Targeting Policies for Multidimensional Poverty and Social Fragility Relief Among Migrants in Italy, Using F-FOD Analysis

In this paper, we apply the novel Fuzzy First-Order Dominance (F-FOD) methodology to rank migrant subpopulations in Lombardy (Italy), in terms of multidimensional poverty and social fragility, for the year 2014, with the purpose to possibly provide useful support to policy-makers, in targeting relief interventions from poverty and discomfort. The F-FOD methodology allows for the direct comparison of different distributions of poverty and fragility, assessed by means of suitable ordinal multi-indicator systems, so extending to this more complex setting, the usual univariate first-order dominance criterion. It also provides complimentary “incomparability” scores, to assess to what extent the final rankings are reliable or instead forcing. It turns out that the levels of poverty and fragility of migrant subpopulations are quite different and, in particular, that the time since migrations has a key impact, on the identification of most critical cases, which typically involve recently migrated people. Evidence also emerges that the temporal poverty/fragility trajectories of migrants, distinguished by country of origin, follow different paths, suggesting how policy interventions must be properly, and differently, tuned to be effective

First Order Dominance Techniques and Multidimensional Poverty Indices:An Empirical Comparison of Different Approaches

In this empirically driven paper we compare the performance of two techniques in the literature of poverty measurement with ordinal data: multidimensional poverty indices and first order dominance techniques (FOD). Combining multiple scenario simulated data with observed data from 48 Demographic and Health Surveys around the developing world, our empirical findings suggest that the FOD approach can be implemented as a useful robustness check for ordinal poverty indices like the multidimensional poverty index (MPI; the United Nations Development Program's flagship poverty indicator) to distinguish between those country comparisons that are sensitive to alternative specifications of basic measurement assumptions and those which are not. To the extent that the FOD approach is able to uncover the socio-economic gradient that exists between countries, it can be proposed as a viable complement to the MPI with the advantage of not having to rely on many of the normatively binding assumptions that underpin the construction of the index

A reduced posetic approach to the measurement of multidimensional ordinal deprivation

In this paper, we discuss the existence of particular systems of generators for posets associated to multidimensional systems of ordinal indicators and derive a reduced posetic procedure for the measurement of multidimensional ordinal deprivation. The proposal is motivated by the need to lessen the computational complexity of the original posetic procedure described in Fattore (Soc Indic Res 128(2):835–858, 2015), so as to make it applicable to larger multi-indicator systems, particularly to those comprising many variables scored on ‘‘short’’ scales, as typical in deprivation studies. The reduced procedure computes identification and severity functions based only on so-called lexicographic linear extensions. These are a particular generating system for the basic achievement poset, naturally associated to rankings of deprivation attributes. After motivating this choice, both from an interpretative and a computational point of view, the paper provides some simulated examples, comparing the reduced and the non-reduced procedure

F-FOD: Fuzzy First Order Dominance Analysis and Populations Ranking Over Ordinal Multi-Indicator Systems

In this paper, we develop a new statistical procedure for the comparison of frequency distributions on systems of ordinal indicators, based on a multidimensional fuzzy extension of the first order dominance (FOD) criterion. The procedure, named fuzzy-first order dominance (F-FOD), employs concepts and tools from partially ordered set theory and from fuzzy relational calculus and is designed to overcome the main limitations of previously developed algorithms for FOD analysis. In particular, F-FOD produces full pairwise comparison matrices, allows for partial orderings and rankings of the statistical units to be derived from the input data, is computationally sufficiently light to be applied in most cases of practical interest and is freely available in the R package PARSEC. To illustrate its effectiveness, we also show F-FOD in action on two real datasets concerning health in Denmark and child well-being in the Democratic Republic of Congo

Using mutual ranking probabilities for dimensionality reduction and ranking extraction in multidimensional systems of ordinal variables

In this paper, we address the extraction of rankings from multi-indicator systems, as a problem of approximation between the so-called “mutual ranking probability” matrices, associated to the partial order relations derived from the data. After providing a theoretical treatment of the topic, we propose a practical algorithm for ranking extraction and show it in action on a real example, pertaining to regional competitivenes

Visualizing Partially Ordered Sets for Socioeconomic Analysis

In this paper, we develop a visualization process for partial orders derived from considering many numerical indicators on a statistical population. The issue is relevant, particularly in the field of socio-economic evaluation, where explicitly taking into account incomparabilities among individuals proves much more informative than adhering to classical aggregative and compensative approaches, which collapse complexity into unidimensional rankings. We propose a process of visual analysis based on a combination of tools and concepts from partial order theory, multivariate statistics and visual design. We develop the process through a real example, based on data pertaining to regional competitiveness in Europe

Measuring Structural Dissimilarity Between Finite Partial Orders

In this paper, we address the problem of measuring structural dissimilarity between two partial orders with n elements. We propose a structural dissimilarity measure, based on the distance between isomorphism classes of partial orders, and propose an interpretation in terms of graph theory. We give examples of structural dissimilarity computations, using a simulated annealing algorithm for numerical optimization

Structural and non-structural temporal evolution of socio-economic real networks

In this paper, we show that a comprehensive analysis of temporal network evolution requires to consider measures of non-structural changes, in addition to classical topological indicators. We employ a recently proposed measure of non-structural dynamics, together with other structural indicators, to analyze the time evolution of three subnetworks, extracted from the Italian corporate board network. Consistently with recent literature, we show that, to different extent, both structural and non-structural changes are present and must be accounted for, in order to get a satisfactory description of their temporal evolution

Method of moments for Zenga's distribution

The aim of this paper is to obtain the analytical solution to the method of moments for Zenga's model (Zenga, M. M., 2010). First, the central moments of Polisicchio's distribution are used to derive the corresponding central moments for Zenga's model. Secondly, the method of moments is applied to such central moments, and then the analytical solution of the related system is obtained. These analytical results are then compared with the numerical ones in Zenga et al. (2010a)