1,721,415 research outputs found
EU STATISTICS ON INCOME AND LIVING CONDITIONS (EU-SILC): Choosing the survey structure and sample design
Fuzzy measures of the incidence of relative poverty and deprivation: a multi-dimensional perspective
Abstract In this paper we present a methodology for the study of multi-dimensional aspects of poverty and deprivation. The conventional poor/non-poor dichotomy is replaced by defining poverty as a matter of degree, determined by the place of the individual in the income distribution. The fuzzy poverty measure proposed is in fact also expressible in terms of the generalised Gini measure. The same methodology facilitates the inclusion of other dimensions of deprivation into the analysis: by appropriately weighting indicators of deprivation to reflect their dispersion and correlation, we can construct measures of non-monetary deprivation in its various dimensions. These indicators illuminate the extent to which purely monetary indicators are insufficient in themselves in capturing the prevalence of deprivation. An important contribution of the paper is to identify rules for the aggregation of fuzzy sets appropriate for the study of poverty and deprivation. In particular, we define a ‘composite’ fuzzy set operator which takes into account whether the sets being aggregated are of a ‘similar’ or a ‘dissimilar’ type. These rules allow us to meaningfully combine income and the diverse non-income deprivation indices at the micro-level and construct what we have termed ‘intensive’ and ‘extensive’ indicators of deprivation. We note that mathematically the same approach can be carried over to the study of persistence of poverty and deprivation over time
Fuzzy measures of the incidence of relative poverty and deprivation: a longitudinal and comparative perspective
In this paper, we present a methodology for the study of multi-dimensional and longitudinal aspects of poverty and deprivation, and apply this in a multi-country comparative context. The conventional poor/non-poor dichotomy is replaced by defining poverty as a matter of degree, determined by the place of the individual in the income distribution. The same methodology facilitates the inclusion of other dimensions of deprivation into the analysis: by appropriately weighting indicators of deprivation to reflect their dispersion and correlation, we can construct measures of non-monetary deprivation in its various dimensions. An important contribution of the paper is to identify rules for the intersection and union of fuzzy sets appropriate for the study of poverty and deprivation. These rules allows us to meaningfully combine income and the diverse non-income deprivation indices at the micro-level and construct what we have termed �latent� and �manifest� indicators of deprivation. Mathematically the same approach is carried over for studying the persistence of poverty and deprivation over time. We establish the consistency of the approach when applied to a time sequence of any length. We can thus study longitudinally over time a whole range of indicators of poverty and deprivation, from cross-sectional monetary poverty rates to multi-dimensional 'latent' and 'manifest' indicators of deprivation
A methodology for the study of multi-dimensional and longitudinal aspects of poverty and deprivation
Sampling Errors for Measures of Inequality and Poverty
Catalytic activity of [L2.Zn][NO3]2 (L = spiro-N3P3[O2C12 H 8g][N(CH3)NH2]) towards the hydrolysis of two phosphodiesters, [bis(p-nitrophenyl)phosphate, bNPP] and [2-(hydroxypropyl)-p- nitro-phenyl phosphate, hNPP] has been examined. While the rate of hydrolysis of the former is accelerated over a million-fold, the rate of hydrolysis of the latter also is enhanced considerably. Detailed kinetic evaluation of these reactions has been carried out and all the kinetic parameters including the Michaelis-Menten parameters are reported. The catalyst [L2.Zn] [NO3]2 has also been found to be an effective nuclease. Relaxation of supercoiled plasmid DNA, pBR322, occurs in presence of [L 2.Zn][NO3]2 without the need for any exogenous reagents. © Indian Academy of Sciences
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