Estimation of inequality indices based on ranked set sampling

Abstract

Measuring the income inequality is a major concern of the economists. Therefore, numerous indices have been devised to show different features of the income inequality. In general, the simple random sampling procedure is commonly utilized to estimate the inequality measures, while the ranked set sampling is a more cost saving method which increases the precision and the efficiency of the inequality estimators. In this paper the advantages of the ranked set sampling when measuring the amount of the income inequality are examined. Through using Monte Carlo simulation technique, this paper proves that the ranked set sampling, increases the precision of inequality indices estimations. In the end, a real income data set is analyzed to illustrate the obtained results.

Keywords

• Ranked set sampling,Gini index,Theil index,MLD index,Atkinson index,Monte Carlo simulation,Generalized beta distribution of the first kind,Generalized beta distribution of the second kind,Generalized gamma distribution

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