Social Indicators Research

, Volume 111, Issue 2, pp 527–547 | Cite as

Social and Economic Wellbeing in Europe and the Mediterranean Basin: Building an Enlarged Human Development Indicator

  • Ernest Reig-Martínez


This paper calculates a human Wellbeing Composite Index (WCI) for 42 countries, belonging to the European Economic Space, North Africa and the Middle East, as an alternative to the shortcomings of other well-known measures of socio-economic development (i.e. Gross Domestic Product per head and Human Development Index). To attain this goal, different data envelopment analysis (DEA) models are used as an aggregation tool for seven selected socio-economic variables which correspond to the following wellbeing dimensions: income per capita, environmental burden of disease, income inequality, gender gap, education, life expectancy at birth and government effectiveness. The use of DEA allows avoiding the subjectivity that would be involved in the exogenous determination of weights for the variables included in WCI. The aim is to establish a complete ranking of all countries in the sample, using a three-step process, with the last step consisting in the use of a model that combines DEA and compromise programming, and permits to obtain a set of common weights for all countries in the analysis. The results highlight the distance that still separates Southern Mediterranean countries from the benchmark levels established by some European countries, and also point to the main weaknesses in individual countries’ performance. Nordic countries, plus Switzerland, top the list of best performers, while Mauritania, Libya and Syria appear at the bottom.


Wellbeing Composite Index (WCI) Human development Data envelopment analysis (DEA) Compromise programming European and Southern Mediterranean countries 



Financial support from Sustainmed Project (FP7-KBBE, European Commission) and from AGL2010-17560-C02-02 Project (Plan Nacional de I+D+i, Spanish Government) is gratefully acknowledged.


  1. Adler, N., Friedman, L., & Sinuany-Stern, Z. (2002). Review of ranking methods in the data envelopment analysis context. European Journal of Operational Research, 140, 49–265.CrossRefGoogle Scholar
  2. Alkire, S. (2010). Human development: Definitions, critiques and related concepts. Human Development Research Paper, No. 2010/01, United Nations Development Program.Google Scholar
  3. Barr, R. S., Durchholz, M. L., & Seiford, L. (2000). Peeling the DEA onion: Layering and rank-ordering DMUs using tiered DEA. Technical Report, Southern Methodist University, USA.Google Scholar
  4. Callens, I., & Tyteca, D. (1999). Towards indicators of sustainable development for firms. A productive efficiency perspective. Ecological Economics, 28, 41–53.CrossRefGoogle Scholar
  5. 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.CrossRefGoogle Scholar
  6. Cherchye, L., Moesen, W., Rogge, N., & van Puyenbroek, T. (2007). An introduction to ‘benefit of the doubt’ composite indicators. Social Indicators Research, 82, 111–145.CrossRefGoogle Scholar
  7. Cohon, J. L. (1978). Multiobjective programming and planning. New York: Academic Press.Google Scholar
  8. Cooper, W. W., Seiford, L. M., & Tone, K. (2007). Data envelopment analysis. A comprehensive text with models, applications, references ad DEA-solver software (2nd ed.). Berlin: Springer.Google Scholar
  9. Desai, M. (1991). Human development: Concepts and measurement. European Economic Review, 35(2/3), 350–357.CrossRefGoogle Scholar
  10. Despotis, D. K. (2002). Improving the discriminating power of DEA: Focus on globally efficient units. Journal of the Operational Research Society, 53, 314–323.CrossRefGoogle Scholar
  11. Despotis, D. K. (2005). A reassessment of the human development index via data envelopment analysis. Journal of the Operational Research Society, 56, 969–980.CrossRefGoogle Scholar
  12. Díaz-Balteiro, L., & Romero, C. (2004). In search of a natural systems sustainability index. Ecological Economics, 49(3), 401–405.CrossRefGoogle Scholar
  13. Domínguez-Serrano, M., & Blancas, F. J. (2011). A gender wellbeing composite indicator: The best–worst global evaluation approach. Social Indicators Research, 102, 477–496.CrossRefGoogle Scholar
  14. Emerson, J., Esty, D. C., Srebotnjak, T., Levy, M. A., Mara, V., de Sherbinin, A., et al. (2010). Environmental Performance Index 2010. Yale Center for Environmental Law and Policy, Yale University, and Center for International Earth Science Information-Network, Columbia University, in collaboration with World Economic Forum and Joint Research Center (European Commission).Google Scholar
  15. Gonçalves, E., Correia, J. C., da Silva, G., Angulo, L., & de Carvalho, J. A. (2009). Efficiency and sustainability assessment for a group of farmers in the Brazilian Amazon. Annals of Operational Research, 169, 167–181.CrossRefGoogle Scholar
  16. González, E., Cárcaba, A., & Ventura, J. (2011). The importance of the geographic level of analysis in the assessment of the quality of life: The case of Spain. Social Indicators Research, 102, 209–228.CrossRefGoogle Scholar
  17. Hashimoto, A., & Kodama, M. (1997). Has livability of Japan gotten better for 1956–1990?: A DEA approach. Social Indicators Research, 40, 359–373.CrossRefGoogle Scholar
  18. Hatefi, S. M., & Torabi, S. A. (2010). A common weight MCDA-DEA approach to construct composite indicators. Ecological Economics, 70, 114–120.CrossRefGoogle Scholar
  19. Hausmann, R., Tyson, L. D., & Zahidi, S. (2009). The global gender gap report 2009. Geneva: World Economic Forum.Google Scholar
  20. Jurado, A., & Perez-Mayo, J. (2011). Construction and evolution of a multidimensional well-being index for the Spanish regions. Social Indicators Research. doi: 10.1007/s11205-011-9835-4. Published online: April 13, 2011.
  21. Kao, C., & Hung, H. T. (2005). Data envelopment analysis with common weights: The compromise solution approach. Journal of the Operational Research Society, 56, 1196–1203.CrossRefGoogle Scholar
  22. Kaufmann, D., Kraay, A., & Mastruzzi, M. (2009). Governance matters VIII. Aggregate and individual governance indicators 19962008. Policy Research Working Paper No. 4978, The World Bank. Development Research Group. Macroeconomics and Growth Team.Google Scholar
  23. 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.CrossRefGoogle Scholar
  24. Mahlberg, B., & Obersteiner, M. (2001). Remeasuring the HDI by data envelopment analysis. Interim Report IR-01-069. International Institute for Applied Systems Analysis (Laxenburg, Austria).Google Scholar
  25. Murias, P., Martínez, F., & de Miguel, C. (2006). An economic wellbeing index for the Spanish Provinces: A data envelopment analysis approach. Social Indicators Research, 77, 395–417.CrossRefGoogle Scholar
  26. Nardo, M., Saisana, M., Saltelli, A., Tarantola, S., Hoffman, A., & Giovannini, E. (2008). Handbook on constructing composite indicators: Methodology and user guide. Paris: OECD and Joint Research Center (European Commission).Google Scholar
  27. Reig-Martínez, E., Gómez-Limón, J. A., & Picazo-Tadeo, A. J. (2011). Ranking farms with a composite indicator of sustainability. Agricultural Economics, 42, 561–575.CrossRefGoogle Scholar
  28. Romero, C. (1996). Multicriteria decision analysis and environmental economics: An approximation. European Journal of Operational Research, 96, 81–89.CrossRefGoogle Scholar
  29. Saaty, T. L. (1980). The analytic hierarchy process. Planning, priority setting, resource allocation. New York: McGraw-Hill.Google Scholar
  30. Saaty, T. L. (2001). Decision making for leaders. The analytic hierarchy process for decisions in a complex world (3rd ed.). Pittsburgh: RWS Publications.Google Scholar
  31. Sagar, A. D., & Najam, A. (1998). The human development index: A critical review. Ecological Economics, 25, 249–264.CrossRefGoogle Scholar
  32. Sen, A. (1999). Development as freedom. Oxford: Oxford University Press.Google Scholar
  33. Tone, K. (2001). A slacks-based measure of efficiency in data envelopment analysis. European Journal of Operational Research, 130, 498–509.CrossRefGoogle Scholar
  34. United Nations Development Program (UNDP). (1990). Human development report 1990: Concept and measurement of human development. New York: Oxford University Press.Google Scholar
  35. United Nations Development Program (UNDP). (2009). Linking climate change policies to human development analysis and advocacy. A guidance note for human development report teams. Washington, DC: United Nations Development Programme, Human Development Report Office.Google Scholar
  36. Zaim, O., Färe, R., & Grosskopf, S. (2001). An economic approach to achievement and improvement indexes. Social Indicators Research, 56, 91–118.CrossRefGoogle Scholar
  37. Zhou, P., Ang, B. W., & Poh, K. L. (2007). A mathematical programming approach to constructing composite indicators. Ecological Economics, 62, 291–297.CrossRefGoogle Scholar
  38. Zhou, P., Ang, B. W., & Zhou, D. Q. (2010). Weighting and aggregation in composite indicator construction: A multiplicative optimization approach. Social Indicators Research, 96, 169–181.CrossRefGoogle Scholar
  39. Zhu, J. (2001). Multidimensional quality-of-life measure with an application to Fortune’s best cities. Socio-Economic Planning Sciences, 35, 263–284.CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media B.V. 2012

Authors and Affiliations

  1. 1.Departamento de Economía Aplicada II, Facultad de EconomíaUniversitat de ValènciaValenciaSpain

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