Modeling of wage distribution in recent years in the Czech republic using L-moments and the prediction of wage distribution by industry

L-moments are based on the linear combinations of order statistics. The question of L-moments presents a general theory covering the summarization and description of sample data sets, the summarization and description of theoretical distributions, but also the estimation of parameters of probability distributions and hypothesis testing for parameters of probability distributions. L-moments can be defined for any random variable in the case that its mean exists. Within the scope of modelling of wage distributions we currently use the method of conventional moments, the quantile method or the maximum likelihood method. The theory of L-moments parallels the other theories and the main advantage of the method of L-moments over these methods is that L-moments suffer less from impact of sampling variability. L-moments are more robust and they provide more secure results in the case of small samples. The three-parametric lognormal distribution is one from the most frequent used distributions within the frame of modelling wage and income distribution. In the case of wage distributions we usually work with very large data sets and in such cases the method of L-moments provides say about alike accurate results as for example the method of moment or quantile method. The question of fitness of concrete parametric distribution for model of wage distribution tends to rejection of tested hypothesis about supposed form distribution practically always in the cases of such large samples. In this connection we can see close relationship between sample size and the value of criterion χ 2 , too. The forecasts of wage distributions were constructed based on the observance of previous development. Within the frame of the financilal crisis were set free the employees with very low wages above all. The effect of this truth to forecasts of wage distribution will be exactly known in the autumn of this year