Simplified Jackknife Variance Estimates for Fuzzy Measures of Multidimensional Poverty

Gianni Betti, Francesca Gagliardi and Vijay Verma

International Statistical Review, 2018, vol. 86, issue 1, 68-86

Abstract: 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.

Date: 2018
References: Add references at CitEc
Citations: View citations in EconPapers (13)

Downloads: (external link)
https://doi.org/10.1111/insr.12219

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:bla:istatr:v:86:y:2018:i:1:p:68-86

Ordering information: This journal article can be ordered from
http://www.blackwell ... bs.asp?ref=0306-7734

Access Statistics for this article

International Statistical Review is currently edited by Eugene Seneta and Kees Zeelenberg

More articles in International Statistical Review from International Statistical Institute Contact information at EDIRC.
Bibliographic data for series maintained by Wiley Content Delivery ().