Study programmes / B-EPA Economic policy and administration / Econometrics I
Course code:EKM1
Course title in language of instruction:Ekonometrie I
Course title in Czech:Ekonometrie I
Course title in English:Econometrics I
Mode of completion and number of credits:Exam (5 credits)
(1 ECTS credit = 28 hours of workload)
Mode of delivery/Timetabled classes:full-time, 1/2; part-time, 16/0
(full-time, hours of lectures per week / hours of seminars per week; part-time, lectures per period / seminars per period)
Language of instruction:Czech
Level of course:bachelor
Semester:SS 2019/2020 - FBE
Name of lecturer:doc. Ing. Luboš Střelec, Ph.D. (supervisor)
Aims of the course:Obtaining theoretical knowledge and practical experience with construction of basic econometric models based on linear regression and models of univariate time series. Students are able to evaluate the econometric models, interpret in economic context and apply for predictions. Students can apply statistical software. Knowledge and skills learned in this course are expected to be used during work on student bachelor's thesis.
Course contents:
1.Introduction to Econometrics (allowance 1/0)
a.Definition of Econometrics, evolution and history
b.Basic steps of econometric analysis
c.Econometric data types

2.Regression and correlation analysis, error term (allowance 4/6)
a.Regression analysis, regression model, variables in regression model
b.Ordinary Least Squares (OLS)
c.Fits, residuals
d.Decomposition of variability, coefficient of determination, information criteria
e.Analysis of variance (ANOVA)
f.Correlation analysis, pairwise coefficient of correlation

3.Testing statistical hypotheses, confidence intervals (allowance 2/4)
a.Tests of significance for regression coefficients (t-tests) and test of overall model significance (F-test)
b.Confidence interval for regression coefficients
c.Confidence interval and prediction interval for the model
d.Significance test of correlation coefficient

4.Gauss-Markov theorem, classical model assumptions (allowance 2/4)
a.Classical assumptions and methods of verification
b.Properties of OLS estimator under Gauss-Markov theorem
c.Violations of classical requirements, consequences for the model

5.Introduction to time series analysis (allowance 1/2)
a.Time series data, definition, properties, types
b.Time series dynamics

6.Models of time series (allowance 4/8)
a.Qualitative (expert) methods
b.Moving averages
c.Time series decomposition
d.Trend analysis, structural break and its detection
e.Modeling seasonality
f.Modeling cyclicality
g.Causal regression models
h.Spurious regression
i.Criteria of model fit

7.Applied econometrics (allowance 0/4)
a.Student presentations, discussion

Learning outcomes and competences:
Generic competences:
-ability to analyse and synthesize
-ability to apply knowledge
-basic computing skills
-science and research skills
-skilled at utilizing and processing information
-work in team

Specific competences:
-Ability to apply the principles of constructing model of univariate time series
-Ability to build econometric model on cross-sectional economic data.
-Understanding the principles of constructing econometric models
-Understanding the statistical methods to describe relationship between two economic variables.

Type of course unit:required
Year of study:Not applicable - the subject could be chosen at anytime during the course of the programme.
Work placement:There is no compulsory work placement in the course unit.
Recommended study modules:none
Assessment methods:For assessment, the active participation in seminars, fulfillment of the ongoing test conditions (minimum 50% score of each test is required) and succesful advocation of semester project are required. The course is completed by a written examination covering the theoretical and practical part (minimum 50% is required). Totally, score above 50% is required to receive a passing grade. The same requirements hold for combined form of study except active participation in seminars.
Learning activities and study load (hours of study load)
Type of teaching methodDaily attendanceCombined form
Direct teaching
     lecture14 h16 h
     practice28 h0 h
     preparation for exam53 h68 h
     preparation for regular testing15 h20 h
     preparation of presentation5 h0 h
     writing of seminar paper25 h36 h
Total140 h140 h

Basic reading list
  • ADAMEC, V. -- STŘELEC, L. -- HAMPEL, D. Ekonometrie I: učební text. 1st ed. 162 p. ISBN 978-80-7375-703-8.
  • ADAMEC, V. -- STŘELEC, L. Ekonometrie I: cvičebnice. 138 p. ISBN 978-80-7509-396-7.
Recommended reading list
  • ARLT, J. -- ARLTOVÁ, M. Ekonomické časové řady. 1st ed. Praha: Professional Publishing, 2009. 290 p. ISBN 978-80-86946-85-6.
  • CIPRA, T. Finanční ekonometrie. 1st ed. Praha: Ekopress, 2008. 538 p. ISBN 978-80-86929-43-9.
  • GUJARATI, D N. -- PORTER, D C. Basic econometrics. 5th ed. Boston: McGraw-Hill Irwin, 922 p. ISBN 978-007-127625-2.
  • HAMPEL, D. -- BLAŠKOVÁ, V. -- STŘELEC, L. Ekonometrie 2. 3rd ed. Mendelova univerzita v Brně, 2016. 153 p. ISBN 978-80-7509-427-8.
  • HINDLS, R. et al. Statistika pro ekonomy. 8th ed. Praha: Professional Publishing, 2007. 415 p. ISBN 978-80-86946-43-6.
  • HUŠEK, R. Aplikovaná ekonometrie: teorie a praxe. 1st ed. Praha: Oeconomica, 2009. 344 p. Vysokoškolská učebnice. ISBN 978-80-245-1623-3.
  • HUŠEK, R. Ekonometrická analýza. 1st ed. Praha: Oeconomica, 2007. 367 p. ISBN 978-80-245-1300-3.
  • MAREK, L. et al. Statistika pro ekonomy: aplikace. 2nd ed. Praha: Professional Publishing, 2007. 485 p. ISBN 978-80-86946-40-5.
  • STUDENMUND, A H. Using econometrics. 6th ed. Boston: Addison-Wesley, 2010. 616 p. ISBN 978-0-13-136773-9.