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Composite Indicators as a Useful Tool for International Comparison: The Europe 2020 Example

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  • Lenka Hudrliková

Abstract

Composite indicators as a tool for a ranking become more and more popular, because they illustrate a comprehensive view on a phenomenon that cannot be captured by only one single indicator. Indicators for Europe 2020 are set of indicators used for monitoring targets defined by the European Commission in the Strategy of Smart, Sustainable and Inclusive Growth. The main objective of this paper is the comparison of performance of the EU Member States using the composite indicator principles. Within constructing composite indicators several steps have to be made and corresponding methods have to be chosen. There is not only one correct method how to develop a composite indicator. Of course, the choice of the methods manipulates the results. Primarily, normalisation methods, weighting schemes and aggregation formulas are fundamental but very subjective. This paper deals with two types of normalisation (z-score and min-max) and four weighting and aggregation schemes (equal weighting with linear aggregation, principal components analysis, benefit of doubt method and multi-criteria analysis). European countries ranking is provided according to the seven different scenarios.

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  • Lenka Hudrliková, 2013. "Composite Indicators as a Useful Tool for International Comparison: The Europe 2020 Example," Prague Economic Papers, Prague University of Economics and Business, vol. 2013(4), pages 459-473.
    • Handle: RePEc:prg:jnlpep:v:2013:y:2013:i:4:id:462:p:459-473
    DOI: 10.18267/j.pep.462
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    References listed on IDEAS

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    1. Giuseppe Munda & Michela Nardo, 2009. "Noncompensatory/nonlinear composite indicators for ranking countries: a defensible setting," Applied Economics, Taylor & Francis Journals, vol. 41(12), pages 1513-1523.
    2. A. Saltelli & G. Mundo & M. Nardo, 2006. "From Complexity to Multidimensionality. The Role of Composite Indicators for Advocacy of EU Reform," Review of Business and Economic Literature, KU Leuven, Faculty of Economics and Business (FEB), Review of Business and Economic Literature, vol. 0(3), pages 221-235.
    3. 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.
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    Cited by:

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    2. Fusco, Elisa & Maggi, Bernardo & Rizzuto, Livia, 2022. "Alternative indicators for the evaluation of renewables in Europe: An efficiency approach," Renewable Energy, Elsevier, vol. 190(C), pages 48-65.
    3. Aditi Jamalpuria, 2017. "Environmental Regulatory Efficacy in India: An Inter-State Comparison," Journal of Environmental Assessment Policy and Management (JEAPM), World Scientific Publishing Co. Pte. Ltd., vol. 19(03), pages 1-28, September.

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    More about this item

    Keywords

    international comparison; principal component analysis; composite indicator; the Europe 2020 indicators; benefit of doubt analysis; multi-criteria analysis;
    All these keywords.

    JEL classification:

    • C38 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Classification Methdos; Cluster Analysis; Principal Components; Factor Analysis
    • C43 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Index Numbers and Aggregation
    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis
    • O1 - Economic Development, Innovation, Technological Change, and Growth - - Economic Development

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