ESF:PMEM2A Math Methods in Economics II - Course Information

PMEM2A Mathematical Methods in Economics II

Extent and Intensity

2/2/0. 5 credit(s). Type of Completion: zk (examination).

Teacher(s)

prof. Ing. Osvald Vašíček, CSc. (lecturer)
doc. Ing. Jan Čapek, Ph.D. (seminar tutor)
Mgr. Hana Fitzová, Ph.D. (seminar tutor)
prof. Ing. Osvald Vašíček, CSc. (seminar tutor)

Guaranteed by

prof. Ing. Osvald Vašíček, CSc.
Department of Applied Mathematics and Computer Science – Faculty of Economics and Administration
Contact Person: Lenka Hráčková

Timetable

Thu 11:05–12:45 P101

• Timetable of Seminar Groups:

PMEM2A/1: Wed 7:40–9:15 VT206, J. Čapek
PMEM2A/2: Wed 17:10–18:45 VT206, J. Čapek
PMEM2A/3: Wed 11:05–12:45 VT206, O. Vašíček
PMEM2A/4: Thu 7:40–9:15 VT206, H. Fitzová
PMEM2A/5: Thu 9:20–11:00 VT206, H. Fitzová
PMEM2A/6: Thu 13:45–15:20 VT206, J. Čapek

Prerequisites (in Czech)

PMSTII Statistics II

Course Enrolment Limitations

The course is also offered to the students of the fields other than those the course is directly associated with.
The capacity limit for the course is 120 student(s).
Current registration and enrolment status: enrolled: 0/120, only registered: 0/120, only registered with preference (fields directly associated with the programme): 0/120

fields of study / plans the course is directly associated with

there are 7 fields of study the course is directly associated with, display

Course objectives

Economic-Mathematical Methods II A (PMEM2A): The course deals with mathematical-statistical approaches to the analysis of economic processes described by time series. The introductory part of the course acquaints students with the basics of work with index numbers and their application in the area of time series. The course participants are also introduced to the methodological premises and the application of the classic procedures of time series decomposition, based on regression. These are non-adaptive methods of description of the process development by a trend expressed by mathematical curves, and adaptive methods, such as polynomial moving averages and methods of exponential smoothing. Simple regression methods of removal of seasonal influence in time series are also covered. Last but not least, this part of the course also explains and applies in practice the procedures of forecasts based on time series smoothed by the above-mentioned methods. The next part of the course focuses on the Box-Jenkins methodology of the analysis of time series, using stochastic and correlation properties of time series. These are particularly the methods of moving totals processes analysis (MA), autoregression processes (AR) and mixed processes (ARMA and ARIMA). The final part of the course summarises the gained knowledge and is devoted to the explanation of the process of behaviour of one economic variable on the basis of behaviour of other variables through a quantified, statistically analysed single-equation model and the use of the model for a forecast of the explained variable s development. Credit requirements: active participation, a sufficient total of points from eaach of progressive skill tests or an essay. Examination: written, a practical economic exercise on a computer, oral.

Literature

• ARLT, Josef. Moderní metody modelování ekonomických časových řad. Vyd. 1. Praha: Grada, 1999, 307 s. ISBN 8071695394. info
• KOZÁK, Josef, Josef ARLT and Richard HINDLS. Úvod do analýzy ekonomických časových řad. 1. vyd. Praha: Vysoká škola ekonomická v Praze, 1994, 208 s. ISBN 8070797606. info

Language of instruction

Czech

Further comments (probably available only in Czech)

Study Materials
The course is taught annually.
Information on course enrolment limitations: 10 pouze přednáška

• Enrolment Statistics (Spring 2006, recent)
  
• Permalink: https://is.muni.cz/course/econ/spring2006/PMEM2A