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The performance of education systems in the light of Europe 2020 strategy

  • S.I.: Data Envelopment Analysis: Four Decades On
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Abstract

The performance evaluation of education systems is at the top of the agenda of governments and education authorities worldwide. However, research involving cross-country comparisons of the performance of education systems is still incipient. This paper proposes a new composite indicator to summarise the performance of education systems, enabling benchmarking comparisons and the definition of objectives for improvement. The research analyses different modelling alternatives for the construction of composite indicators, with varying degrees of weight flexibility. Our study uses annual data of 29 European countries, collected from Eurostat and the Organisation for Economic Co-operation and Development databases. The results obtained in terms of performance scores and country rankings are presented and their managerial implications are discussed. We conclude that composite indicators estimated using frontier techniques can support the transition from the paradigm of performance assessment (control) to performance management (improvement).

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Notes

  1. http://ec.europa.eu/education/policy/strategic-framework_en.

  2. http://ec.europa.eu/europe2020/europe-2020-in-a-nutshell/targets/index_en.htm.

  3. http://ec.europa.eu/eurostat/web/education-and-training/data/database.

  4. http://www.oecd.org/pisa/data/2015database/.

References

  • Afonso, A., & Aubyn, M. S. (2004). Non-parametric approaches to education and health expenditure efficiency in OECD countries. ISEG-UTL Economics working paper no. 1/2004/DE/CISEP/UECE.

  • Afonso, A., & Aubyn, M. S. (2006). Cross-country efficiency of secondary education provision: A semi-parametric analysis with nondiscretionary inputs. Economic Modelling,23(3), 476–491.

    Article  Google Scholar 

  • Agasisti, T. (2011). Performances and spending efficiency in higher education: A European comparison through non-parametric approaches. Education Economics,19(2), 199–224.

    Article  Google Scholar 

  • Agasisti, T. (2014). The efficiency of public spending on education: An empirical comparison of EU countries. European Journal of Education,49(4), 543–557.

    Article  Google Scholar 

  • Allen, R., Athanassopoulos, A. D., Dyson, R. G., & Thanassoulis, E. (1997a). Weights restrictions and value judgments in data envelopment analysis: Evolution, development and future directions. Annals of Operations Research,73, 13–64.

    Article  Google Scholar 

  • Allen, R., Athanassopoulos, A., Dyson, R. G., & Thanassoulis, E. (1997b). Weights restrictions and value judgements in data envelopment analysis: Evolution, development and future directions. Annals of Operations Research,73, 13–34.

    Article  Google Scholar 

  • Blancas, F. J., Contreras, I., & Ramírez-Hurtado, J. M. (2012). Constructing a composite indicator with multiplicative aggregation under the objective of ranking alternatives. Journal of the Operational Research Society,64(5), 668–678.

    Article  Google Scholar 

  • Bogetoft, P., Heinesen, E., & Tranæs, T. (2015). The efficiency of educational production: A comparison of the Nordic countries with other OECD countries. Economic Modelling,50, 310–321.

    Article  Google Scholar 

  • Breakspear, S. (2012). The policy impact of PISA: An exploration of the normative effects of international benchmarking in school system performance, OECD education working papers, no. 71. OECD Publishing, Paris.

  • Burck, J., Marten, F., Bals, C., & Hohne, N. (2018). The Climate change performance index: Results 2018. Germanwatch. https://germanwatch.org/sites/germanwatch.org/files/publication/20504.pdf. Accessed 5 Aug 2019.

  • Calabria, F., Camanho, A. S., & Zanella, A. (2018). The use of composite indicators to evaluate the performance of Brazilian hydropower plants. International Transactions in Operations Research,25(4), 1323–1343.

    Article  Google Scholar 

  • Charnes, A., Cooper, W. W., & Rhodes, E. (1978). Measuring the efficiency of decision making units. European Journal of Operational Research,2(6), 429–444.

    Article  Google Scholar 

  • Charnes, A., Cooper, W. W., & Rhodes, E. (1981). Evaluating program and managerial efficiency: An application of data envelopment analysis to program follow through. Management Science,27(6), 668–697.

    Article  Google Scholar 

  • Cherchye, L., Moesen, W., & Puyenbroeck, T. (2004). Legitimately diverse, yet comparable: On synthesizing social inclusion performance in the EU. JCMS: Journal of Common Market Studies,42(5), 919–955.

    Google Scholar 

  • Cherchye, L., Moesen, W., Rogge, N., & Puyenbroeck, T. V. (2007). An introduction to ‘benefit of the doubt’ composite indicators. Social Indicators Research,82(1), 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 

  • Clements, B. (2002). How efficient is education spending in Europe? European Review of Economics and Finance,1(1), 3–26.

    Google Scholar 

  • Cooper, W. W., Seiford, L., & Tone, K. (2000). Data envelopment analysis. Boston: Kluwer Academic Publishers.

    Google Scholar 

  • De Witte, K., & López-Torres, L. (2017). Efficiency in education: A review of literature and a way forward. Journal of the Operational Research Society,68(4), 339–363.

    Article  Google Scholar 

  • Delors, J., et al. (1996). Report to UNESCO on education for the 21st century—Learning: The treasure within. Paris: UNESCO.

    Google Scholar 

  • Despotis, D. K. (2004). A reassessment of the human development index via data envelopment analysis. Journal of the Operational Research Society,56(8), 969–980.

    Article  Google Scholar 

  • Despotis, D. K. (2005). Measuring human development via data envelopment analysis: The case of Asia and the Pacific. Omega,33(5), 385–390.

    Article  Google Scholar 

  • Dyson, R. G., Allen, R., Camanho, A. S., Podinovski, V. V., Sarrico, C. S., & Shale, E. A. (2001). Pitfalls and protocols in DEA. European Journal of Operational Research,132(2), 245–259.

    Article  Google Scholar 

  • Dyson, R. G., & Thanassoulis, E. (1988). Reducing weight flexibility in data envelopment analysis. Journal of the Operational Research Society,39(6), 563–576.

    Article  Google Scholar 

  • Emerson, J. W., Hsu, A., Levy, M. A., de Sherbinin, A., Mara, V., Esty, D. C., et al. (2012). Environmental performance index and pilot trend environmental performance index. http://sedac.ciesin.columbia.edu/data/set/epi-environmental-performance-index-pilot-trend-2012. Accessed 20 Mar 2018.

  • Fare, R., Grosskopf, S., & Hernandez-Sancho, F. (2004). Environmental performance: An index number approach. Resource and Energy Economics,26, 343–352.

    Article  Google Scholar 

  • Flisi, S., Goglio, V., & Meroni, E. (2014). Monitoring the evolution of education and training systems: A guide to the joint assessment framework. Luxembourg: Joint Research Centre, Publications Office of the European Union. https://doi.org/10.2788/15187.

  • Freudenberg, M. (2003). Composite indicators of country performance: A critical assessment, STI working paper 2003/16, Organization for Economic Co-operation and Development, Paris.

  • Fried, H. O., Lovell, C. K., & Schmidt, S. S. (Eds.). (2008). The measurement of productive efficiency and productivity growth. Oxford: Oxford University Press.

    Google Scholar 

  • Fuentes, A. (2009). Raising education outcomes in Spain, OECD Economics Department working papers, no. 666. OECD Publishing, Paris.

  • Giambona, F., Vassallo, E., & Vassiliadis, E. (2011). Educational systems efficiency in European Union countries. Studies in Educational Evaluation,37(2–3), 108–122.

    Article  Google Scholar 

  • Gilthorpe, M. S. (1995). The importance of normalization in the construction of deprivation indices. Journal of Epidemiology and Community Health,49(Supplement 2), S45–S50.

    Article  Google Scholar 

  • Gimenez, V., Prior, D., & Thieme, C. (2007). Technical efficiency, managerial efficiency and objective-setting in the educational system: An international comparison. Journal of the Operational Research Society,58(8), 996–1007.

    Article  Google Scholar 

  • Grupp, H., & Mogee, M. E. (2004). Indicators for national science and technology policy: How robust are composite indicators? Research Policy,33(9), 1373–1384.

    Article  Google Scholar 

  • Hanushek, E. A., & Luque, J. A. (2003). Efficiency and equity in schools around the world. Economics of education Review,22(5), 481–502.

    Article  Google Scholar 

  • Hashimoto, A. (1996). A DEA selection system for selective examinations. Journal of the Operations Research Society of Japan,39(4), 475–485.

    Article  Google Scholar 

  • Horta, I. M., Camanho, A. S., & Costa, J. M. (2010). Performance assessment of construction companies integrating key performance indicators and data envelopment analysis. Journal of Construction Engineering and Management,136(5), 581–594.

    Article  Google Scholar 

  • Karagiannis, G. (2017). On aggregate composite indicators. Journal of the Operational Research Society,68(7), 741–746.

    Article  Google Scholar 

  • Koopmans, T. (1951). An analysis of production as an efficient combination of activities. In T. Koopmans (Ed.), Activity analysis of production and allocation (pp. 33–97). New York: Wiley.

    Google Scholar 

  • Liu, W., Meng, W., & Zhang, T. Q. (2006). Incorporating Value Judgments in DEA. In N. K. Avkiran (Ed.), Productivity analysis in the service sector using data envelopment analysis. Australia: The University of Queensland Business School.

    Google Scholar 

  • Lovell, C. A. K., Pastor, J. T., & Turner, J. A. (1995). Measuring macroeconomic performance in the OECD: A comparison of European and non-European countries. European Journal of Operational Research,87(3), 507–518.

    Article  Google Scholar 

  • Mahlberg, B., & Obersteiner, M. (2001). Remeasuring the HDI by data envelopment analysis. Laxenburg: International Institute for Applied Systems Analysis.

    Google Scholar 

  • Morais, P., & Camanho, A. S. (2011). Evaluation of performance of European cities with the aim to promote quality of life improvements. Omega,39(4), 398–409.

    Article  Google Scholar 

  • Murias, P., Miguel, J. C., & Rodriguez, D. (2007). A composite indicator for university quality assessment: The case of Spanish higher education system. Social Indicators Research,89(1), 129–146.

    Article  Google Scholar 

  • OECD. (2008). Joint Research Centre-European Commission. Handbook on constructing composite indicators: Methodology and User guide. Paris: OECD Publishing.

    Google Scholar 

  • Podinovski, V. V., & Athanassopoulos, A. D. (1998). Assessing the relative efficiency of decision making units using DEA models with weight restrictions. Journal of the Operational Research Society,49(5), 500–508.

    Article  Google Scholar 

  • Saisana, M. (2008). The 2007 composite learning index: Robustness issues and critical assessment. Ispra: European Commission, Joint Research Centre.

    Google Scholar 

  • Saltelli, A. (2007). Composite indicators between analysis and advocacy. Social Indicators Research,81(1), 65–77.

    Article  Google Scholar 

  • Sapir, A. (2006). Globalization and the reform of European social models. JCMS: Journal of Common Market Studies,44(2), 369–390.

    Google Scholar 

  • Sarrico, C. S., & Dyson, R. G. (2004). Restricting virtual weights in data envelopment analysis. European Journal of Operational Research,159(1), 17–34.

    Article  Google Scholar 

  • Shen, Y., Hermans, E., Brijs, T., & Wets, G. (2013). Data envelopment analysis for composite indicators: A multiple layer model. Social Indicators Research,114(2), 739–756.

    Article  Google Scholar 

  • Šonje, A. A., Deskar-Škrbić, M., & Šonje, V. (2018). Efficiency of public expenditure on education: Comparing Croatia with other NMS. In INTED2018 conference proceedings (pp. 2317–2326).

  • Stiftung, B. (2010). Making lifelong learning tangible. The European ELLI-index 2010. http://www.deutscher-lernatlas.de/fileadmin/Inhalte/Ergebnisse/Publikationen/ELLI_EU_eng.pdf. Accessed 17 Apr 2017.

  • Stiftung, B. (2013). The German learning atlas: Making lifelong learning tangible on a regional level. http://www.deutscher-lernatlas.de/fileadmin/Inhalte/Ergebnisse/Publikationen/DLA_Expose_120206.pdf. Accessed 17 Apr 2017.

  • Sutherland, D., Price, R., & Gonand, F. (2010). Improving public spending efficiency in primary and secondary education. OECD Journal: Economic Studies,2009(1), 1–30.

    Google Scholar 

  • Thanassoulis, E., De Witte, K., Johnes, J., Johnes, G., Karagiannis, G., & Portela, C. S. (2016). Applications of data envelopment analysis in education. In Data envelopment analysis (pp. 367–438). Boston, MA: Springer.

  • Thanassoulis, E., Portela, M. C., & Allen, R. (2004). Incorporating value judgments in DEA. Handbook on data envelopment analysis (pp. 99–138). Boston: Springer.

    Chapter  Google Scholar 

  • Thieme, C., Gimenez, V., & Prior, D. (2012). A comparative analysis of the efficiency of national education systems. Asia Pacific Education Review,13(1), 1–15.

    Article  Google Scholar 

  • Thompson, R. G., Langemeier, L. N., Lee, C. T., Lee, E., & Thrall, R. M. (1990). The role of multiplier bounds in efficiency analysis with application to Kansas farming. Journal of econometrics,46(1–2), 93–108.

    Article  Google Scholar 

  • Thompson, R. G., Singleton, F. D., Thrall, R. M., & Smith, B. A. (1986). Comparative site evaluations for locating a high-energy physics lab in texas. Interfaces,16(6), 35–49.

    Article  Google Scholar 

  • Van Vught, F. A. (2006). Youth, education and the labour market. Brussels: European Commission.

    Google Scholar 

  • Wong, Y. H., & Beasley, J. E. (1990). Restricting weight flexibility in data envelopment analysis. Journal of the Operational Research Society,41(9), 829–835.

    Article  Google Scholar 

  • Zaim, O., Fare, R., & Grosskopf, S. (2001). An economic approach to achievement and improvement indexes. Social Indicators Research,56(1), 91–118.

    Article  Google Scholar 

  • Zanella, A., Camanho, A. S., & Dias, T. G. (2013). Benchmarking countries’ environmental performance. Journal of the Operational Research Society,64(3), 426–438.

    Article  Google Scholar 

  • Zanella, A., Camanho, A. S., & Dias, T. G. (2015a). Undesirable outputs and weighting schemes in composite indicators based on data envelopment analysis. European Journal of Operational Research,245(2), 517–530.

    Article  Google Scholar 

  • Zanella, A., Camanho, A. S., & Dias, T. G. (2015b). The assessment of cities’ livability integrating human wellbeing and environmental impact. Annals of Operations Research,226(1), 695–726.

    Article  Google Scholar 

  • Zhou, P., Ang, B. W., & Poh, K. L. (2007). A mathematical programming approach to constructing composite indicators. Ecological Economics,62, 291–297.

    Article  Google Scholar 

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Authors and Affiliations

  1. Vilnius University Institute of Data Science and Digital Technologies, Akademijos str. 4, 08663, Vilnius, Lithuania

    Dovile Stumbriene & Audrone Jakaitiene

  2. Faculdade de Engenharia, Universidade do Porto, R. Dr. Roberto Frias, 4200-465, Porto, Portugal

    Ana S. Camanho

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  1. Dovile Stumbriene
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Stumbriene, D., Camanho, A.S. & Jakaitiene, A. The performance of education systems in the light of Europe 2020 strategy. Ann Oper Res 288, 577–608 (2020). https://doi.org/10.1007/s10479-019-03329-5

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