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Noncompensatory/nonlinear composite indicators for ranking countries: a defensible setting

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  • Giuseppe Munda
  • Michela Nardo

Abstract

Composite indicators (or indexes) are very common in economic and business statistics for benchmarking the mutual and relative progress of countries in a variety of policy domains such as industrial competitiveness, sustainable development, globalization and innovation. The proliferation of the production of composite indicators by all the major international organizations is a clear symptom of their political importance and operational relevance in policy-making. As a consequence, improvements in the way these indicators are constructed and used seem to be a very important research issue from both the theoretical and operational points of view. This article aims at contributing to the improvement of the overall quality of composite indicators (or indexes) by looking at one of their technical weaknesses, that is, the aggregation convention used for their construction. For this aim, we build upon concepts coming from multi-criteria decision analysis, measurement theory and social choice. We start from the analysis of the axiomatic system underlying the mathematical modelling commonly used to construct composite indicators. Then a different methodological framework, based on noncompensatory/nonlinear aggregation rules, is developed. Main features of the proposed approach are: (i) the axiomatic system is made completely explicit and (ii) the sources of technical uncertainty and imprecise assessment are reduced to the minimum possible degree.

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Bibliographic Info

Article provided by Taylor & Francis Journals in its journal Applied Economics.

Volume (Year): 41 (2009)
Issue (Month): 12 ()
Pages: 1513-1523

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Handle: RePEc:taf:applec:v:41:y:2009:i:12:p:1513-1523

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Cited by:
  1. Mónica Domínguez-Serrano & Francisco Blancas, 2011. "A Gender Wellbeing Composite Indicator: The Best-Worst Global Evaluation Approach," Social Indicators Research, Springer, vol. 102(3), pages 477-496, July.
  2. Matteo Mazziotta, Adriano Pareto, 2013. "Methods For Constructing Composite Indices: One For All Or All For One?," RIEDS - Rivista Italiana di Economia, Demografia e Statistica - Italian Review of Economics, Demography and Statistics, SIEDS Societa' Italiana di Economia Demografia e Statistica, vol. 0(2), pages 67-80, April-Jun.
  3. Giuseppe Munda, 2012. "Choosing Aggregation Rules for Composite Indicators," Social Indicators Research, Springer, vol. 109(3), pages 337-354, December.
  4. Radosevic, Slavo & Yoruk, Esin, 2013. "Entrepreneurial propensity of innovation systems: Theory, methodology and evidence," Research Policy, Elsevier, vol. 42(5), pages 1015-1038.
  5. Blancas, Francisco J. & Caballero, Rafael & González, Mercedes & Lozano-Oyola, Macarena & Pérez, Fátima, 2010. "Goal programming synthetic indicators: An application for sustainable tourism in Andalusian coastal counties," Ecological Economics, Elsevier, vol. 69(11), pages 2158-2172, September.
  6. Giuseppe Munda, 2012. "Intensity of preference and related uncertainty in non-compensatory aggregation rules," Theory and Decision, Springer, vol. 73(4), pages 649-669, October.
  7. Emanuele Felice, 2012. "Neither dashboard nor 'mashup' indices: an empirical wealth approach as a pathway to a comprehensive measure of development," UHE Working papers 2012_01, Universitat Autònoma de Barcelona, Departament d'Economia i Història Econòmica, Unitat d'Història Econòmica.
  8. Stergios Athanassoglou, 2013. "Robust Multidimensional Welfare Comparisons: One Vector of Weights, One Vote," Working Papers 2013.40, Fondazione Eni Enrico Mattei.
  9. P. Zhou & B. Ang & D. Zhou, 2010. "Weighting and Aggregation in Composite Indicator Construction: a Multiplicative Optimization Approach," Social Indicators Research, Springer, vol. 96(1), pages 169-181, March.
  10. Enrico Casadio Tarabusi & Giulio Guarini, 2013. "An Unbalance Adjustment Method for Development Indicators," Social Indicators Research, Springer, vol. 112(1), pages 19-45, May.

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