1,721,052 research outputs found
Measuring levels and trends in absolute poverty in the world: open questions and possible alternatives
No full textMultidimensional and longitudinal poverty: an integrated fuzzy approach
No full textThis Chapter discusses approaches and procedures for constructing fuzzy measures of income poverty and of combining them with similarly constructed measures of non-monetary deprivation using the fuzzy set approach.
In fact, the procedures for combining fuzzy measures in multiple dimensions at a given time are identical, in formal terms, to the procedures for combining fuzzy cross-sectional measures over multiple time periods. We have proposed a general rule for the construction of fuzzy set intersections, that is, for the construction of a longitudinal poverty measure from a sequence of cross-sectional measures under fuzzy conceptualization. This general rule is meant to be applicable to any sequence of “poor” and “non-poor” sets, and it satisfies all the marginal constraints. On the basis of the results obtained, various fuzzy poverty measures over time can be constructed as consistent generalizations of the corresponding conventional (dichotomous) measures.
Numerical results of these procedures applied to measures of multidi-mensional poverty and deprivation, and to combinations of such measures have been presented elsewhere
Measuring levels and trends in absolute poverty in the world: open questions and possible alternatives
No full textEstimating the dynamics of poverty in Europe via a TFR approach: the experience of the second half of the nineties
No full textMultidimensional and longitudinal poverty: an integrated fuzzy approach
No full textWhen poverty is viewed as a matter of degree in contrast to the conventional poor/non-poor dichotomy, that is, as a fuzzy state, two additional aspects are introduced into the analysis. (i)The choice of membership functions i.e. quantitative specification of individuals’ or households’ degrees of poverty and deprivation.(ii)And the choice of rules for the manipulation of the resulting fuzzy sets, rules defining their complements, intersections, union and aggregation. Specifically, for longitudinal analysis of poverty using the fuzzy set approach, we need joint membership functions covering more than one time period, which have to be constructed on the basis of the series of cross-sectional membership functions over those time periods. This Chapter has discussed approaches and procedures for constructing fuzzy measures of income poverty and of combining them with similarly constructed measures of non-monetary deprivation using the fuzzy set approach. In fact, the procedures for combining fuzzy measures in multiple dimensions at a given time are identical, in formal terms, to the procedures for combining fuzzy cross-sectional measures over multiple time periods. We have proposed a general rule for the construction of fuzzy set intersections, that is, for the construction of a longitudinal poverty measure from a sequence of cross-sectional measures under fuzzy conceptualization. This general rule is meant to be applicable to any sequence of “poor” and “non-poor” sets, and it satisfies all the marginal constraints. On the basis of the results obtained, various fuzzy poverty measures over time can be constructed as consistent generalizations of the corresponding conventional (dichotomous) measures. Numerical results of these procedures applied to measures of multidimensional poverty and deprivation, and to combinations of such measures have been presented elsewhere. © 2006, Springer Science+Business Media, LLC
Evolution of the fuzzy-set approach to multi-dimensional poverty measurement
No full textThe spectrum of poverty measurements is wide and varies from purely monetary indicators to more or less sophisticated models based on non-monetary measures. The most traditional approach focuses on measuring monetary poverty, which includes conventional poverty analyses using information on household income or consumption expenditure, and more recently also on wealth. Measures of poverty that exceed the exclusive use of monetary indicators have been developed in different conceptual contexts, referring to different terms such as exclusion, inclusion or social cohesion, deprivation or ‘capability’ poverty. More complex and sophisticated models are also found in the literature, in order to obtain a comprehensive description of the various facets of a complex phenomenon, through a suitable synthesis of the associated elementary indicators. The map on the left displays the severe material deprivation (SMD) rate by geographical region, whereas the map on the right refers to the at-risk-of-poverty (AROP) rate
Disoccupazione e condizioni di vita: dinamiche e relazioni nella realtà degli anni novanta
No full textOn the construction of fuzzy measures for the analysis of poverty and social exclusion
No full textThis paper is a contribution to the analysis of deprivation seen as a
multi-dimensional condition. Multi-dimensionality involves both monetary and
diverse non-monetary aspects – the former as the incidence and intensity of low
income, and the latter as a lack of access to other resources, facilities, social
interactions and even individual attributes determining the life-style. A most useful
tool for such analysis is to view deprivation as a matter of degree, giving a
quantitative expression to its intensity for individuals in different dimensions and at
different times. Such ‘fuzzy’ conceptualisation has been increasingly utilised in
poverty and deprivation research. This paper aims to further develop and refine this
strand of research, so as to integrate it in the form of a more ‘integrated fuzzy and
relative’ (IFR) approach to the analysis of poverty and deprivation. The concern of
the paper is primarily methodological rather than detailed numerical analysis from
particular applications. We re-examine the two additional aspects introduced by the
use of fuzzy (as distinct from the conventional poor/non-poor dichotomous)
measures, namely: the choice of membership functions and the choice of rules for
the manipulation of the resulting fuzzy sets, rules defining their complement,
intersection, union and averaging. The relationship of the proposed fuzzy monetary
measure with the Lorenz curve and the Gini coefficient
Measuring Educational Poverty in Italy: A Multi-Dimensional and Fuzzy Approach
No full textThis chapter presents the data and the indicators used to define the Educational Poverty (EP) multi-dimensional measure. From the policymaking perspective, the results of our analysis demonstrate the actual consistency and dimensions of EP at a useful local level, which in turn, suggest, for example, a revision of local governments’ normal policies employed to reverse EP. From a methodological point of view, taking a fuzzy perspective on EP attains particular significance in our multi-dimensional approach. Indeed, it overcomes the issue of transforming each single indicator used in the analysis into a simple dichotomous variable to indicate the percentage of people who are deprived with respect to each specific aspect, as implied by the approach taken by Mazziotta-Pareto. Although it is good practice to do so, this procedure requires information on the primary sampling units, rotational groups and strata, which are not available in the user database of the aspects of everyday life (AVQ) survey
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