A model-based ultrametric composite indicator for studying waste management in Italian municipalities

Carlo Cavicchia, Pasquale Sarnacchiaro, Maurizio Vichi, Giorgia Zaccaria*

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review


A Composite Indicator (CI) is a useful tool to synthesize information on a multidimensional phenomenon and make policy decisions. Multidimensional phenomena are often modeled by hierarchical latent structures that reconstruct relationships between variables. In this paper, we propose an exploratory, simultaneous model for building a hierarchical CI system to synthesize a multidimensional phenomenon and analyze its several facets. The proposal, called the Ultrametric Composite Indicator (UCI) model, reconstructs the hierarchical relationships among manifest variables detected by the correlation matrix via an extended ultrametric correlation matrix. The latter has the feature of being one-to-one associated with a hierarchy of latent concepts. Furthermore, the proposal introduces a test to unravel relevant dimensions in the hierarchy and retain statistically significant higher-level CIs. A simulation study is illustrated to compare the proposal with other existing methodologies. Finally, the UCI model is applied to study Italian municipalities’ behavior toward waste management and to provide a tool to guide their councils in policy decisions.
Original languageEnglish
Pages (from-to)21-50
Number of pages30
JournalComputational Statistics
Issue number1
Publication statusPublished - Feb 2024

Bibliographical note

Funding Information:
Open access funding provided by Università degli Studi di Milano - Bicocca within the CRUI-CARE Agreement. The authors did not received support from any organization for the submitted work.

Publisher Copyright:
© 2023, The Author(s).

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