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A Composite Indicator of Social Inclusion for EU based on the Inverted BoD Model. (2023). Ravanos, Panagiotis ; Karagiannis, Giannis.
In: Discussion Paper Series.
RePEc:mcd:mcddps:2023_02.

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  1. An SDG composite index based on Hierarchical DEA and Cooperative Game Theory. (2025). Saavedra-Nieves, Alejandro ; Lozano, Sebastin.
    In: Socio-Economic Planning Sciences.
    RePEc:eee:soceps:v:99:y:2025:i:c:s0038012125000680.

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  2. On the use of Malmquist productivity indices for intertemporal performance assessment by means of composite indicators. (2025). Ravanos, Panagiotis ; Karagiannis, Giannis.
    In: The Journal of Economic Asymmetries.
    RePEc:eee:joecas:v:31:y:2025:i:c:s1703494925000040.

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  3. On the Coherence of Composite Indexes: Multiversal Model and Specification Analysis for an Index of Well-Being. (2024). Tomaselli, Venera ; Cantone, Giulio Giacomo.
    In: MetaArXiv.
    RePEc:osf:metaar:d5y26_v1.

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  4. On the Coherence of Composite Indexes: Multiversal Model and Specification Analysis for an Index of Well-Being. (2024). Tomaselli, Venera ; Cantone, Giulio Giacomo.
    In: MetaArXiv.
    RePEc:osf:metaar:d5y26.

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  2. Atkinson, T., Cantillon, B., Marlier, E. & Nolan, B. (2002). Social Indicators: The EU and social inclusion. Oxford University Press. https://doi.org/10.1093/0199253498.001.0001 Atkinson, A.B., Marlier, E., & Nolan, B. (2004). Indicators and targets for social inclusion in the European Union. Journal of Common Market Studies, 42, 4775. https://doi.org/10.1111/j.0021-9886.2004.00476.x Bastos, J.T., Shen, Y., Hermans, E., Brijs, T., Wets, G., & Pinto Ferraz, A.C. (2015).

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  11. Fernández-Macho, J., González, P. & Virto, J. (2020). Assessing anthropogenic vulnerability of coastal regions: DEA-based index and rankings for the European Atlantic Area. Marine Policy, 119, 104030. https://doi.org/10.1016/j.marpol.2020.104030.
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  12. Fӓre, R., Karagiannis, G., Hassanasab, M., & Margaritis, D. (2019). A Benefit-of-theDoubt model with reverse indicators, European Journal of Operational Research, 278, 394-400. https://doi.org/10.1016/j.ejor.2019.02.009.

  13. Giambona, F., & Vassallo, E. (2014). Composite indicator of social inclusion for European countries. Social Indicators Research, 116, 269-293. https://doi.org/10.1007/s11205-013-0274-2 Herrero‑Prieto, L.C., Boal‑San Miguel, I., & Gómez‑Vega, M. (2020). Deep‑rooted culture and economic development: Taking the seven deadly sins to build a well‑being composite indicator. Social Indicators Research, 144, 601-624. https://doi.org/10.1007/s11205-019-02067-2.

  14. Karagiannis, G. (2021). DEA Models Without Inputs or Outputs: A Tour de Force. In: C. F. Parmeter & R. C. Sickles (Eds.), Advances in Efficiency and Productivity Analysis. NAPW 2018 (pp. 211-232), Springer Proceedings in Business and Economics. Springer, Cham. https://doi.org/10.1007/978-3-030-47106-4_10.

  15. Luxembourg: Publications Office of the European Union. Available at: https://op.europa.eu/webpub/empl/european-pillar-of-socialrights /downloads/KE0921008ENN.pdf Fare, R. Grosskopf, S., Norris, M., & Zhang, Z. (1994). Productivity growth, technical progress and efficiency change in industrialized countries. American Economic Review, 84, 66-83. https://www.jstor.org/stable/2117971 Fӓre, R., & Karagiannis, G. (2014). Benefit-of-the-doubt aggregation and the diet problem, Omega, 47, 33-35. https://doi.org/10.1016/j.omega.2014.03.001.

  16. Rogge and Konttinen (2018) aggregated the same data for year 2014 using a variant of the BoD-I model. In that model, “pie-share” restrictions (see Cherchye et al., 2007) were used to force the share of each of the four indicators in the composite index to be no less than 5%. After estimating this model, the composite index was constructed, for each country, as a geometric mean of its performance in each indicator divided by the overall EU27 performance, using the country-specific weights derived from the weight-restricted BoD-I model. The country ranking obtained differs from that in
    Paper not yet in RePEc: Add citation now
  17. Traffic fatality indicators in Brazil: State diagnosis based on data envelopment analysis research. Accident Analysis and Prevention, 81, 61-73. https://doi.org/10.1016/j.aap.2015.01.024 Blancard, S., Bonnet, M., & Hoarau, J-F. (2021): The influence of agriculture on the structural economic vulnerability of small island spaces: Assessment using DEA based composite indicators, Applied Economics, 53, 79-97. https://doi.org/10.1080/00036846.2020.1795071.
    Paper not yet in RePEc: Add citation now
  18. Van Puyenbroeck, T., & Rogge, N. (2017). Geometric mean quantity index numbers with Benefit-of-the-Doubt weights. European Journal of Operational Research, 256, 1004-1014. https://doi.org/10.1016/j.ejor.2016.07.038 Whittaker, G., Barnhart, B., Färe, R., & Grosskopf, S. (2015). Application of index number theory to the construction of a water quality index: Aggregated nutrient loadings related to the areal extent of hypoxia in the northern Gulf of Mexico. Ecological Indicators, 49, 162-168. https://doi.org/10.1016/j.ecolind.2014.10.003 Footnotes OMC is a voluntary coordination mechanism adopted for monitoring and evaluating EU country performances in policy areas over which these have no real competence and for which control over the policy schemes is maintained as the country level (see Atkinson et al., 2004; Cherchye et al., 2004). Its main features involve identifying best practices and disseminating national experiences between EU countries. (Rogge, 2017).

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