J
2016
Another Approaches to Modeling the Wage and Income Distribution Based on the Use of Order Statistics
BÍLKOVÁ, Diana
Basic information
Original name
Another Approaches to Modeling the Wage and Income Distribution Based on the Use of Order Statistics
Authors
BÍLKOVÁ, Diana (203 Czech Republic, guarantor, belonging to the institution)
Edition
International Journal of Mathematical and Computer Modelling, 2016, 2051-4271
Other information
Type of outcome
Článek v odborném periodiku
Field of Study
50200 5.2 Economics and Business
Country of publisher
United Kingdom of Great Britain and Northern Ireland
Confidentiality degree
není předmětem státního či obchodního tajemství
RIV identification code
RIV/04274644:_____/16:#0000115
Organization unit
University of Finance and Administration
Keywords in English
Order statistics; L-moments and TL-moments; probability density function; distribution function; quantile function
Tags
International impact, Reviewed
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.
Displayed: 2/11/2024 23:32