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

Year: 2025

Type: article

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.

Source: Econometrics

DOI: 10.3390/econometrics13040050

Authors: Rosaria Lombardo, Jean-François Durand, Ida Camminatiello, Corrado Cuccurullo

Institutions: University of Campania "Luigi Vanvitelli", Université de Montpellier

Language: English

Topic: Income, Poverty, and Inequality

Subfield: Sociology and Political Science

Field: Social Sciences

Domain: Social Sciences

SDGs: No poverty, Reduced inequalities

Open Access status: gold

Estimated APC paid: $1,689