BPE_INEC Introduction to Econometrics

Faculty of Economics and Administration
Autumn 2010
Extent and Intensity
1/1. 6 credit(s). Type of Completion: zk (examination).
Teacher(s)
doc. Ing. Daniel Němec, Ph.D. (seminar tutor)
Guaranteed by
doc. Ing. Daniel Němec, Ph.D.
Department of Economics – Faculty of Economics and Administration
Contact Person: doc. Ing. Daniel Němec, Ph.D.
Timetable
Mon 12:50–13:35 VT206
  • Timetable of Seminar Groups:
BPE_INEC/01: Mon 13:45–14:30 VT206
Prerequisites
elementary probability and mathematical statistics
Course Enrolment Limitations
The course is offered to students of any study field.
The capacity limit for the course is 24 student(s).
Current registration and enrolment status: enrolled: 0/24, only registered: 0/24, only registered with preference (fields directly associated with the programme): 0/24
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
    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
  • GUJARATI, Damodar N. and Dawn C. PORTER. Basic econometrics. 5th ed. Boston: McGraw-Hill, 2009, xx, 922. ISBN 9780071276252. info
  • WOOLDRIDGE, Jeffrey M. Introductory econometrics : a modern approach. 4th ed. (International stude. Canada: South-Western, 2009, xx, 865. ISBN 9780324585483. info
  • KENNEDY, Peter. A guide to econometrics. 6th ed. Malden: Blackwell, 2008, xii, 585. ISBN 9781405182584. info
Teaching methods
tutorials, class discussion, computer labs practices, drills
Assessment methods
final project, written and oral exam
Language of instruction
English
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 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, Spring 2024, Autumn 2024.
  • Enrolment Statistics (Autumn 2010, recent)
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