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Course, academic year 2023/2024
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Advanced Topics on Econometrics - NMEK563
Title: Pokročilé partie ekonometrie
Guaranteed by: Department of Probability and Mathematical Statistics (32-KPMS)
Faculty: Faculty of Mathematics and Physics
Actual: from 2018
Semester: winter
E-Credits: 3
Hours per week, examination: winter s.:2/0, Ex [HT]
Capacity: unlimited
Min. number of students: unlimited
4EU+: no
Virtual mobility / capacity: no
State of the course: not taught
Language: Czech
Teaching methods: full-time
Teaching methods: full-time
Guarantor: doc. RNDr. Petr Lachout, CSc.
Class: M Mgr. PMSE
M Mgr. PMSE > Volitelné
Classification: Mathematics > Math. Econ. and Econometrics, Probability and Statistics
Pre-requisite : NMEK432
Is interchangeable with: NEKN007
Annotation -
Last update: T_KPMS (05.05.2015)
The lecture follows lecture NMEK432 with specialization on the mathematical theory of modern econometrics. Linear regression with general loss function. Censored data.
Aim of the course -
Last update: T_KPMS (10.05.2013)

Presentation of advanced methods of econometrics.

Literature - Czech
Last update: T_KPMS (10.05.2013)

Drymes, P.J.: Mathematics for Econometrics. Springer Verlag, New York, 1984

Drymes, P.J.: Topics in Advanced Econometrics. Springer Verlag, New York, 1994

Fomby, T.B., Hill, R.C., Johnson, S.R.:Advance Econometric Methods. Springer Verlag, New York, 1984

Teaching methods -
Last update: T_KPMS (10.05.2013)

Lecture.

Syllabus -
Last update: T_KPMS (10.05.2013)

1. Linear regression model.

2. Estimation of regression parameters.

3. M-estimators and efficient estimators.

4. Consistency and speed of convergence of these estimators.

5. Linear regression model adapted for economical applications.

6. Error dependence in linear regression model.

7. Autoregressive model.

8. Censored linear regression model.

 
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