In 2023, ISTAT formed a Scientific Commission in collaboration with other institutions to study and map educational poverty. The Commission embraced a multidimensional approach based on two key aspects: poverty in educational outcomes and poverty in educational drivers. These two dimensions must be addressed simultaneously to assess and understand educational poverty effectively. The Commission selected a wide range of multisource indicators to evaluate the framework quantitatively. According to data availability reasons, we select a subgroup of 23 multisource indicators and compute their values for three areas identified within the 14 Italian metropolitan areas. To this end, we applied small area estimation techniques only to the indicator of relative poverty, which is based on sample survey data that do not provide reliable estimates at the required territorial level. Lastly, we apply the AMPI methodology to compute two composite indices, one for the outcomes dimension and one for the drivers dimension. The two indices allow us to compare the level of deprivation between metropolitan areas and their distance from the national average.

Misurare la povertà educativa nelle città metropolitane

Monica Pratesi
Primo
;
Caterina Giusti
Secondo
;
Nicola Salvati
Penultimo
;
Matteo Mazziotta
2025-01-01

Abstract

In 2023, ISTAT formed a Scientific Commission in collaboration with other institutions to study and map educational poverty. The Commission embraced a multidimensional approach based on two key aspects: poverty in educational outcomes and poverty in educational drivers. These two dimensions must be addressed simultaneously to assess and understand educational poverty effectively. The Commission selected a wide range of multisource indicators to evaluate the framework quantitatively. According to data availability reasons, we select a subgroup of 23 multisource indicators and compute their values for three areas identified within the 14 Italian metropolitan areas. To this end, we applied small area estimation techniques only to the indicator of relative poverty, which is based on sample survey data that do not provide reliable estimates at the required territorial level. Lastly, we apply the AMPI methodology to compute two composite indices, one for the outcomes dimension and one for the drivers dimension. The two indices allow us to compare the level of deprivation between metropolitan areas and their distance from the national average.
2025
Pratesi, Monica; Giusti, Caterina; Salvati, Nicola; Savioli, Miria; Segre, Elisabetta; Mazziotta, Matteo
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11568/1340572
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