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A population of households is considered and each household is distinguished by two attributes: pre-tax income and family size. To compare incomes in this heterogeneous environment an affine transformation is proposed as equivalent income function, from which income dependent equivalence scales...
Persistent link: https://www.econbiz.de/10005007222
The analysis of growth patterns is a branch of research of great practical importance: the identification of factors that influence changes in the income distribution making them pro-poor or pro-rich can be a crucial element in the process of designing a social policy. It seems natural that...
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<Para ID="Par1">The paper deals with poverty orderings when multidimensional attributes exhibit some degree of comparability. The paper focuses on an important special case of this, that is, comparisons of poverty that make use of incomes at different time periods. The ordering criteria extend the power of...</para>
Persistent link: https://www.econbiz.de/10011241366
The paper deals with poverty orderings when the value of multidimensional attributes can be compared on a same scale, such as with income of different types or from different members of the same household. The dominance criteria extend the power of earlier multidimensional dominance tests (see...
Persistent link: https://www.econbiz.de/10010821488
Most welfare studies are based on the assumption that wellbeing is monotonically related to the variables used for the analysis. While this assumption can be regarded as reasonable for many dimensions of wellbeing like income, education, or empowerment, there are some cases where it is...
Persistent link: https://www.econbiz.de/10010899416
Most studies have reported non negligible improvements for China in terms of poverty during the last three decades. However, this result is potentially hampered by two limitations. First, it may be contingent to the specific choices made regarding the poverty line and the poverty indices used...
Persistent link: https://www.econbiz.de/10010875326
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