Course syllabus EKM1 - Econometrics I (FBE - WS 2017/2018)

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Course code: EKM1
Course title in language of instruction: Ekonometrie I
Course title in Czech: Econometrics 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 (hours of lectures per week / hours of seminars per week)
part-time, 16/0 (lectures per period / seminars per period)
Language of instruction: Czech
Level of course: bachelor
Semester: WS 2017/2018
Name of lecturer: doc. Ing. Luboš Střelec, Ph.D. (examiner, supervisor)
Prerequisites: Statistics
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, multiple and partial 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
e.Tests of model specification, LM test of specification and RESET test

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, exponential filters
c.Time series decomposition
d.Modeling seasonality
e.Models based on filters
f.Causal regression models
g.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: optional
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: -
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 h78 h
     preparation for regular testing15 h0 h
     preparation of presentation5 h0 h
     writing of seminar paper25 h46 h
Total140 h140 h
Assessment methods:
Midterm exam (50 minutes) is held after regression and correlation material is completed (minimum 60% score is required to pass). Written report of the semester project (16-22 pages) is due at the end of the semester. PowerPoint presentations of the project are planned before the class. The project is graded on pass - fail basis. Course grade is primarily based on written final exam (60 minutes) covering real-world problems and answering theoretical questions. Minimum 55% score is required to receive a passing grade.
Recommended reading:
TypeAuthorTitlePublished inPublisherYearISBN
RQADAMEC, V. -- STŘELEC, L. -- HAMPEL, D.Ekonometrie I: učební text978-80-7375-703-8
RQADAMEC, V. -- STŘELEC, L.Ekonometrie I: cvičebniceBrnoMendelova univerzita v Brně2013978-80-7375-706-9
REGUJARATI, D N. -- PORTER, D C.Basic econometricsBostonMcGraw-Hill Irwin978-007-127625-2
REHAMPEL, D. -- BLAŠKOVÁ, V. -- STŘELEC, L.Ekonometrie 2BrnoMendelova univerzita v Brně2012978-80-7375-664-2
REHINDLS, R. et al.Statistika pro ekonomyPrahaProfessional publishing200680-86946-16-9
REHUŠEK, R. -- PELIKÁN, J.Aplikovaná ekonometrie: teorie a praxePrahaProfessional Publishing200380-86419-29-0
REMAREK, L. et al.Statistika pro ekonomy: aplikacePrahaProfessional Publishing2007978-80-86946-40-5


Last modification made by Ing. Jiří Gruber on 08/28/2017.

Type of output: