Course syllabus EKM2 - Econometrics II (FBE - WS 2020/2021)

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Course code: EKM2
Course title in language of instruction: Ekonometrie II
Course title in Czech: Econometrics II
Course title in English: Econometrics II
Mode of completion and number of credits: Exam (5 credits)
(1 ECTS credit = 28 hours of workload)
Mode of delivery/Timetabled classes: full-time, 2/2 (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: master continuing
Semester: WS 2020/2021
Name of lecturer: doc. Mgr. David Hampel, Ph.D. (supervisor)
Prerequisites: Final Bachelor Exam and not Uznaný předmět pro obor REO
Aims of the course:
Mastery of theory of multivariate econometric models formation using OLS method, its prerequisites and issue violations, including practical use of the methodology in the field of cross-sectional data and time series. Theoretical and practical knowledge of advanced methods of time series analysis involving the Box-Jenkins methodology and the related methods.
Course contents:
1.Classical linear regression model and its assumptions (allowance 5/6)
a.Classical linear regression model with multiple explanatory variables
b.Hypothesis testing in the linear regression model
c.Assumptions of classical linear regression model

2.Violations and remedies of classical linear regression model assumptions (allowance 6/6)
a.Model specification
c.Serial correlations

3.Specific problems of economic time series analysis (allowance 3/3)
a.Nonlinearity of time series
b.Seasonality and periodicity in time series
c.Nonstationarity of time series
d.The seeming dependence in time series
e.Cointegration of time series

4.Advanced methods for the analysis of univariate time series (allowance 7/5)
a.Stationary Box-Jenkins ARMA processes
b.Nonstationary Box-Jenkins ARIMA processes
c.Seasonal Box-Jenkins SARIMA processes
d.Volatility models

5.Advanced methods for the analysis of multivariate time series (allowance 3/2)
a.Vector autoregressive model (VAR)
b.Granger causality

6.Nonlinear models (allowance 2/2)
a.Nonlinear least squares
b.Logit model

7.Presentation of selected econometric problems (allowance 0/4)
8.Analysis of panel data (allowance 2/0)
a.Elementary models of panel data
b.Panel data analysis in software Gretl

Learning outcomes and competences:
Generic competences:
-Ability to analyse and synthesize
-Ability to create new ideas (creativity)
-Ability to solve problems
-Skilled at utilizing and processing information

Specific competences:
-Student is able to apply the theory associated with a multidimensional regression model to real data.
-Student is able to apply the VAR model and interpret the results.
-Student is able to create models of one-dimensional time series according to Box-Jenkins methodology.
-Student is able to solve problems arising in the construction of multidimensional regression model.
-Student is able to work with non-linear models.
-Student knows and is able to apply advanced econometric models and methods.

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: -
Learning activities and study load (hours of study load):
Type of teaching methodDaily attendanceCombined form
Direct teaching
     lecture28 h16 h
     practice28 h0 h
     preparation for exam36 h50 h
     preparation for regular assessment8 h4 h
     preparation for regular testing20 h20 h
     elaboration and execution of projects20 h50 h
Total140 h140 h
Assessment methods:
Participation in the seminar is compulsory, attendance is considered to be fulfilled if the student visits at least 9 seminars. Active participation is required in the seminary (the student has an overview of the lectured topics and can elaborate the basic exercises demonstrated at the lectures).

During the semester, it is necessary to pass a continuous test, ie to get at least 13 points out of the total possible 20 points. Students will bring only the student card to the test. Students can not use any papers or calculator during the test. The test can be repeated twice.

Furthermore, it is necessary to successfully defend the semestral project, which includes in particular the compilation and analysis of a multidimensional econometric model including quantification and its verification. The defense is considered successful or unsuccessful. The unsuccessful project can be reworked once.

If a students complete attendance (only in the case of a full-time form), successfully pass the test and successfully defends a semester project, they are eligible to apply for the exam. Otherwise, the final score will not be "not present".

The exam is in the form of a written work and is considered successful if the gain is at least 50 points out of a total of 100 points. If students are not successful in writing, they are rated F. If students successfully pass a written work, the subject assessment is given by the sum of the points obtained from the the written exam:
(91; 100) points - A
(82; 90) points - B
(73; 81) points - C
(64; 72) points - D
[55; 63] points - E

Students will bring writing accessories and the student card for written work. Students can not use their own papers or a calculator.

Any copying, recording or excerpt of tests and written works, the use of illicit devices as well as means of communication or other impairment of objectivity in the verification of knowledge will be considered gross violation of the study regulations. As a result, the course is closed in the UIS by F; F; F. Further, teacher can initiate disciplinary proceedings, which may result in termination of studies.

The course is not possible to enroll in a foreign trip.
Recommended reading:
TypeAuthorTitlePublished inPublisherYearISBN
RQHAMPEL, D. -- BLAŠKOVÁ, V. -- STŘELEC, L.Ekonometrie 2BrnoMendelova univerzita v Brně2012978-80-7375-664-2
RQCIPRA, T.Finanční ekonometriePrahaEkopress2008978-80-86929-43-9
RQGUJARATI, D N. -- PORTER, D C.Basic econometricsBostonMcGraw-Hill Irwin978-007-127625-2
REARLT, J. -- ARLTOVÁ, M.Ekonomické časové řady: [vlastnosti, metody modelování, příklady a aplikace]PrahaGrada2007978-80-247-1319-9
REGREENE, W H.Econometric analysisBoston [u.a.]Pearson2012978-0-273-75356-8
REKMENTA, J.Elements of econometricsAnn ArborUniversity of Michigan Press20110-472-10886-7


Last modification made by Ing. Jiří Gruber on 11/05/2019.

Type of output: