Arbeitspapier

A counting approach for measuring multidimensional deprivation

This paper is concerned with the problem of ranking and quantifying the extent of deprivation exhibited by multidimensional distributions, where the multiple attributes in which an individual can be deprived are represented by dichotomized variables. To this end we first aggregate deprivation for each individual into a "deprivation count", representing the number of dimensions for which the individual suffers from deprivation. Next, by drawing on the rank-dependent social evaluation framework that originates from Sen (1974) and Yaari (1988) the individual deprivation counts are aggregated into summary measures of deprivation, which prove to admit decomposition into the mean and the dispersion of the distribution of multiple deprivations. Moreover, second-degree upward and downward count distribution dominance are shown to be useful criteria for dividing the measures of deprivation into two separate subfamilies. To provide a normative justification of the dominance criteria we introduce alternative principles of association (correlation) rearrangements, where either the marginal deprivation distributions or the mean deprivation are assumed to be kept fixed.

Language
Englisch

Bibliographic citation
Series: Discussion Papers ; No. 700

Classification
Wirtschaft
Personal Income, Wealth, and Their Distributions
Equity, Justice, Inequality, and Other Normative Criteria and Measurement
Measurement and Analysis of Poverty
Subject
Multidimensional deprivation
counting approach
partial orderings
rank-dependent measures of deprivation
principles of association rearrangements

Event
Geistige Schöpfung
(who)
Aaberge, Rolf
Peluso, Eugenio
Event
Veröffentlichung
(who)
Statistics Norway, Research Department
(where)
Oslo
(when)
2012

Handle
Last update
10.03.2025, 11:42 AM CET

Data provider

This object is provided by:
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. If you have any questions about the object, please contact the data provider.

Object type

  • Arbeitspapier

Associated

  • Aaberge, Rolf
  • Peluso, Eugenio
  • Statistics Norway, Research Department

Time of origin

  • 2012

Other Objects (12)