher(s)
doc. Ing. Daniel Němec, Ph.D. (lecturer)
prof. Ing. Osvald Vašíček, CSc. (lecturer)
Ing. Mgr. Jakub Buček (seminar tutor)
Mgr. Hana Fitzová, Ph.D. (seminar tutor)
Mgr. Jakub Chalmovianský, Ph.D. (seminar tutor)
doc. Ing. Daniel Němec, Ph.D. (seminar tutor)
Mgr. Zlatica Peňáková, Ph.D. (seminar tutor)
Ing. Mgr. Vlastimil Reichel, Ph.D. (seminar tutor)
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
Wed 16:20–17:55 P101
  • Timetable of Seminar Groups:
BPE_ZAEK/T01: Tue 20. 9. to Thu 22. 12. Tue 9:40–11:15 115, V. Reichel, Nepřihlašuje se. Určeno pro studenty se zdravotním postižením.
BPE_ZAEK/01: Wed 18:00–19:35 VT204, D. Němec
BPE_ZAEK/02: Wed 9:20–11:00 VT105, H. Fitzová
BPE_ZAEK/03: Wed 11:05–12:45 VT204, H. Fitzová
BPE_ZAEK/04: Tue 16:20–17:55 VT204, J. Chalmovianský
BPE_ZAEK/05: Mon 12:50–14:30 VT203, J. Buček
BPE_ZAEK/06: Tue 12:50–14:30 VT204, D. Němec
BPE_ZAEK/07: Mon 14:35–16:15 VT204, J. Buček
BPE_ZAEK/08: Tue 14:35–16:15 VT204, J. Chalmovianský
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
there are 18 fields of study the course is directly associated with, display
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
  • 1. Introduction to econometrics and working with data
  • 2. A non-technical introduction to regression
  • 3. Simple regression model
  • 4. Multiple regression model
  • 5. Freeing up the classical assumptions - heteroskedasticity
  • 6. Freeing up the classical assumptions - autocorrelated errors
  • 7. Instrumental variables method
  • 8. Qualitative choice and limited dependent variable models
  • 9. Univariate time series analysis
  • 10. Regression with time series variables
  • 11. Vector autoregressive models
  • 12. Models for panel data
  • 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
  • WOOLDRIDGE, Jeffrey M. Introductory econometrics : a modern approach. 4th ed. (International stude. Canada: South-Western, 2009, xx, 865. ISBN 9780324585483. 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
Teaching methods
lectures, class discussion, computer labs practices, drills
Assessment methods
homeworks, final project, written and oral exam
Language of instruction
Czech
Follow-Up Courses
Further comments (probably available only in Czech)
Study Materials
The course is taught annually.
General note: Přednášky jsou dostupné online a ze záznamu.
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.

logo image
Listed among pre-requisites of other courses
The course is also listed under the following terms Autumn 2009, Autumn 2010, Autumn 2011, Autumn 2012, Autumn 2013, Autumn 2014, Autumn 2015, Autumn 2017, Autumn 2018, Autumn 2019, Autumn 2020, Autumn 2021, Autumn 2022, Autumn 2023, Autumn 2024.

BPE_ZAEK Introduction to Econometrics

Faculty of Economics and Administration
Autumn 2015
Extent and Intensity
2/2. 8 credit(s). Type of Completion: zk (examination).
Teacher(s)
doc. Ing. Daniel Němec, Ph.D. (lecturer)
prof. Ing. Osvald Vašíček, CSc. (lecturer)
Ing. Mgr. Jakub Buček (seminar tutor)
Mgr. Hana Fitzová, Ph.D. (seminar tutor)
Mgr. Jakub Chalmovianský, Ph.D. (seminar tutor)
Ing. Michal Chribik (seminar tutor)
doc. Ing. Daniel Němec, Ph.D. (seminar tutor)
Mgr. Zlatica Peňáková, Ph.D. (seminar tutor)
Ing. Mgr. Vlastimil Reichel, Ph.D. (seminar tutor)
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
Wed 16:20–17:55 P101
  • Timetable of Seminar Groups:
BPE_ZAEK/01: Wed 18:00–19:35 VT204, D. Němec
BPE_ZAEK/02: Wed 9:20–11:00 VT105, H. Fitzová
BPE_ZAEK/03: Wed 11:05–12:45 VT204, H. Fitzová
BPE_ZAEK/05: Mon 12:50–14:30 VT203, J. Buček
BPE_ZAEK/06: Thu 11:05–12:45 VT204, Z. Peňáková
BPE_ZAEK/07: Mon 14:35–16:15 VT204, J. Buček
BPE_ZAEK/08: Tue 14:35–16:15 VT204, M. Chribik
BPE_ZAEK/10: Tue 12:50–14:30 VT204, D. Němec
BPE_ZAEK/13: Wed 12:50–14:30 VT105, V. Reichel
BPE_ZAEK/14: Thu 9:20–11:00 VT105, J. Chalmovianský
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
there are 18 fields of study the course is directly associated with, display
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
  • 1. Introduction to econometrics and working with data
  • 2. A non-technical introduction to regression
  • 3. Simple regression model
  • 4. Multiple regression model
  • 5. Freeing up the classical assumptions - heteroskedasticity
  • 6. Freeing up the classical assumptions - autocorrelated errors
  • 7. Instrumental variables method
  • 8. Qualitative choice and limited dependent variable models
  • 9. Univariate time series analysis
  • 10. Regression with time series variables
  • 11. Vector autoregressive models
  • 12. Models for panel data
  • 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
  • WOOLDRIDGE, Jeffrey M. Introductory econometrics : a modern approach. 4th ed. (International stude. Canada: South-Western, 2009, xx, 865. ISBN 9780324585483. 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
Teaching methods
lectures, class discussion, computer labs practices, drills
Assessment methods
homeworks, final project, written and oral exam
Language of instruction
Czech
Follow-Up Courses
Further comments (probably available only in Czech)
The course is taught annually.
General note: Přednášky jsou dostupné online a ze záznamu.
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.

logo image
Listed among pre-requisites of other courses
The course is also listed under the following terms Autumn 2009, Autumn 2010, Autumn 2011, Autumn 2012, Autumn 2013, Autumn 2014, Autumn 2016, Autumn 2017, Autumn 2018, Autumn 2019, Autumn 2020, Autumn 2021, Autumn 2022, Autumn 2023, Autumn 2024.

BPE_ZAEK Introduction to Econometrics

Faculty of Economics and Administration
Autumn 2014
Extent and Intensity
2/2. 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. (seminar tutor)
doc. Ing. Daniel Němec, Ph.D. (seminar tutor)
Ing. Vratislav Pisca (seminar tutor)
prof. Ing. Zdeněk Tomeš, Ph.D. (seminar tutor)
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
Wed 16:20–17:55 P101
  • Timetable of Seminar Groups:
BPE_ZAEK/01: Wed 18:00–19:35 VT204, D. Němec
BPE_ZAEK/02: Wed 9:20–11:00 VT105, H. Fitzová
BPE_ZAEK/03: Wed 11:05–12:45 VT204, H. Fitzová
BPE_ZAEK/04: Tue 8:30–10:05 VT203
BPE_ZAEK/05: Mon 12:50–14:30 VT204
BPE_ZAEK/06: Thu 11:05–12:45 VT204
BPE_ZAEK/07: Mon 14:35–16:15 VT204
BPE_ZAEK/08: Tue 14:35–16:15 VT204, D. Němec
BPE_ZAEK/09: Tue 16:20–17:55 VT204
BPE_ZAEK/10: Tue 12:50–14:30 VT204, Z. Tomeš
BPE_ZAEK/11: Mon 9:20–11:00 VT105, H. Fitzová
BPE_ZAEK/12: Mon 11:05–12:45 VT105, H. Fitzová
BPE_ZAEK/13: Wed 12:50–14:30 VT105, V. Pisca
BPE_ZAEK/14: Thu 9:20–11:00 VT105, V. Pisca
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
there are 18 fields of study the course is directly associated with, display
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
  • 1. Introduction to econometrics and working with data
  • 2. A non-technical introduction to regression
  • 3. Simple regression model
  • 4. Multiple regression model
  • 5. Freeing up the classical assumptions - heteroskedasticity
  • 6. Freeing up the classical assumptions - autocorrelated errors
  • 7. Instrumental variables method
  • 8. Qualitative choice and limited dependent variable models
  • 9. Univariate time series analysis
  • 10. Regression with time series variables
  • 11. Vector autoregressive models
  • 12. Models for panel data
  • 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
  • WOOLDRIDGE, Jeffrey M. Introductory econometrics : a modern approach. 4th ed. (International stude. Canada: South-Western, 2009, xx, 865. ISBN 9780324585483. 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
Teaching methods
lectures, class discussion, computer labs practices, drills
Assessment methods
homeworks, final project, written and oral exam
Language of instruction
Czech
Follow-Up Courses
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.

logo image
Listed among pre-requisites of other courses
The course is also listed under the following terms Autumn 2009, Autumn 2010, Autumn 2011, Autumn 2012, Autumn 2013, Autumn 2015, Autumn 2016, Autumn 2017, Autumn 2018, Autumn 2019, Autumn 2020, Autumn 2021, Autumn 2022, Autumn 2023, Autumn 2024.

BPE_ZAEK Introduction to Econometrics

Faculty of Economics and Administration
Autumn 2013
Extent and Intensity
2/2. 8 credit(s). Type of Completion: zk (examination).
Teacher(s)
doc. Ing. Daniel Němec, Ph.D. (lecturer)
prof. Ing. Osvald Vašíček, CSc. (lecturer)
doc. Ing. Daniel Němec, Ph.D. (seminar tutor)
RNDr. Dalibor Moravanský, CSc. (seminar tutor)
Mgr. Jaroslav Bil (seminar tutor)
Ing. Vladimír Hajko, Ph.D. (seminar tutor)
prof. Ing. Zdeněk Tomeš, Ph.D. (seminar tutor)
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
Wed 16:20–17:55 P101
  • Timetable of Seminar Groups:
BPE_ZAEK/01: Wed 18:00–19:35 VT204, D. Němec
BPE_ZAEK/02: Wed 9:20–11:00 VT105, J. Bil
BPE_ZAEK/03: Wed 11:05–12:45 VT204, J. Bil
BPE_ZAEK/04: Tue 8:30–10:05 VT203
BPE_ZAEK/05: Mon 12:50–14:30 VT204, V. Hajko
BPE_ZAEK/06: Thu 11:05–12:45 VT204
BPE_ZAEK/07: Mon 14:35–16:15 VT204, V. Hajko
BPE_ZAEK/08: Tue 14:35–16:15 VT204, D. Němec
BPE_ZAEK/09: Tue 16:20–17:55 VT204, D. Moravanský
BPE_ZAEK/10: Tue 12:50–14:30 VT204, D. Němec
BPE_ZAEK/11: Mon 9:20–11:00 VT105, D. Moravanský
BPE_ZAEK/12: Mon 11:05–12:45 VT105, D. Moravanský
BPE_ZAEK/13: Wed 12:50–14:30 VT105, J. Bil
BPE_ZAEK/14: Thu 9:20–11:00 VT105
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
there are 18 fields of study the course is directly associated with, display
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
  • 1. Introduction to econometrics and working with data
  • 2. A non-technical introduction to regression
  • 3. Simple regression model
  • 4. Multiple regression model
  • 5. Freeing up the classical assumptions - heteroskedasticity
  • 6. Freeing up the classical assumptions - autocorrelated errors
  • 7. Instrumental variables method
  • 8. Qualitative choice and limited dependent variable models
  • 9. Univariate time series analysis
  • 10. Regression with time series variables
  • 11. Vector autoregressive models
  • 12. Models for panel data
  • 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
  • WOOLDRIDGE, Jeffrey M. Introductory econometrics : a modern approach. 4th ed. (International stude. Canada: South-Western, 2009, xx, 865. ISBN 9780324585483. 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
Teaching methods
lectures, class discussion, computer labs practices, drills
Assessment methods
homeworks, final project, written and oral exam
Language of instruction
Czech
Follow-Up Courses
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.

logo image
Listed among pre-requisites of other courses
The course is also listed under the following terms Autumn 2009, Autumn 2010, Autumn 2011, Autumn 2012, Autumn 2014, Autumn 2015, Autumn 2016, Autumn 2017, Autumn 2018, Autumn 2019, Autumn 2020, Autumn 2021, Autumn 2022, Autumn 2023, Autumn 2024.

BPE_ZAEK Introduction to Econometrics

Faculty of Economics and Administration
Autumn 2012
Extent and Intensity
2/2. 8 credit(s). Type of Completion: zk (examination).
Teacher(s)
doc. Ing. Daniel Němec, Ph.D. (lecturer)
prof. Ing. Osvald Vašíček, CSc. (lecturer)
doc. Ing. Daniel Němec, Ph.D. (seminar tutor)
RNDr. Dalibor Moravanský, CSc. (seminar tutor)
Mgr. Jaroslav Bil (seminar tutor)
Ing. Vladimír Hajko, Ph.D. (seminar tutor)
prof. Ing. Zdeněk Tomeš, Ph.D. (seminar tutor)
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
Wed 16:20–17:55 P101
  • Timetable of Seminar Groups:
BPE_ZAEK/01: Wed 18:00–19:35 VT206, D. Němec
BPE_ZAEK/02: Wed 9:20–11:00 VT105, J. Bil
BPE_ZAEK/03: Wed 11:05–12:45 VT206, V. Hajko
BPE_ZAEK/04: Tue 11:05–12:45 VT203, D. Moravanský
BPE_ZAEK/05: Mon 12:50–14:30 VT206, D. Moravanský
BPE_ZAEK/06: Thu 11:05–12:45 VT206, D. Němec
BPE_ZAEK/07: Mon 14:35–16:15 VT206, J. Bil
BPE_ZAEK/08: Tue 14:35–16:15 VT206, Z. Tomeš
BPE_ZAEK/09: Tue 16:20–17:55 VT206, D. Moravanský
BPE_ZAEK/10: Tue 12:50–14:30 VT206, Z. Tomeš
BPE_ZAEK/11: Mon 9:20–11:00 VT105, V. Hajko
BPE_ZAEK/12: Mon 11:05–12:45 VT105, V. Hajko
BPE_ZAEK/13: Wed 12:50–14:30 VT105, J. Bil
BPE_ZAEK/14: Thu 9:20–11:00 VT105, D. Němec
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
there are 20 fields of study the course is directly associated with, display
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
  • 1. Introduction to econometrics and working with data
  • 2. A non-technical introduction to regression
  • 3. Simple regression model
  • 4. Multiple regression model
  • 5. Freeing up the classical assumptions - heteroskedasticity
  • 6. Freeing up the classical assumptions - autocorrelated errors
  • 7. Instrumental variables method
  • 8. Qualitative choice and limited dependent variable models
  • 9. Univariate time series analysis
  • 10. Regression with time series variables
  • 11. Vector autoregressive models
  • 12. Models for panel data
  • 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
  • WOOLDRIDGE, Jeffrey M. Introductory econometrics : a modern approach. 4th ed. (International stude. Canada: South-Western, 2009, xx, 865. ISBN 9780324585483. 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
Teaching methods
lectures, class discussion, computer labs practices, drills
Assessment methods
homeworks, final project, written and oral exam
Language of instruction
Czech
Follow-Up Courses
Further comments (probably available only in Czech)
The course is taught annually.
Listed among pre-requisites of other courses
The course is also listed under the following terms Autumn 2009, Autumn 2010, Autumn 2011, Autumn 2013, Autumn 2014, Autumn 2015, Autumn 2016, Autumn 2017, Autumn 2018, Autumn 2019, Autumn 2020, Autumn 2021, Autumn 2022, Autumn 2023, Autumn 2024.

BPE_ZAEK Introduction to Econometrics

Faculty of Economics and Administration
Autumn 2011
Extent and Intensity
2/2. 8 credit(s). Type of Completion: zk (examination).
Teacher(s)
doc. Ing. Daniel Němec, Ph.D. (lecturer)
prof. Ing. Osvald Vašíček, CSc. (lecturer)
doc. Ing. Daniel Němec, Ph.D. (seminar tutor)
RNDr. Dalibor Moravanský, CSc. (seminar tutor)
Mgr. Hana Fitzová, Ph.D. (seminar tutor)
Mgr. Jaroslav Bil (seminar tutor)
Ing. Vladimír Hajko, Ph.D. (seminar tutor)
prof. Ing. Zdeněk Tomeš, Ph.D. (seminar tutor)
Guaranteed by
doc. Ing. Daniel Němec, Ph.D.
Department of Economics – Faculty of Economics and Administration
Contact Person: Lydie Pravdová
Timetable
Wed 16:20–17:55 P101
  • Timetable of Seminar Groups:
BPE_ZAEK/01: Wed 18:00–19:35 VT206, D. Němec
BPE_ZAEK/02: Wed 9:20–11:00 VT105, Z. Tomeš
BPE_ZAEK/03: Wed 11:05–12:45 VT206, V. Hajko
BPE_ZAEK/04: Tue 11:05–12:45 VT203, D. Moravanský
BPE_ZAEK/05: Tue 9:20–11:00 VT203, D. Moravanský
BPE_ZAEK/06: Thu 11:05–12:45 VT206, D. Němec
BPE_ZAEK/07: Mon 14:35–16:15 VT206, D. Němec
BPE_ZAEK/08: Tue 14:35–16:15 VT206, J. Bil
BPE_ZAEK/09: Tue 16:20–17:55 VT206, D. Moravanský
BPE_ZAEK/10: Tue 12:50–14:30 VT206, J. Bil
BPE_ZAEK/11: Mon 8:30–10:05 VT105, V. Hajko
BPE_ZAEK/12: Mon 10:15–11:50 VT105, V. Hajko
BPE_ZAEK/13: Wed 12:50–14:30 VT105, Z. Tomeš
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
there are 21 fields of study the course is directly associated with, display
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
  • 1. Introduction to econometrics and working with data
  • 2. A non-technical introduction to regression
  • 3. Simple regression model
  • 4. Multiple regression model
  • 5. Freeing up the classical assumptions - heteroskedasticity
  • 6. Freeing up the classical assumptions - autocorrelated errors
  • 7. Instrumental variables method
  • 8. Qualitative choice and limited dependent variable models
  • 9. Univariate time series analysis
  • 10. Regression with time series variables
  • 11. Vector autoregressive models
  • 12. Models for panel data
  • 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
  • WOOLDRIDGE, Jeffrey M. Introductory econometrics : a modern approach. 4th ed. (International stude. Canada: South-Western, 2009, xx, 865. ISBN 9780324585483. 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
Teaching methods
lectures, class discussion, computer labs practices, drills
Assessment methods
homeworks, final project, written and oral exam
Language of instruction
Czech
Follow-Up Courses
Further Comments
The course is taught annually.
Listed among pre-requisites of other courses
The course is also listed under the following terms Autumn 2009, Autumn 2010, Autumn 2012, Autumn 2013, Autumn 2014, Autumn 2015, Autumn 2016, Autumn 2017, Autumn 2018, Autumn 2019, Autumn 2020, Autumn 2021, Autumn 2022, Autumn 2023, Autumn 2024.

BPE_ZAEK Introduction to Econometrics

Faculty of Economics and Administration
Autumn 2010
Extent and Intensity
2/2. 8 credit(s). Type of Completion: zk (examination).
Teacher(s)
doc. Ing. Daniel Němec, Ph.D. (lecturer)
prof. Ing. Osvald Vašíček, CSc. (lecturer)
doc. Ing. Daniel Němec, Ph.D. (seminar tutor)
RNDr. Dalibor Moravanský, CSc. (seminar tutor)
Mgr. Hana Fitzová, Ph.D. (seminar tutor)
Ing. Mgr. Pavel Herber (seminar tutor)
Guaranteed by
doc. Ing. Daniel Němec, Ph.D.
Department of Economics – Faculty of Economics and Administration
Contact Person: Lydie Pravdová
Timetable
Wed 16:20–17:55 P101
  • Timetable of Seminar Groups:
BPE_ZAEK/01: Wed 18:00–19:35 VT206, D. Němec
BPE_ZAEK/02: Wed 9:20–11:00 VT105, P. Herber
BPE_ZAEK/03: Wed 11:05–12:45 VT206, P. Herber
BPE_ZAEK/04: Tue 11:05–12:45 VT203, D. Moravanský
BPE_ZAEK/05: Tue 9:20–11:00 VT203, D. Moravanský
BPE_ZAEK/06: Thu 11:05–12:45 VT206, D. Němec
BPE_ZAEK/07: Mon 14:35–16:15 VT206, P. Herber
BPE_ZAEK/08: Tue 14:35–16:15 VT206, H. Fitzová
BPE_ZAEK/09: Tue 16:20–17:55 VT206, D. Moravanský
BPE_ZAEK/10: Tue 12:50–14:30 VT206, H. Fitzová
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
there are 17 fields of study the course is directly associated with, display
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
  • 1. Introduction to econometrics and working with data
  • 2. A non-technical introduction to regression
  • 3. Simple regression model
  • 4. Multiple regression model
  • 5. Freeing up the classical assumptions - heteroskedasticity
  • 6. Freeing up the classical assumptions - autocorrelated errors
  • 7. Instrumental variables method
  • 8. Qualitative choice and limited dependent variable models
  • 9. Univariate time series analysis
  • 10. Regression with time series variables
  • 11. Vector autoregressive models
  • 12. Models for panel data
  • 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
  • WOOLDRIDGE, Jeffrey M. Introductory econometrics : a modern approach. 4th ed. (International stude. Canada: South-Western, 2009, xx, 865. ISBN 9780324585483. 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
Teaching methods
lectures, class discussion, computer labs practices, drills
Assessment methods
homeworks, final project, written and oral exam
Language of instruction
Czech
Follow-Up Courses
Further Comments
The course is taught annually.
Listed among pre-requisites of other courses
The course is also listed under the following terms Autumn 2009, Autumn 2011, Autumn 2012, Autumn 2013, Autumn 2014, Autumn 2015, Autumn 2016, Autumn 2017, Autumn 2018, Autumn 2019, Autumn 2020, Autumn 2021, Autumn 2022, Autumn 2023, Autumn 2024.

BPE_ZAEK Introduction to Econometrics

Faculty of Economics and Administration
Autumn 2009
Extent and Intensity
2/2. 8 credit(s). Type of Completion: zk (examination).
Teacher(s)
doc. Ing. Daniel Němec, Ph.D. (lecturer)
prof. Ing. Osvald Vašíček, CSc. (lecturer)
doc. Ing. Daniel Němec, Ph.D. (seminar tutor)
RNDr. Dalibor Moravanský, CSc. (seminar tutor)
Mgr. Hana Fitzová, Ph.D. (seminar tutor)
doc. Ing. Jan Čapek, Ph.D. (seminar tutor)
Guaranteed by
doc. Ing. Daniel Němec, Ph.D.
Department of Economics – Faculty of Economics and Administration
Contact Person: Lydie Pravdová
Timetable
Wed 16:20–17:55 P101
  • Timetable of Seminar Groups:
BPE_ZAEK/01: Wed 18:00–19:35 VT206
BPE_ZAEK/02: Wed 9:20–11:00 VT105, J. Čapek
BPE_ZAEK/03: Wed 11:05–12:45 VT206, J. Čapek
BPE_ZAEK/04: Tue 11:05–12:45 VT203, D. Moravanský
BPE_ZAEK/05: Tue 9:20–11:00 VT203, D. Moravanský
BPE_ZAEK/06: Thu 11:05–12:45 VT206, D. Němec
BPE_ZAEK/07: Mon 14:35–16:15 VT206
BPE_ZAEK/08: Tue 14:35–16:15 VT206, H. Fitzová
BPE_ZAEK/09: Tue 16:20–17:55 VT206, D. Moravanský
BPE_ZAEK/10: Tue 12:50–14:30 VT206, H. Fitzová
Prerequisites
BPM_STA2 Statistics 2 || PMSTII Statistics II || PřF:M4122 Probability and 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
there are 7 fields of study the course is directly associated with, display
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
  • 1. Introduction to econometrics and working with data
  • 2. A non-technical introduction to regression
  • 3. Simple regression model
  • 4. Multiple regression model
  • 5. Freeing up the classical assumptions - heteroskedasticity
  • 6. Freeing up the classical assumptions - autocorrelated errors
  • 7. Instrumental variables method
  • 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
  • KOOP, Gary. Introduction to econometrics. Chichester: John Wiley & Sons, 2008, 371 s. ISBN 9780470032701. 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
  • WOOLDRIDGE, Jeffrey M. Introductory econometrics : a modern approach. 4th ed. (International stude. Canada: South-Western, 2009, xx, 865. ISBN 9780324585483. 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
Follow-Up Courses
Further comments (probably available only in Czech)
The course is taught annually.
General note: Ekvivalent předmětu PMEM2B, PMEM2A, PMEMMI.
Listed among pre-requisites of other courses
The course is also listed under the following terms Autumn 2010, Autumn 2011, Autumn 2012, Autumn 2013, Autumn 2014, Autumn 2015, Autumn 2016, Autumn 2017, Autumn 2018, Autumn 2019, Autumn 2020, Autumn 2021, Autumn 2022, Autumn 2023, Autumn 2024.
  • Enrolment Statistics (recent)