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Interval-Based Composite Indicators with a Triplex Representation: A Measure of the Potential Demand for the "Ristori" Decree in Italy

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  • Drago, Carlo

Abstract

In this work, we propose a new approach to constructing interval-based composite indicators based on the triplex representation. So, we measure the principal value of the indicator and simultaneously the value's uncertainty due to the different assumptions as different weightings associated how the indicator and their ranks can vary considering different assumptions or weights. The approach is useful not only on the construction of the composite indicators but also for a reliable interpretation of the results. The application shows the usefulness of the approach in detecting the regions higher the potential demand for economic support due to the Covid-19 emergency. In questo lavoro proponiamo un nuovo approccio alla costruzione di indicatori compositi basati su intervalli, basati sulla rappresentazione triplex. In questo caso siamo in grado di misurare non solo il valore principale dell'indicatore e l'incertezza del valore dovuta alla diversa assunzione come differenti ponderazioni associate ma anche come l'indicatore e il loro rango possono variare considerando differenti assunzioni o pesi. Quindi l'approccio è utile non solo sulla costruzione degli indicatori compositi, ma anche su un'interpretazione affidabile dei risultati.

Suggested Citation

  • 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.
    • Handle: RePEc:pra:mprapa:106904
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    References listed on IDEAS

    as
    1. 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.
    2. Billard L. & Diday E., 2003. "From the Statistics of Data to the Statistics of Knowledge: Symbolic Data Analysis," Journal of the American Statistical Association, American Statistical Association, vol. 98, pages 470-487, January.
    3. Carlo Drago, 2017. "Interval Based Composite Indicators," Working Papers 2017.42, Fondazione Eni Enrico Mattei.
    4. Salvatore Greco & Alessio Ishizaka & Menelaos Tasiou & Gianpiero Torrisi, 2019. "On the Methodological Framework of Composite Indices: A Review of the Issues of Weighting, Aggregation, and Robustness," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 141(1), pages 61-94, January.
    5. M. Saisana & A. Saltelli & S. Tarantola, 2005. "Uncertainty and sensitivity analysis techniques as tools for the quality assessment of composite indicators," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 168(2), pages 307-323, March.
    6. Gatto, Andrea & Drago, Carlo, 2020. "Measuring and modeling energy resilience," Ecological Economics, Elsevier, vol. 172(C).
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    Cited by:

    1. Céline Diebold, 2022. "How Meaningful is the Elite Quality Index Ranking?," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 163(1), pages 137-170, August.

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    More about this item

    Keywords

    Interval-based Composite Indicators; Composite Indicators; Symbolic Data Analysis; Triplex Representation;
    All these keywords.

    JEL classification:

    • C43 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Index Numbers and Aggregation
    • C81 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Methodology for Collecting, Estimating, and Organizing Microeconomic Data; Data Access
    • C82 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Methodology for Collecting, Estimating, and Organizing Macroeconomic Data; Data Access
    • C88 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Other Computer Software

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