A multidimensional view on poverty in the European Union by partial order theory

Paola Annoni, Rainer Bruggemann and Lars Carlsen

Journal of Applied Statistics, 2015, vol. 42, issue 3, 535-554

Abstract: Poverty can be seen as a multidimensional phenomenon described by a set of indicators, the poverty components. A one-dimensional measure of poverty serving as a ranking index can be obtained by combining the component indicators via aggregation techniques. Ranking indices are thought of as supporting political decisions. This paper proposes an alternative to aggregation based on simple concepts of partial order theory and illustrates the pros and cons of this approach taking as case study a multidimensional measure of poverty comprising three components - absolute poverty, relative poverty and income - computed for the European Union regions. The analysis enables one to highlight conflicts across the components with some regions detected as controversial, with, for example, low levels of relative poverty and high levels of monetary poverty. The partial order approach enables one to point to the regions with the most severe data conflicts and to the component indicators that cause these conflicts.

Date: 2015
References: View complete reference list from CitEc
Citations: View citations in EconPapers (12)

Downloads: (external link)
http://hdl.handle.net/10.1080/02664763.2014.978269 (text/html)
Access to full text is restricted to subscribers.

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:taf:japsta:v:42:y:2015:i:3:p:535-554

Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/CJAS20

DOI: 10.1080/02664763.2014.978269

Access Statistics for this article

Journal of Applied Statistics is currently edited by Robert Aykroyd

More articles in Journal of Applied Statistics from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().