The paper characterizes the class of weakly decomposable (aggregable) inequality measures which satisfy a new (weak) decomposition (and agregation) property. These measures can be decomposed into the sum of the usual within-group and a between-group term which is based on the inequality between...

A certain spectrum, indexed by a\in[0,\infty], of upper bounds P_a(X;x) on the tail probability P(X\geq x), with P_0(X;x)=P(X\geq x) and P_\infty(X;x) being the best possible exponential upper bound on P(X\geq x), is shown to be stable and monotonic in a, x, and X, where x is a real number and X...

A stationary stochastic process is defined to be locally independent if it eventually becomes independent of pastrealizations. I develop a simple nonparametric test for this condition. Size and power comparisons favor this statistic over the one proposed by Brock, Dechert and Scheinkman (1987)...

Abstract In this paper the problem is investigated how to prove that after a specified time t 0 of operation the conditional survival probability of an item is less than the corresponding survival probability of a new item. This problem occurs in various areas like for instance in industry, when...

The bootstrap is a popular and useful tool for estimating the asymptotic variance of complicated estimators. Ironically, the fact that the estimators are complicated can make the standard bootstrap computationally burdensome because it requires repeated re-calculation of the estimator. In...

We propose an Aitken estimator for Gini regression. The suggested A -Gini estimator is proven to be a U-statistics. Monte Carlo simulations are provided to deal with heteroskedasticity and to make some comparisons between the generalized least squares and the Gini regression. A Gini-White test...

Gini index is a widely used measure of economic inequality. This article develops a theory and methodology for constructing a confidence interval for Gini index with a specified confidence coefficient and a specified width without assuming any specific distribution of the data. Fixed sample size...

The bootstrap is a popular and useful tool for estimating the asymptotic variance of complicated estimators. Ironically, the fact that the estimators are complicated can make the standard bootstrap computationally burdensome because it requires repeated re-calculation of the estimator. In...