Abstract
The aim of this paper is to propose multidimensional measures of deprivation and wellbeing in contemporary Switzerland, in order to overcome the limitations of standard approaches. More precisely, we have developed self organising maps (SOM) using data drawn from the 2009 Swiss Household Panel wave, in order to identify highly homogeneous clusters of individuals characterized by distinct profiles across 44 indicators of deprivation and well-being. SOM is a vector quantiser that performs a topology-preserving mapping of the k-dimensional input data to a two-dimensional, rectangular grid of output units, preserving as much as possible the information contained in the original input data. “Topology-preserving” means that, when an SOM is properly developed, units that are close in the output space are also close in the input space. Our results suggest that the SOM approach could improve our understanding of complex and multidimensional phenomena, like those of well-being, deprivation, vulnerability, that show only a partial overlapping with standard income poverty measures.
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Notes
For further details of the Proportional Deprivation Index see Halleröd (1995).
More specifically, the percentage of deprived individuals in the 1999 wave amounted to 4.38 %.
As has been recently proven in other papers (Lucchini et al. 2007; Pisati et al. 2010; Whelan et al. 2010), in comparison with latent class analysis, the SOM approach involves minimal assumptions and offers considerable additional discriminatory power for analysing the shape and form of social exclusion.
The term ‘unsupervised clustering procedure’ means that the groups of interest are not known a priori to the researcher and must be discovered by using an appropriate classification technique.
All the analyses reported in this paper, including SOM development and visualization, have been carried out using routines written in R programming language (http://cran.r-project.org\).
Indicators that appear as scales have been normalised.
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This study has been financed by the Swiss National Science Foundation (Grants 00017_138033/1).
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Lucchini, M., Assi, J. Mapping Patterns of Multiple Deprivation and Well-Being using Self-Organizing Maps: An Application to Swiss Household Panel Data. Soc Indic Res 112, 129–149 (2013). https://doi.org/10.1007/s11205-012-0043-7
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DOI: https://doi.org/10.1007/s11205-012-0043-7