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

Author

Listed:
  • 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)

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.

Suggested Citation

  • Carlo Cavicchia & Pasquale Sarnacchiaro & Maurizio Vichi & Giorgia Zaccaria, 2024. "A model-based ultrametric composite indicator for studying waste management in Italian municipalities," Computational Statistics, Springer, vol. 39(1), pages 21-50, February.
    • Handle: RePEc:spr:compst:v:39:y:2024:i:1:d:10.1007_s00180-023-01333-9
    DOI: 10.1007/s00180-023-01333-9
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    References listed on IDEAS

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    4. Carlo Cavicchia & Maurizio Vichi & Giorgia Zaccaria, 2022. "Gaussian mixture model with an extended ultrametric covariance structure," Advances in Data Analysis and Classification, Springer;German Classification Society - Gesellschaft für Klassifikation (GfKl);Japanese Classification Society (JCS);Classification and Data Analysis Group of the Italian Statistical Society (CLADAG);International Federation of Classification Societies (IFCS), vol. 16(2), pages 399-427, June.
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