We review the fuzzy approach to poverty measurement by comparing poverty indices using different membership functions proposed in the literature. We put our main focus on the issue of estimation of the mean squared errors of these fuzzy methods showing which indices can be more accurately estimated using sample data. By means of simulations, we also investigate the role of parameters of the membership function when it comes to estimating mean squared errors via a robustness analysis.

翻译：本文通过比较文献中提出的不同隶属函数下的贫困指数，综述了贫困测量中的模糊方法。我们主要聚焦于这些模糊方法均方误差的估计问题，揭示了哪些指数能够利用样本数据实现更精确的估计。通过模拟分析，我们还从稳健性角度探讨了隶属函数参数在均方误差估计中所起的作用。