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Econometrics - NEKN041

Title:	Ekonometrie
Guaranteed by:	Department of Probability and Mathematical Statistics (32-KPMS)
Faculty:	Faculty of Mathematics and Physics
Actual:	from 2018
Semester:	winter
E-Credits:	6
Hours per week, examination:	winter s.:4/0, Ex [HT]
Capacity:	unlimited
Min. number of students:	unlimited
4EU+:	no
Virtual mobility / capacity:	no
State of the course:	cancelled
Language:	Czech
Teaching methods:	full-time
Teaching methods:	full-time

Guarantor:	prof. RNDr. Tomáš Cipra, DrSc.
Classification:	Mathematics > Math. Econ. and Econometrics, Probability and Statistics
Co-requisite :	{NSTP097 nebo (NSTP201 a NSTP202)}
Interchangeability :	NMEK432
Is co-requisite for:	NEKN025, NEKN042, NEKN007
Is incompatible with:	NEKN001

Opinion survey results Examination dates Schedule Noticeboard

Annotation -

Last update: T_KPMS (13.05.2010)

Overview of modern methods used in econometrics. Econometric problems of linear regression (heteroscedasticity, autocorrelated residuals, multicollinearity, estimation methods, models with a priori restrictions). Discrete and limited dependent variables. Econometric systems of equations (SUR model, simultaneous-equations model, identification problem, estimation methods). Vector autoregression (causality, response to impulse, cointegration). Requierements: Basic knowledge of statistics.

Aim of the course -

Last update: T_KPMS (09.05.2008)

The students should master the most important methods of modern econometrics so that they are capable to apply them in practice. The applications in finance are preferred.

Literature - Czech

Last update: prof. RNDr. Tomáš Cipra, DrSc. (09.09.2013)

Cipra, T.: Finanční ekonometrie. Ekopress, Praha 2008

Cipra, T.: Matematika cenných papírů. Professional Publishing, Praha 2013

Teaching methods -

Last update: G_M (27.05.2008)

Lecture.

Syllabus -

Last update: T_KPMS (13.05.2010)

I. Subject of econometrics.

II. Econometric problems of linear regression (heteroscedasticity, autocorrelated residuals, multicollinearity, estimation methods, models with a priori restrictions).

III. Discrete and limited dependent variables.

IV. Econometric systems of equations: 1. General formulation. 2. SUR model. 3. Simultaneous-equations model. 4. Identification problem. 5. Estimation methods.

V. Vector autoregression: 1. Causality. 2. Response to impulse. 3. Cointegration.