A Quantile Approach for Measuring Multidimensional Educational Poverty in Italy

Caterina Giusti () and Francesco Schirripa Spagnolo ()
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Caterina Giusti: Università di Pisa
Francesco Schirripa Spagnolo: Università di Pisa

Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, 2025, vol. 179, issue 1, No 2, 29-45

Abstract: Abstract In recent years, the need to address educational poverty (EP) has become a pressing concern on the political agenda of several countries, and this issue has been recognized as a novel social challenge that demands immediate attention. To measure the level of EP in Italy, based on an original proposal by the Italian National Statistical Institute, a composite index known as the Educational Poverty Index (EPI) has been defined and used by several authors. In this paper, we focus on the same set of dimensions included in the multidimensional EPI and the relationships among them; we also employ a hierarchical composite model to measure EP in Italian regions while simultaneously taking gender into account as an additional factor. However, employing this method limits the estimation solely to average effects, resulting in an insufficient portrayal. Therefore, we also use quantile composite-based path modelling, which offers a comprehensive view of the relationships among the variables. Our results suggest that the dimensions of the EPI play distinct roles at different points in the index distribution. Moreover, the results tend to exhibit different patterns at the lower and higher quantiles of the index distribution according to gender.

Keywords: Hierarchical composite model; Quantile composite-based path modelling; Composite indicators; Educational inequalities; Gender inequalities (search for similar items in EconPapers)
Date: 2025
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DOI: 10.1007/s11205-025-03607-9

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