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An R tool for computing and evaluating Fuzzy poverty indices: The package FuzzyPovertyR.

F Crescenzi1, L Mori2, G Betti3

  • 1Department of Economics, Statistics and Business, Universitas Mercatorum, Rome, Italy.

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|December 4, 2025
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Summary
This summary is machine-generated.

This study introduces FuzzyPovertyR, an R package for estimating fuzzy poverty indices. It provides tools for calculating uni- and multi-dimensional poverty measures with various membership functions and variance estimation methods.

Keywords:
03E7262F4091B82BootstrapEU-SILCJack-Knifemulti-dimensional povertyunidimensional poverty

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Area of Science:

  • Economics
  • Statistics
  • Computational Social Science

Background:

  • Fuzzy set theory is increasingly used for poverty estimation.
  • Various methods for defining membership functions and calculating fuzzy poverty indices exist.
  • A need for a unified R package for these estimations is apparent.

Purpose of the Study:

  • Introduce the new R package FuzzyPovertyR for estimating fuzzy poverty indices.
  • Demonstrate the package's utility with uni- and multi-dimensional poverty indices in Italy.
  • Provide tools for selecting membership functions and estimating index variance.

Main Methods:

  • Development of the FuzzyPovertyR R package.
  • Estimation of three fuzzy poverty indices (one multi-dimensional, two uni-dimensional) at NUTS 2 level in Italy.
  • Implementation of Jack-Knife and bootstrap methods for variance estimation.

Main Results:

  • The FuzzyPovertyR package successfully estimates fuzzy poverty indices.
  • The package allows for flexible selection of membership functions.
  • Variance estimation is supported through Jack-Knife and bootstrap procedures.

Conclusions:

  • FuzzyPovertyR offers a comprehensive tool for fuzzy poverty index estimation.
  • The package facilitates the application of fuzzy set theory in poverty analysis.
  • It supports robust variance estimation for fuzzy poverty measures.