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Non-compensability in Composite Indicators: A Robust Directional Frontier Method

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  • Francesco Vidoli
  • Elisa Fusco
  • Claudio Mazziotta

Abstract

This paper follows the research mainstream aimed to link the efficiency frontier approaches and the composite indicators (CI) methods. More in detail, the main drawbacks of the CI methods based on Benefit of the Doubt (BoD) approach are the sensitivity to the outliers, the perfect compensability and the lack of consideration about the marginal rate of substitution between simple indicators. Following Simar and Vanhems (J Econ 166(2):342–354, 2012 ) results, we propose a weighting method that bypassing all previous shortcomings suggests a comprehensive approach to construct robust and non-compensatory composite indicators. This approach is based on the integration of BoD by a directional distance function. In order to better highlight the advantages and limitations of our approach we present two applications: in the first one we test our approach on simulated data, while in the second one we consider the supply level of the Italian national health service with the aim to analyse the regional differences and verify the robustness of the results. Copyright Springer Science+Business Media Dordrecht 2015

Suggested Citation

  • Francesco Vidoli & Elisa Fusco & Claudio Mazziotta, 2015. "Non-compensability in Composite Indicators: A Robust Directional Frontier Method," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 122(3), pages 635-652, July.
  • Handle: RePEc:spr:soinre:v:122:y:2015:i:3:p:635-652
    DOI: 10.1007/s11205-014-0710-y
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    11. Koronakos, Gregory & Smirlis, Yiannis & Sotiros, Dimitris & Despotis, Dimitris K., 2020. "Assessment of OECD Better Life Index by incorporating public opinion," Socio-Economic Planning Sciences, Elsevier, vol. 70(C).
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    15. Fusco, Elisa & Vidoli, Francesco & Sahoo, Biresh K., 2018. "Spatial heterogeneity in composite indicator: A methodological proposal," Omega, Elsevier, vol. 77(C), pages 1-14.
    16. Tziogkidis, Panagiotis & Philippas, Dionisis & Leontitsis, Alexandros & Sickles, Robin C., 2020. "A data envelopment analysis and local partial least squares approach for identifying the optimal innovation policy direction," European Journal of Operational Research, Elsevier, vol. 285(3), pages 1011-1024.
    17. Juan Aparicio & Magdalena Kapelko & Juan F. Monge, 2020. "A Well-Defined Composite Indicator: An Application to Corporate Social Responsibility," Journal of Optimization Theory and Applications, Springer, vol. 186(1), pages 299-323, July.
    18. Färe, Rolf & Karagiannis, Giannis & Hasannasab, Maryam & Margaritis, Dimitris, 2019. "A benefit-of-the-doubt model with reverse indicators," European Journal of Operational Research, Elsevier, vol. 278(2), pages 394-400.
    19. Vidoli, F.; & Fusco, E.; & Pignataro, G.; & Guccio, C.;, 2023. "Multi-directional Robust Benefit of the Doubt model: a comprehensive measure for the quality of health care in OECD countries," Health, Econometrics and Data Group (HEDG) Working Papers 23/14, HEDG, c/o Department of Economics, University of York.
    20. Ramon Sala-Garrido & Manuel Mocholí-Arce & María Molinos-Senante, 2021. "Assessing the Quality of Service of Water Companies: a ‘Benefit of the Doubt’ Composite Indicator," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 155(1), pages 371-387, May.
    21. Leontitsis, Alexandros & Philippas, Dionisis & Sickles, Robin C. & Tziogkidis, Panagiotis, 2018. "Evaluating countries’ innovation potential: an international perspective," Working Papers 18-011, Rice University, Department of Economics.
    22. Juan Aparicio & Magdalena Kapelko, 2019. "Enhancing the Measurement of Composite Indicators of Corporate Social Performance," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 144(2), pages 807-826, July.
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