BPE_INEC Introduction to Econometrics

Faculty of Economics and Administration
Spring 2024
Extent and Intensity
1/2/0. 6 credit(s). Type of Completion: zk (examination).
Teacher(s)
Riga Qi (lecturer)
Riga Qi (seminar tutor)
doc. Ing. Daniel Němec, 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
Thu 16:00–17:50 VT314, except Thu 4. 4.
  • Timetable of Seminar Groups:
BPE_INEC/01: Thu 18:00–18:50 VT314, except Thu 4. 4., R. Qi
Prerequisites
(! BPE_AIEC Introduction to Econometrics ) && (!NOWANY( BPE_AIEC Introduction to Econometrics ))
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.
The capacity limit for the course is 24 student(s).
Current registration and enrolment status: enrolled: 4/24, only registered: 0/24, only registered with preference (fields directly associated with the programme): 0/24
fields of study / plans the course is directly associated with
Course objectives
The course is designed to give students experience in using econometric methods important in economics, finance and other business subjects. It provides skills in regression essential for understanding much of the literature on economics, finance, and empirical studies in other business areas.
We begin with the simple regression and multiple regression models. They are treated in depth and have a range of applications. Careful attention is given to interpreting regression results, statistical inference and hypothesis testing. A part of the course introduces various specification and diagnostics tests and the problem of endogeneity and instrumental variables methods.
By the end of the course, students should be able to use regression models in many different applications and critically examine reported regression results in empirical research in economics and other business studies. They will be able to identify and deal with many econometric problems in analysing cross-section data and will have experience with a range of essential econometric tools and 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 modelling, estimation, inference, and forecasting in the context of real-world economic problems.
They can evaluate critically the results and conclusions from others who use essential econometric tools and techniques.
They have a foundation and understanding for further study of econometrics.
They appreciate the range of more advanced techniques that may be covered in advanced econometric courses.
Syllabus
  • 1. The Nature of Econometrics and Economic data
  • 2. The Simple Regression Model
  • 3. Multiple Regression Analysis: Estimation
  • 4. Multiple Regression Analysis: Inference
  • 5. Multiple Regression Analysis: OLS Asymptotics
  • 6. Multiple Regression Analysis: Further Issues
  • 7. Multiple Regression Analysis with Qualitative Information
  • 8. Heteroskedasticity
  • 9. More on Specification and Data Issues
  • 10. Instrumental Variables Estimation and Two-Stage Least Squares
Literature
    required literature
  • WOOLDRIDGE, Jeffrey M. Introductory econometrics : a modern approach. Seventh edition. Boston: Cengage Learning, 2020, xxi, 826. ISBN 9781337558860. info
  • HEISS, Florian. Using R for introductory econometrics. 2nd edition. Düsseldorf: Florian Heiss, 2020, 368 stran. ISBN 9788648424364. 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
Teaching methods
tutorials, class discussion, computer labs practices, drills
Assessment methods
assignments in the seminar group, homework, written exam
Language of instruction
English
Follow-Up Courses
Further Comments
Study Materials
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 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 (Spring 2024, recent)
  • Permalink: https://is.muni.cz/course/econ/spring2024/BPE_INEC