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Undesirable specialization in the construction of composite policy indicators: The Environmental Performance Index

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  • Rogge, Nicky

    () (Hogeschool-Universiteit Brussel (HUB))

Abstract

The non-parametric Data Envelopment Analysis approach is increasingly used to construct composite indicators for country performance monitoring, benchmarking, and policy evaluation in a large variety of fields. The flexibility in the definition of aggregation weights is praised as the method's most important advantage: DEA allows each evaluated country to look for its own optimal weights that maximize the composite indicator relative to the other countries. However, this flexibility also carries a potential disadvantage as it may allow countries to appear as a brilliant performer in a manner that is hard to justify: by ignoring or overemphasizing one or multiple of the judiciously selected performance indicators. To illustrate this issue of undesirable specialization in DEA-based evaluations, this paper compares the Environmental Performance Index (EPI) as computed by the optimistic and pessimistic version of the DEA-model as proposed by Zhou et al. (2007). Based on both computed composites, undesirable specialization in performance is identified.

Suggested Citation

  • Rogge, Nicky, 2012. "Undesirable specialization in the construction of composite policy indicators: The Environmental Performance Index," Working Papers 2012/08, Hogeschool-Universiteit Brussel, Faculteit Economie en Management.
  • Handle: RePEc:hub:wpecon:201208
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    Citations

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    Cited by:

    1. Blancard, Stéphane & Hoarau, Jean-François, 2013. "A new sustainable human development indicator for small island developing states: A reappraisal from data envelopment analysis," Economic Modelling, Elsevier, vol. 30(C), pages 623-635.
    2. repec:eee:ejores:v:264:y:2018:i:1:p:388-401 is not listed on IDEAS
    3. Zanella, Andreia & Camanho, Ana S. & Dias, Teresa G., 2015. "Undesirable outputs and weighting schemes in composite indicators based on data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 245(2), pages 517-530.
    4. Fusco, Elisa, 2015. "Enhancing non-compensatory composite indicators: A directional proposal," European Journal of Operational Research, Elsevier, vol. 242(2), pages 620-630.
    5. H. K. Millington & J. E. Lovell & C. A. K. Lovell, 2013. "Using Fieldwork, GIS and DEA to Guide Management of Urban Stream Health," CEPA Working Papers Series WP072013, School of Economics, University of Queensland, Australia.
    6. Van Puyenbroeck, Tom & Rogge, Nicky, 2017. "Geometric mean quantity index numbers with Benefit-of-the-Doubt weights," European Journal of Operational Research, Elsevier, vol. 256(3), pages 1004-1014.
    7. Stergios Athanassoglou, 2016. "Revisiting Worst-Case DEA for Composite Indicators," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 128(3), pages 1259-1272, September.
    8. Maričić Milica & Bulajić Milica & Radojičić Zoran & Jeremić Veljko, 2016. "Multivariate approach to imposing additional constraints on the Benefit-of-the-Doubt model: The case of QS World University Rankings by Subject," Croatian Review of Economic, Business and Social Statistics, De Gruyter Open, vol. 2(1), pages 1-14, September.
    9. Karagiannis, Giannis & Knox Lovell, C.A., 2016. "Productivity measurement in radial DEA models with a single constant input," European Journal of Operational Research, Elsevier, vol. 251(1), pages 323-328.
    10. 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.
    11. Amado, Carla A.F. & São José, José M.S. & Santos, Sérgio P., 2016. "Measuring active ageing: A Data Envelopment Analysis approach," European Journal of Operational Research, Elsevier, vol. 255(1), pages 207-223.
    12. repec:eee:ecolec:v:139:y:2017:i:c:p:19-32 is not listed on IDEAS

    More about this item

    Keywords

    Data envelopment analysis; benefit of the doubt; Composite indicators; Expert opinion; Undesirable specialization; Environmental Performance Index;

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