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Spatial Distribution of Multidimensional Educational Poverty in Italy using Small Area Estimation

Author

Listed:
  • Monica Pratesi

    (University of Pisa
    Tuscan Universities Research Centre)

  • Luciana Quattrociocchi

    (Italian National Institute of Statistics)

  • Gaia Bertarelli

    (University of Pisa
    Tuscan Universities Research Centre)

  • Alessandro Gemignani

    (Tuscan Universities Research Centre)

  • Caterina Giusti

    (University of Pisa
    Tuscan Universities Research Centre)

Abstract

Inclusive and equitable education and the promotion of lifelong learning opportunities for all are important targets in the 2030 Agenda for Sustainable Development. Deprivation in education, read also as deprivation of opportunities and rights i.e. health, culture, participation, social relations, referred to as educational poverty (EP), has attracted interest of researchers, which highlighted its complexities and consequences, such as being excluded from acquiring the skills needed to live in a world characterized by knowledge-based economy, rapidity and innovation. In the last few years, the Italian National Statistical Institute started to measure it by a multidimensional index, the composite educational poverty index (EPI). The index is based on survey direct estimates, which are reliable only at regional (NUTS 2) level, while to monitor and contrast the phenomenon it is important to obtain information at a finer geographical level. In this paper small area estimation models are applied to the unidimensional indicators which compose the multidimensional EPI. The aim is to enhance the knowledge of the spatial distribution of EP at local level in Italy, separating urban and non urban areas and focusing on peripheries in Italian Regions, using DEGURBA classification in order to help the policy maker to address resources towards the areas where the phenomenon is strongly present.

Suggested Citation

  • Monica Pratesi & Luciana Quattrociocchi & Gaia Bertarelli & Alessandro Gemignani & Caterina Giusti, 2021. "Spatial Distribution of Multidimensional Educational Poverty in Italy using Small Area Estimation," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 156(2), pages 563-586, August.
    • Handle: RePEc:spr:soinre:v:156:y:2021:i:2:d:10.1007_s11205-020-02328-5
    DOI: 10.1007/s11205-020-02328-5
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    References listed on IDEAS

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    Cited by:

    1. Angelo Moretti, 2023. "Regional Public Opinions on LGBTI People Equal Opportunities in Employment: Evidence from the Eurobarometer Programme using Small Area Estimation," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 166(2), pages 413-438, April.
    2. Arianna Carciotto, 2023. "Experimental Statistics: a New Common Language for Uncommon Data," RIEDS - Rivista Italiana di Economia, Demografia e Statistica - The Italian Journal of Economic, Demographic and Statistical Studies, SIEDS Societa' Italiana di Economia Demografia e Statistica, vol. 77(4), pages 256-269, October-D.
    3. Niall Farrell, 2024. "Small Area Poverty Estimation by Conditional Monte Carlo," Papers WP773, Economic and Social Research Institute (ESRI).
    4. María-del-Carmen Sánchez-Antón & Rosa Badillo-Amador & María-del-Carmen Marco-Gil & Juan-Vicente LLinares-Ciscar & Susana Álvarez-Díez & Juan-Francisco Sánchez-García, 2022. "Analysis of the Educational Poverty in Spain by Subjects, Regions and Gender," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 162(2), pages 829-861, July.

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