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The Analysis and the Measurement of Poverty: An Interval-Based Composite Indicator Approach

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  • Carlo Drago

    (University “Niccolò Cusano” Rome, Via Don Carlo Gnocchi 3, 00166 Rome, Italy)

Abstract

The study of poverty and its quantification is a critical yet unresolved problem in social science. This work seeks to use a new composite indicator to assess poverty as a multidimensional concept. However, subjective decisions, such as various weighting systems on the indicator’s creation, may affect its perception. In order to solve this issue, we propose to use random different composite indicators based on simulated weightings and specifications to get a comprehensive interval-based composite indicator. Our method generates robust and trustworthy measurements based on a meaningful conceptual model of poverty. Furthermore, we use some interval parameters such as the upper bound, center, and lower bound to compare the different intervals related to the different statistical units and rankings to aid in analyzing extreme situations and policy scenarios. In Sicily, Calabria, Campania, and Puglia, we identify urgent circumstances. The findings reveal a consistent indicator measurement and the shadow sector’s influence on the final measurements.

Suggested Citation

  • Carlo Drago, 2021. "The Analysis and the Measurement of Poverty: An Interval-Based Composite Indicator Approach," Economies, MDPI, vol. 9(4), pages 1-17, October.
    • Handle: RePEc:gam:jecomi:v:9:y:2021:i:4:p:145-:d:651526
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    1. Matheus Pereira Libório & Alexandre Magno Alves Diniz & Hamidreza Rabiei-Dastjerd & Oseias da Silva Martinuci & Carlos Augusto Paiva da Silva Martins & Petr Iakovlevitch Ekel, 2023. "A Decision Framework for Identifying Methods to Construct Stable Composite Indicators That Capture the Concept of Multidimensional Social Phenomena: The Case of Social Exclusion," Sustainability, MDPI, vol. 15(7), pages 1-17, April.
    2. Xiaoning Li & Lingling Li, 2021. "Evaluation of China’s Targeted Poverty Alleviation Policies: A Decomposition Analysis Based on the Poverty Reduction Effects," Sustainability, MDPI, vol. 13(21), pages 1-17, October.
    3. Yizhong Huan & Lingqing Wang & Mark Burgman & Haitao Li & Yurong Yu & Jianpeng Zhang & Tao Liang, 2022. "A multi‐perspective composite assessment framework for prioritizing targets of sustainable development goals," Sustainable Development, John Wiley & Sons, Ltd., vol. 30(5), pages 833-847, October.
    4. Carlo Drago & Loris Di Nallo & Maria Lucetta Russotto, 2023. "Social Sustainability in European Banks: A Machine Learning Approach using Interval- Based Composite Indicators," Working Papers 2023.13, Fondazione Eni Enrico Mattei.
    5. Carlo Drago & Andrea Gatto, 2022. "An interval‐valued composite indicator for energy efficiency and green entrepreneurship," Business Strategy and the Environment, Wiley Blackwell, vol. 31(5), pages 2107-2126, July.
    6. Drago, Carlo & Gatto, Andrea, 2022. "Policy, regulation effectiveness, and sustainability in the energy sector: A worldwide interval-based composite indicator," Energy Policy, Elsevier, vol. 167(C).
    7. Drago, Carlo, 2021. "Interval-Based Composite Indicators with a Triplex Representation: A Measure of the Potential Demand for the "Ristori" Decree in Italy," MPRA Paper 106904, University Library of Munich, Germany.
    8. Marek Walesiak & Grażyna Dehnel, 2023. "A Measurement of Social Cohesion in Poland’s NUTS2 Regions in the Period 2010–2019 by Applying Dynamic Relative Taxonomy to Interval-Valued Data," Sustainability, MDPI, vol. 15(4), pages 1-21, February.
    9. Yue Pan & Ying Wang & Yingxue Wang & Yanling Xie & Junmei Dong & Min Liu, 2023. "Spatiotemporal Dynamics of the Suitability for Ecological Livability of Green Spaces in the Central Yunnan Urban Agglomeration," Sustainability, MDPI, vol. 15(22), pages 1-18, November.

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    More about this item

    Keywords

    poverty; composite indicators; interval data; interval-based composite indicators;
    All these keywords.

    JEL classification:

    • C02 - Mathematical and Quantitative Methods - - General - - - Mathematical Economics
    • C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
    • C43 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Index Numbers and Aggregation
    • I3 - Health, Education, and Welfare - - Welfare, Well-Being, and Poverty
    • I32 - Health, Education, and Welfare - - Welfare, Well-Being, and Poverty - - - Measurement and Analysis of Poverty

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