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Exploring Poverty and SDG Indicators in Italy: An Identity Spline Approach to Partial Least Squares Regression

Author

Listed:
  • Rosaria Lombardo

    (Department of Economics, University of Campania “Luigi Vanvitelli”, 81043 Capua, Italy)

  • Jean-François Durand

    (Department of Mathematics, University of Montpellier, place Eugène Bataillon, 34090 Montpellier, France)

  • Ida Camminatiello

    (Department of Economics, University of Campania “Luigi Vanvitelli”, 81043 Capua, Italy)

  • Corrado Cuccurullo

    (Department of Economics, University of Campania “Luigi Vanvitelli”, 81043 Capua, Italy)

Abstract

Poverty is a complex global issue, closely linked to economic and social inequalities. It encompasses not only a lack of financial resources but also disparities in access to education, healthcare, employment, and social participation. In alignment with the United Nations’ Sustainable Development Goals—specifically SDGs 3 (Good Health and Well-being), 4 (Quality Education), and 8 (Decent Work and Economic Growth)—this study investigates the relationship between poverty and a set of socioeconomic indicators across Italy’s 20 regions. To explore how poverty levels respond to different predictors, we apply an identity spline transformation to simulate controlled changes in the poverty indicator. The resulting scenarios are analyzed using partial least squares regression, enabling the identification of the most influential variables. The findings offer insights into regional disparities and contribute to evidence-based strategies aimed at reducing poverty and promoting inclusive, sustainable development.

Suggested Citation

  • Rosaria Lombardo & Jean-François Durand & Ida Camminatiello & Corrado Cuccurullo, 2025. "Exploring Poverty and SDG Indicators in Italy: An Identity Spline Approach to Partial Least Squares Regression," Econometrics, MDPI, vol. 13(4), pages 1-16, December.
    • Handle: RePEc:gam:jecnmx:v:13:y:2025:i:4:p:50-:d:1812787
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