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

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Author Info

  • Laurens Cherchye

    ()

  • Wim Moesen

    ()

  • Nicky Rogge

    ()

  • Tom Van Puyenbroeck

    ()

  • Michaela Saisana

    ()

  • A. Saltelli

    ()

  • R. Liska

    ()

  • S. Tarantola

    ()

Abstract

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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Bibliographic Info

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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Keywords: composite indicators; aggregation; weighting; Internal Market;

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References

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  1. Cook, Wade D. & Kress, Moshe, 1994. "A multiple-criteria composite index model for quantitative and qualitative data," European Journal of Operational Research, Elsevier, vol. 78(3), pages 367-379, November.
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Citations

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Cited by:
  1. 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.
  2. Sahoo, Biresh K. & Acharya, Debashis, 2010. "An alternative approach to monetary aggregation in DEA," European Journal of Operational Research, Elsevier, vol. 204(3), pages 672-682, August.
  3. Bryony Hoskins & Massimiliano Mascherini, 2009. "Measuring Active Citizenship through the Development of a Composite Indicator," Social Indicators Research, Springer, vol. 90(3), pages 459-488, February.
  4. Cherchye, Laurens & Moesen, Willem & Rogge, Nicky & Van Puyenbroeck, Tom, 2009. "Constructing a knowledge economy composite indicator with imprecise data," Open Access publications from Katholieke Universiteit Leuven urn:hdl:123456789/237727, Katholieke Universiteit Leuven.
  5. Van den Bossche, Filip & Rogge, Nicky & Devooght, Kurt & Van Puyenbroeck , Tom, 2009. "Robust CSR Investment Screening," Working Papers 2009/05, Hogeschool-Universiteit Brussel, Faculteit Economie en Management.
  6. Darold Barnum & John Gleason, 2011. "Measuring efficiency under fixed proportion technologies," Journal of Productivity Analysis, Springer, vol. 35(3), pages 243-262, June.
  7. 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.
  8. Jean-Charles Billaut & Denis Bouyssou & Philippe Vincke, 2010. "Should you believe in the Shanghai ranking?," Post-Print hal-00388319, HAL.
  9. Ernest Reig, 2012. "Building an Enlarged Human Development Indicator: Europe and the Southern Mediterranean Basin," Working Papers 1203, Department of Applied Economics II, Universidad de Valencia.
  10. Montalvo, Carlos & Moghayer, Saeed, 2011. "State of an innovation system: theoretical and empirical advance towards an innovation efficiency index," MPRA Paper 38002, University Library of Munich, Germany.
  11. P. Zhou & B. Ang, 2009. "Comparing MCDA Aggregation Methods in Constructing Composite Indicators Using the Shannon-Spearman Measure," Social Indicators Research, Springer, vol. 94(1), pages 83-96, October.

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