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Creating Composite Indicators with DEA and Robustness Analysis: the case of the Technology Achievement Index

  • Laurens Cherchye


  • Wim Moesen


  • Nicky Rogge


  • Tom Van Puyenbroeck


  • Michaela Saisana


  • A. Saltelli


  • R. Liska


  • S. Tarantola


Composite indicators are regularly used for benchmarking countries’ performance, but equally often stir controversies about the unavoidable subjectivity that is connected with their construction. Data Envelopment Analysis helps to overcome some key limitations, viz., the undesirable dependence of final results from the preliminary normalization of sub-indicators, and, more cogently, from the subjective nature of the weights used for aggregating. Still, subjective decisions remain, and such modelling uncertainty propagates onto countries’ composite indicator values and relative rankings. Uncertainty and sensitivity analysis are therefore needed to assess robustness of final results and to analyze how much each individual source of uncertainty contributes to the output variance. The current paper reports on these issues, using the Technology Achievement Index as an illustration.factor is more important in explaining the observed progress.

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Paper provided by Katholieke Universiteit Leuven, Centrum voor Economische Studiën, Working Group Public Economics in its series Public Economics Working Paper Series with number ces0613.

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Length: 21 pp.
Date of creation: 2006
Date of revision:
Handle: RePEc:wpe:papers:ces0613
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  1. Meghnad Desai & Sakiko Fukuda-Parr & Claes Johansson & Fransisco Sagasti, 2002. "Measuring the Technology Achievement of Nations and the Capacity to Participate in the Network Age," Journal of Human Development and Capabilities, Taylor & Francis Journals, vol. 3(1), pages 95-122.
  2. Sen, Amartya, 1997. "On Economic Inequality," OUP Catalogue, Oxford University Press, number 9780198292975.
  3. Michela Nardo & Michaela Saisana & Andrea Saltelli & Stefano Tarantola & Anders Hoffman & Enrico Giovannini, 2005. "Handbook on Constructing Composite Indicators: Methodology and User Guide," OECD Statistics Working Papers 2005/3, OECD Publishing.
  4. Atkinson, Tony & Cantillon, Bea & Marlier, Eric & Nolan, Brian, 2002. "Social Indicators: The EU and Social Inclusion," OUP Catalogue, Oxford University Press, number 9780199253494.
  5. M. Desai, S. Fukuda-Parr, C. Johansson, and F. Sagasti, 2002. "Measuring Technology Achievement of Nations and the Capacity to Participate in the Network Age," Human Development Occasional Papers (1992-2007) HDOCPA-2002-22, Human Development Report Office (HDRO), United Nations Development Programme (UNDP).
  6. 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.
  7. Sarrico, C. S. & Dyson, R. G., 2004. "Restricting virtual weights in data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 159(1), pages 17-34, November.
  8. Charnes, A. & Cooper, W. W. & Rhodes, E., 1978. "Measuring the efficiency of decision making units," European Journal of Operational Research, Elsevier, vol. 2(6), pages 429-444, November.
  9. Cherchye, Laurens & Kuosmanen, Timo, 2004. "Benchmarking Sustainable Development: A Synthetic Meta-index Approach," Working Paper Series UNU-WIDER Research Paper , World Institute for Development Economic Research (UNU-WIDER).
  10. Léopold Simar, 2003. "Detecting Outliers in Frontier Models: A Simple Approach," Journal of Productivity Analysis, Springer, vol. 20(3), pages 391-424, November.
  11. Laurens Cherchye & Knox Lovell & Wim Moesen & Tom Van Puyenbroeck, 2005. "One Market, One Number? A Composite Indicator Assessment of EU Internal Market Dynamics," Public Economics Working Paper Series ces0513, Katholieke Universiteit Leuven, Centrum voor Economische Studiën, Working Group Public Economics.
  12. Michael Freudenberg, 2003. "Composite Indicators of Country Performance: A Critical Assessment," OECD Science, Technology and Industry Working Papers 2003/16, OECD Publishing.
  13. Simar, L. & Wilson, P.W., . "Sensitivity analysis of efficiency scores: how to bootstrap in nonparametric frontier models," CORE Discussion Papers RP 1304, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
  14. Laurens Cherchye & Wim Moesen & Tom Puyenbroeck, 2004. "Legitimately Diverse, yet Comparable: On Synthesizing Social Inclusion Performance in the EU," Journal of Common Market Studies, Wiley Blackwell, vol. 42(5), pages 919-955, December.
  15. Cazals, Catherine & Florens, Jean-Pierre & Simar, Leopold, 2002. "Nonparametric frontier estimation: a robust approach," Journal of Econometrics, Elsevier, vol. 106(1), pages 1-25, January.
  16. Storrie, Donald & Bjurek, Hans, 2000. "Benchmarking European labour market performance with efficiency frontier techniques," Discussion Papers, Research Unit: Labor Market Policy and Employment FS I 00-211, Social Science Research Center Berlin (WZB).
  17. Knox Lovell, C. A. & Pastor, Jesus T. & Turner, Judi A., 1995. "Measuring macroeconomic performance in the OECD: A comparison of European and non-European countries," European Journal of Operational Research, Elsevier, vol. 87(3), pages 507-518, December.
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