Skip to main content
Log in

Disentangling Heterogeneity Gaps and Pure Performance Differences in Composite Indexes Over Time: The Case of the Europe 2020 Strategy

  • Published:
Social Indicators Research Aims and scope Submit manuscript

Abstract

Composite indexes have been widely used in different contexts to evaluate the performances of entities. The popularity of these indexes come mainly from their ease of use, interpretation and computation. In practice, heterogeneity could be present in the performance evaluation exercise due to differences between entities. For example, they could differ with respect to their ownership, geographical localization, economic infrastructure, resource endowments, social environment, and so on. As a result, composite indexes fail to capture the performance differences, as they are biased by the presence of heterogeneity. In this paper, we suggest a simple procedure to disentangle the heterogeneity gaps and pure performance differences in the composite indexes over time. We apply our procedure to the case of the Europe 2020 strategy by distinguishing between old and new European members.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1

Source: Author’s computations

Fig. 2

Source: Author’s computations

Fig. 3

Source: Author’s computations

Fig. 4

Source: Author’s computations

Fig. 5

Source: Author’s computations

Fig. 6

Source: Author’s computations

Fig. 7

Source: Author’s computations

Similar content being viewed by others

References

  • Battese, G. E., & Rao, D. P. (2002). Technology gap, efficiency, and a stochastic metafrontier function. International Journal of Business Economics, 1(2), 87–93.

    Google Scholar 

  • Battese, G. E., Rao, D. P., & O’Donnell, C. J. (2004). A metafrontier production function for estimation of technical efficiencies and technology gaps for firms operating under different technologies. Journal of Productivity Analysis, 21, 91–103.

    Article  Google Scholar 

  • Charnes, A., Cooper, W. W., & Rhodes, E. (1978). Measuring the efficiency of decision making units. European Journal of Operational Research, 2, 429–444.

    Article  Google Scholar 

  • Cherchye, L., Lovell, C. A., Moesen, W., & Van Puyenbroeck, T. (2007a). One market, one number? A composite indicator assessment of EU internal market dynamics. European Economic Review, 51, 749–779.

    Article  Google Scholar 

  • Cherchye, L., Moesen, W., Rogge, N., & Van Puyenbroeck, T. (2007b). An introduction to benefit of the doubt composite indicators. Social Indicators Research, 82, 111–145.

    Article  Google Scholar 

  • Cherchye, L., Moesen, W., Rogge, N., Van Puyenbroeck, T., Saisana, M., Saltelli, A., et al. (2008). Creating composite indicators with DEA and robustness analysis: The case of the technology achievement index. Journal of the Operational Research Society, 59, 239–251.

    Article  Google Scholar 

  • Colak, M. S., & Ege, A. (2013). An assessment of EU 2020 strategy: Too far to reach? Social Indicators Research, 110, 659–680.

    Article  Google Scholar 

  • European Commission. (2010). Europe 2020: A strategy for smart, sustainable and inclusive growth. Brussels: European Commissions.

    Google Scholar 

  • Freudenberg, M. (2003). Composite indicators of country performance: A critical assessment. OECD Science, Technology and Industry Working Papers, 16.

  • Fusco, E., Vidoli, F., & Sahoo, B. K. (2018). Spatial heterogeneity in composite indicator: A methodological proposal. Omega, 77, 1–14.

    Article  Google Scholar 

  • Hayami, Y., & Ruttan, V. W. (1970). Agricultural productivity differences among countries. American Economic Review, 60, 895–911.

    Google Scholar 

  • Karagiannis, R., & Karagiannis, G. (2018). Intra- and inter-group composite indicators using the BoD model. Socio-Economic Planning Sciences, 61, 44–51.

    Article  Google Scholar 

  • OECD. (2008). Handbook on constructing composite indicators methodology and user guide. Paris: OECD Publications.

    Book  Google Scholar 

  • Pasimeni, P. (2012). Measuring Europe 2020: A new tool to assess the strategy. International Journal of Innovation and Regional Development, 4, 365–385.

    Article  Google Scholar 

  • Pasimeni, P. (2013). The Europe 2020 index. Social Indicators Research, 110, 613–635.

    Article  Google Scholar 

  • Pasimeni, F., & Pasimeni, P. (2016). An institutional analysis of the Europe 2020 strategy. Social Indicators Research, 127, 1021–1038.

    Article  Google Scholar 

  • Rappai, G. (2016). Europe en route to 2020: A new way of evaluating the overall fulfillment of the Europe 2020 strategic goals. Social Indicators Research, 129, 77–93.

    Article  Google Scholar 

  • Rogge, N. (2018). On aggregating benefit of the doubt composite indicators. European Journal of Operational Research, 264, 364–369.

    Article  Google Scholar 

  • Saltelli, A., D’Hombres, B., Jesinghaus, J., Manca, A., Mascherini, M., Nardo, M., et al. (2011). Indicators for EU policies. Business as usual? Social Indicators Research, 102, 197–207.

    Article  Google Scholar 

  • Walheer, B. (2017). Decomposing the Europe 2020 index. Social Indicators Research. https://doi.org/10.1007/s11205-017-1797-8.

    Google Scholar 

  • Walheer, B. (2018). Aggregation of metafrontier technology gap ratios: The case of European sectors in 1995–2015. European Journal of Operational Research, 269, 1013–1026.

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Barnabé Walheer.

Additional information

We thank the Editor in Chief Filomena Maggino and three anonymous referees for their comments that improved the paper substantially.

Appendix

Appendix

See Table 1.

Table 1 Abbreviations

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Walheer, B. Disentangling Heterogeneity Gaps and Pure Performance Differences in Composite Indexes Over Time: The Case of the Europe 2020 Strategy. Soc Indic Res 143, 25–45 (2019). https://doi.org/10.1007/s11205-018-1974-4

Download citation

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11205-018-1974-4

Keywords

Navigation