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

Carlo Cavicchia (), Pasquale Sarnacchiaro (), Maurizio Vichi () and Giorgia Zaccaria ()
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Carlo Cavicchia: Erasmus University Rotterdam
Pasquale Sarnacchiaro: University of Naples Federico II
Maurizio Vichi: University of Rome La Sapienza
Giorgia Zaccaria: University of Milano-Bicocca

Computational Statistics, 2024, vol. 39, issue 1, No 3, 50 pages

Abstract: Abstract 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.

Keywords: Composite indicators; Hierarchical models; Ultrametricity; Waste management; External information (search for similar items in EconPapers)
Date: 2024
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DOI: 10.1007/s00180-023-01333-9

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