J 2016

Another Approaches to Modeling the Wage and Income Distribution Based on the Use of Order Statistics

BÍLKOVÁ, Diana

Základní údaje

Originální název

Another Approaches to Modeling the Wage and Income Distribution Based on the Use of Order Statistics

Autoři

BÍLKOVÁ, Diana (203 Česká republika, garant, domácí)

Vydání

International Journal of Mathematical and Computer Modelling, 2016, 2051-4271

Další údaje

Jazyk

angličtina

Typ výsledku

Článek v odborném periodiku

Obor

50200 5.2 Economics and Business

Stát vydavatele

Velká Británie a Severní Irsko

Utajení

není předmětem státního či obchodního tajemství

Kód RIV

RIV/04274644:_____/16:#0000115

Organizační jednotka

Vysoká škola finanční a správní

Klíčová slova anglicky

Order statistics; L-moments and TL-moments; probability density function; distribution function; quantile function

Štítky

Příznaky

Mezinárodní význam, Recenzováno
Změněno: 19. 4. 2017 15:04, Ing. Dominika Moravcová

Anotace

V originále

Despite not producing good results, the method of moments is commonly applied when constructing the parametric distribution for a data file. An alternative approach is to use the so-called order statistics. The present paper deals with the application of order statistics (parameter estimation methods of L-moments and TL-moments) to the economic data. Theoretical advantages of L-moments over conventional moments become obvious when applied to small data sets, e.g. in hydrology, meteorology and climatology, considering extreme precipitation in particular. The main aim of this paper is to apply the two methods to large data sets, comparing their parametric estimation accuracy with that of the maximum likelihood method. The methods of L-moments and TL-moments are utilized for the construction of income and wage distribution models. Three-parameter lognormal curves represent the basic theoretical probability distribution whose parameters were estimated simultaneously by the three methods of parameter estimation, their accuracy having been then evaluated.