In this paper we present some nonparametric bootstrap methods to construct distributionfree confidence intervals for inequality indices belonging to the Gini family. These methods have a coverage accuracy better than that obtained with the asymptotic distribution of their natural estimators, typically the standard normal. The coverage performances of these methods are evaluated for the index R by Gini with a Monte Carlo experiment on samples simulated.
Confidence interval estimation for inequality indices of the Gini Family.
PROVASI, CORRADO;
1998
Abstract
In this paper we present some nonparametric bootstrap methods to construct distributionfree confidence intervals for inequality indices belonging to the Gini family. These methods have a coverage accuracy better than that obtained with the asymptotic distribution of their natural estimators, typically the standard normal. The coverage performances of these methods are evaluated for the index R by Gini with a Monte Carlo experiment on samples simulated.File in questo prodotto:
Non ci sono file associati a questo prodotto.
Pubblicazioni consigliate
I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.