Non-parametric estimation and evaluation of capability sets
Gender differences in Italian children's capabilities
Pim Verbunt,
Nicky Rogge and
Tom Van Puyenbroeck
Oxford Economic Papers, 2022, vol. 74, issue 1, 265-296
Abstract:
A major difficulty for the application of Amartya Sen’s capability approach is that individual capability sets cannot readily be observed. This article proposes a non-parametric framework to construct such sets, on the basis of observed functionings of individuals that are taken to belong to a group sharing the same capability set. Within this framework, the earlier theoretical proposals of Muellbauer to compare different capability sets can be easily implemented. Associated robust empirical estimators are provided and applied to EU-SILC data on household income, material living conditions, housing quality and health; we illustrate our approach with a multilateral comparison of 32 European countries, with a comparison of both a ‘fixed ray’ and a ‘multiple rays’ evaluation metric to compare French and German capability sets, and with a multilateral comparison of socioeconomic sub-groups in France.
JEL-codes: C14 D63 I31 I32 (search for similar items in EconPapers)
Date: 2022
References: Add references at CitEc
Citations: View citations in EconPapers (2)
Downloads: (external link)
http://hdl.handle.net/10.1093/oep/gpaa029 (application/pdf)
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:oup:oxecpp:v:74:y:2022:i:1:p:265-296.
Ordering information: This journal article can be ordered from
https://academic.oup.com/journals
Access Statistics for this article
Oxford Economic Papers is currently edited by James Forder and Francis J. Teal
More articles in Oxford Economic Papers from Oxford University Press Oxford University Press, Great Clarendon Street, Oxford OX2 6DP, UK.
Bibliographic data for series maintained by Oxford University Press ().