rivista italiana di economia demografia e statistica - Sieds

Rivista Italiana di Economia Demografia e Statistica 169
( )
Pˆ X = t W = m, Z
i*
. For instance, the probability to belong to class 6 for a retired
person rises from 0.02 for cluster 2 to 0.60 for cluster 3, against a probability equal
to 0.11 for an average region. For clusters 1, 2 and 4, this hypothetical individual
has high probabilities to belong to class 3 characterized by low levels of income
but by a positive subjective evaluation of the overall conditions in all domains of
the life. Again, for a young unemployed person, the highest probability to belong to
the latent class of excluded people is given membership to cluster 3 (0.57). On the
other hand, for these regions, such an individual has high probability to be
classified in class 5 (institutional exclusion, 0.38 versus 0.03 for an average region).
Moreover, except for cluster 4, this hypothetical individual has a low probability to
belong to class 1 (relational exclusion).
5. Concluding remarks
In this contribution, starting from a working definition of social exclusion,
which encompasses some founding elements of social exclusion notion namely
multidimensionality, subjectivity and relativity, we implemented a multilevel
Latent Class model, which simultaneously derives regional and individual profiles.
Our outcomes have proved, firstly, that it exists different typologies of social
exclusion, according to the three identified dimensions. The role of economic
conditions in determining social exclusion situations seems to be reduced whether
one considers in the analysis also the relational dimension. Secondly, the multilevel
extension allows accounting for the social, cultural and economic context, thus
underlying different structures of the same latent concept social exclusion for
different groups of regions. It being understood the multidimensionality of the
concept, for some European areas the social exclusion condition is mainly due to
the relational sphere, for others to the economic dimension, and for other ones to
the detachment with respects the institutions and the public context.
These findings imply that social networks, as well as social and protection
system, might not to have the same impact both in influencing the perception of
social exclusion and in reducing the risk of social exclusion in all European regions.
In this sense, we deem that the contextualization and the knowledge of the cultural,
economic, social and institutional environment is fundamental to understand the
relations among the risk factors that may trigger social exclusion situations, and
that these differences should be accounted for during the formulation and
implementation of the measures and policy strategies at European level.