On reliability of estimates of inequality in distributions derived from sample survey data

On reliability of estimates of inequality in distributions derived from sample survey data

Descripción

For studying inequalities in populations, the interest often lies in estimating frequency distributions. Several factors of interest, such as income or expenditure, depict highly skewed distributions. The study of economic inequality with respect to such distributions is of common interest, and estimation of frequency distributions is more meaningful in such cases. The sample surveys planned for estimating population parameters such as the mean or total may not adequately capture the d istributional properties of the populations needed for estimation of frequency distributions. Among several measures of inequalities, the Lorenz ratio or Gini concentration coefficient (G) is considered as one of the most important measures. Estimation of G involves estimation of frequency distributions as well. It may not be reasonable to estimate these parameters from data collected through sample surveys planned for the estimation of the mean or total. The reliability of such sampli ng designs as well as estimates of G needs to be investigated. In this paper, the problem of choice of sampling designs for estimation of G as well as frequency distributions is attempted. Since studying the distributional properties of estimators of such complex parameters is not simple, the problem is approached empirically on simulated data.