Modelling of Conditional Distributions of Wages in the Czech Republic
Abstract
In the text conditional distributions of positive value random variable are studied. The conditions are described by information that the random variable is less or equal to a given value, it is included in a given (finite) interval or greater than a given value. Conditional distribution functions are derived and characteristics of the level and variability are evaluated with the use of numeric methods. The results are applied to monthly gross wages (in CZK) in the Czech Republic in 2008. In the text two models for the probability distribution of wages are used; three parametric lognormal distribution and a mixture of three parametric lognormal densities for men and women. All unknown parameters were estimated with the use of moment method of estimation. Conditional moment and quantile characteristics of location (median, expected value) and variability (quartile deviation, standard deviation, coefficient of variation) are evaluated and given in the tables in order to obtain estimated characteristics and to compare results from different models fitted to the same dataset.References
Bartošová, J. Logarithmic-Normal Model of Income Distribution in the Czech Republic. Austrian Journal of Statistics, Vol. 35, No. 23, s. 215 – 222. 2006.
Bartošová, J., Bína, V. Modelling of income distribution of Czech households in years 1996-2005. Acta Oeconomica Pragensia, roč. 17, č. 4, s. 3–18. 2009.
Bílková, D. Application of Lognormal Curves in Modeling of Wage Distributions. Journal of Applied Mathematics, Vol. 1, No. 2, pp. 341 – 352. 2008.
Bílková, D. Analysis of the Development in Wage Distributions of Men and Women in the Czech Republic in Recent Years. Statistika, 2011, roč. 48, č. 1, s. 40–57. 2011.
Bílková, D. Malá, I. Modelling the Income Distributions in the Czech Republic since 1992. Austrian Journal of Statistics, 41 (2), 133–152. 2012.
Bílková, D. Recent Development of the Wage and Income Distribution in the Czech Republic. Prague Economic Papers: 21 (2), 233–250. 2012.
Cohen A.C., Whitten J.B. Estimation in the three-parameter lognormal distribution, Journal of American Statistical Association, 75,399-404. 1980.
Kleiber, C., Kotz, S. Statistical size distributions in economics and actuarial sciences. Hoboken : John Wiley and Sons. 2003.
Malá. I. The use of finite mixtures of lognormal distributions in the modeling of incomes in the Czech Republic. Research Journal of Economics, Business and ICT, 2011, Vol. 4, 41–46. 2011.
McLachlan, G. J., Peel, D. Finite Mixture Models. Wiley series in Probability and Mathematical Statistics: Applied Probability and Statistics Section, New York. 2000.
Pacáková,V., Sipková,L. Generalized Lambda Distributions of Households Incomes. E + M Ekonomie a Management, Vol.10, Iss.1, s. 98 – 107. 2007.
CZSO. Czech statistical office. www.czso.cz. [2012-10-15]
CNB. Czech National Bank. www.cnb.cz. [2012-10-10]
RPROGRAM. R Core Team. R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. 2012. http://www.R-project.org/. [2012-10-20]
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