A note on a modification of the adaptive kernel density estimation of income distribution and poverty index via the range}

In this paper we propose an estimator of Foster, Greer and Thorbecke class of poverty measures. The new estimator is constructed with adaptive kernel and the bandwidth of the new improvement is obtained depending on the range of the observations. Simulated example is presented, including comparisons with four others estimators. The performance of the proposed new estimator is evaluated via the variance and the mean square error criterion. The results of the simulation study are very promising; they show that our modified estimator performs well in all cases.