- Data, Statistics and AI for Well-Being of People and Organisations
- A cura di Luigi Fabbris, Alberto Franci, Pietro Renzi
Statistical and econometric tools for measuring municipal well-being: Moving beyond GDP in the digital transformation era
- Chiara Colamartino
- Vincenzo Calabrese
- Pierluigi Toma
- © 2026 Author(s) |
- CC BY 4.0
- DOI: 10.36253/979-12-215-1062-1.27
In an age of systemic crises and accelerated digitalisation, the limitations of Gross Domestic Product (GDP) as a measure of well-being have become increasingly evident. GDP fails to reflect crucial dimensions such as access to services, environmental sustainability, social inclusion, and the digital divide—factors that significantly shape territorial development and people’s quality of life. This study proposes an alternative, multidimensional framework to evaluate local well-being more comprehensively and equitably. Using harmonised data from all Italian municipalities (2016–2020), the research develops a composite well-being indicator that integrates income distribution, education, healthcare access, environmental quality, and social cohesion. This indicator is combined with Data Envelopment Analysis (DEA) and normalised per capita income to assess how efficiently public administrations convert available resources into well-being outcomes across diverse territorial contexts. The results reveal substantial spatial disparities and institutional asymmetries, and smaller municipalities are generally more efficient. At the same time, larger urban areas display greater heterogeneity, often reflecting both digital potential and persistent inequality. The statistical analysis highlights the importance of digital infrastructure and administrative capacity in influencing performance, particularly in sectors that are increasingly dependent on digital tools and access. From a policy perspective, the study contributes a practical, data-driven methodology that supports evidence-based governance aligned with several Sustainable Development Goals (SDGs), including those related to poverty reduction, health, inequality, and sustainable communities. It demonstrates how official statistics and administrative data, when organised into multidimensional indicators, can provide actionable insights for local governments and decision-makers. Ultimately, this research supports the shift beyond GDP-centric models by offering a statistically robust and scalable tool to monitor well-being and guide place-based policy interventions in the context of digital transformation and emerging societal challenges.
- Keywords:
- Beyond GDP,
- Multidimensional Composite Indicator,
- Territorial Well-being,
- Data Envelopment Analysis (DEA),
- Digital Divide,
- Sustainable Development Goals (SDGs),
LUM Giuseppe Degennaro University, Italy - ORCID: 0000-0002-1651-4642
LUM Giuseppe Degennaro University, Italy
University of Salerno, Italy - ORCID: 0000-0003-0462-4622
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Informazioni sul capitolo
Titolo del capitolo
Statistical and econometric tools for measuring municipal well-being: Moving beyond GDP in the digital transformation era
Autori
Chiara Colamartino, Vincenzo Calabrese, Pierluigi Toma
Lingua
Inglese
DOI
10.36253/979-12-215-1062-1.27
Opera sottoposta a peer review
Anno di pubblicazione
2026
Copyright
© 2026 Author(s)
Licenza d'uso
Licenza dei metadati
Informazioni bibliografiche
Titolo del libro
Data, Statistics and AI for Well-Being of People and Organisations
Curatori
Luigi Fabbris, Alberto Franci, Pietro Renzi
Opera sottoposta a peer review
Numero di pagine
420
Anno di pubblicazione
2026
Copyright
© 2026 Author(s)
Licenza d'uso
Licenza dei metadati
Editore
Firenze University Press
DOI
10.36253/979-12-215-1062-1
ISBN Print
979-12-215-1061-4
eISBN (pdf)
979-12-215-1062-1
eISBN (xml)
979-12-215-1063-8
Collana
Applied Statistics Series