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Benchmarking European labour market performance with efficiency frontier techniques

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  • Storrie, Donald
  • Bjurek, Hans

Abstract

The issue addressed in this paper is how to obtain a composite measure of several indicators using benchmarking principles. While the exposition is only in two dimensions, and thus can be presented graphically, this is sufficient to capture the essence of the methodology and provide the basis for a critical examination of the assumptions. The data used is labour market statistics for the Member States of the European Union. The proposed approach comes from a technique originally used in production theory, namely efficiency frontiers. Here, however, we benchmark not efficiency but performance. There are two main problems. First, related to composite measures, how does one compare (weigh) indicators that are not obviously comparable? Second, related to benchmarking, how does one benchmark countries that may differ considerably as regards the mix of the various indicators. Both these issues concern weights and require that the weighting system should be parsimonious as regards assumptions and flexible, in that not all countries should necessarily be awarded the same weights.

Suggested Citation

  • 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, WZB Berlin Social Science Center.
  • Handle: RePEc:zbw:wzblpe:fsi00211
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    Citations

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    Cited by:

    1. Gebel, Michael, 2006. "Monitoring und Benchmarking bei arbeitsmarktpolitischen Maßnahmen," ZEW Dokumentationen 06-01, ZEW - Leibniz Centre for European Economic Research.
    2. Fusco, Elisa, 2015. "Enhancing non-compensatory composite indicators: A directional proposal," European Journal of Operational Research, Elsevier, vol. 242(2), pages 620-630.
    3. Fabio Pammolli & Francesco Porcelli & Francesco Vidoli & Guido Borà, 2014. "La spesa sanitaria delle Regioni in Italia - Saniregio 3," Working Papers CERM 02-2014, Competitività, Regole, Mercati (CERM).
    4. Fabio Pammolli & Francesco Porcelli & Francesco Vidoli & Monica Auteri & Guido Borà, 2017. "La spesa sanitaria delle Regioni in Italia - Saniregio2017," Working Papers CERM 01-2017, Competitività, Regole, Mercati (CERM).
    5. Jacqueline O’Reilly, 2006. "Framing comparisons: gendering perspectives on cross-national comparative research on work and welfare," Work, Employment & Society, British Sociological Association, vol. 20(4), pages 731-750, December.
    6. Martínez Roget, F. & Murias Fernández, P. & Miguel Domínguez, J.C. De, 2005. "El análisis envolvente de datos en la construcción de indicadores sintéticos. Una aplicación a las provincias españolas/DEA Construction of Composite Indicators. An Application to the Spanish Province," Estudios de Economia Aplicada, Estudios de Economia Aplicada, vol. 23, pages 753-771, Diciembre.
    7. Fabio Pammolli & Francesco Porcelli & Francesco Vidoli & Guido Borà, 2015. "La spesa sanitaria delle Regioni in Italia - Saniregio 2015," Working Papers CERM 01-2015, Competitività, Regole, Mercati (CERM), revised 04 Jan 2016.
    8. 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.
    9. L Cherchye & W Moesen & N Rogge & T Van Puyenbroeck & M Saisana & A Saltelli & R Liska & S Tarantola, 2008. "Creating composite indicators with DEA and robustness analysis: the case of the Technology Achievement Index," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 59(2), pages 239-251, February.
    10. Laurens Cherchye & Wim Moesen & Tom Van 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.
    11. Cherchye, Laurens & Moesen, Willem & Rogge, Nicky, 2009. "Constructing a Knowledge Economy Composite Indicator with Imprecise Data," Working Papers 2009/16, Hogeschool-Universiteit Brussel, Faculteit Economie en Management.
    12. Riccardo Natoli & Segu Zuhair, 2011. "Measuring Progress: A Comparison of the GDP, HDI, GS and the RIE," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 103(1), pages 33-56, August.
    13. Martínez Roget, Fidel & Murias Fernández, Pilar, 2011. "Pension Systems And Economic Well-Being Of Older People: A Synthetic Indicator For The Oecd Countries," Revista Galega de Economía, University of Santiago de Compostela. Faculty of Economics and Business., vol. 20(ex).
    14. Pilar Murias & José Miguel & David Rodríguez, 2008. "A Composite Indicator for University Quality Assesment: The Case of Spanish Higher Education System," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 89(1), pages 129-146, October.
    15. Francesco Vidoli & Elisa Fusco & Claudio Mazziotta, 2015. "Non-compensability in Composite Indicators: A Robust Directional Frontier Method," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 122(3), pages 635-652, July.
    16. Pilar Murias & Simone Novello & Fidel Martinez, 2012. "The Regions of Economic Well-being in Italy and Spain," Regional Studies, Taylor & Francis Journals, vol. 46(6), pages 793-816, June.

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