Simplified Jackknife Variance Estimates for Fuzzy Measures of Multidimensional Poverty

被引：26

作者：

Betti, Gianni ^{[1
]}

Gagliardi, Francesca ^{[1
]}

Verma, Vijay ^{[1
]}

机构：

[1] Univ Siena, Dipartimento Econ Polit & Stat, Siena, Italy

来源：

INTERNATIONAL STATISTICAL REVIEW | 2018年 / 86卷 / 01期

关键词：

variance estimation; resampling methods; Jackknife repeated replication; multi-dimensional deprivation; fuzzy poverty measures; QUALITY-OF-LIFE; RELATIVE POVERTY; COMPLEX SURVEYS; EU-SILC; INDICATORS; DEPRIVATION; LINEARIZATION; PERSPECTIVE; STATISTICS; INCOME;

D O I：

10.1111/insr.12219

中图分类号：

O21 [概率论与数理统计]; C8 [统计学];

学科分类号：

020208 ; 070103 ; 0714 ;

摘要：

In this paper, we present a practical methodology for variance estimation for multi-dimensional measures of poverty and deprivation of households and individuals, derived from sample surveys with complex designs and fairly large sample sizes. The measures considered are based on fuzzy representation of individuals' propensity to deprivation in monetary and diverse non-monetary dimensions. We believe this to be the first original contribution for estimating standard errors for such fuzzy poverty measures. The second objective is to describe and numerically illustrate computational procedures and difficulties in producing reliable and robust estimates of sampling error for such complex statistics. We attempt to identify some of these problems and provide solutions in the context of actual situations. A detailed application based on European Union Statistics on Income and Living Conditions data for 19 NUTS2 regions in Spain is provided.

引用

页码：68 / 86

页数：19

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