Copula-based Measurement of Dependence Between Dimensions of Well-being
By Koen Decancq. 2014
48 citations recorded by the source corpus.
Well-being consists of many dimensions such as income, health and education. A society exhibits greater dependence between its dimensions of well-being when the positions of the individuals in the dierent dimensions are more aligned or corre- lated. Dierences in dependence may lead to very dierent societies, even when the dimension-wise distributions are identical. I propose to use a copula-based frame- work to order societies with respect to their dependence. A class of measures of dependence is derived to which the multidimensional rank correlation coe¢ cient be- longs. I illustrate the usefulness of the approach by showing that Russian dependence between three dimensions of well-being has increased signi…cantly between 1995 and 2003. Unfortunately, the aspect of dependence is missed by all composite well-being measures based on dimension-speci…c summary statistics such as the popular Human Development Index (HDI).
Subfields: General Health Professions, Social Psychology, Sociology and Political Science
View Paper: https://www.semanticscholar.org/paper/3bc3ad408fb423fb956d1d6223ceaf1ae1992c16
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In General Health Professions
In Social Psychology
In Sociology and Political Science
Citations in the corpus
- Multidimensional poverty and inequality (2014, unknown): “Decancq (2014) introduces a copula-based generalization of the rearrangement principles for continuous variables and provides an analysis of their links with stochastic dominance.”
- Multidimensional Poverty Analysis : Looking for a Middle Ground (2012, methodology): “In addition, and in the same way that information on unidimensional inequality can be summarized by an index (such as the Gini coefficient or the mean log deviation), measures of rank correlation allow us to order distributions unambiguously in terms of their degree of interdependency (Decancq 2009)”