Social Indicators Research

, Volume 118, Issue 3, pp 987–1007 | Cite as

Measuring World Better Life Frontier: A Composite Indicator for OECD Better Life Index

  • Hideyuki MizobuchiEmail author


The OECD Better Life initiative recently released a comprehensive set of 11 indicators of well-being covering a group of countries. Each individual indicator corresponds to a key topic that is essential to well-being. However, the problem of aggregating them is left to users of this dataset. Using these as individual indicators, we propose a composite indicator of overall well-being, which is intended to measure the performance of each country in terms of providing well-being to its people. The ‘benefit of the doubt’ approach (BOD), a well-known aggregation tool based on a weighed sum, assigns the most favourable weights for each entity under investigation. BOD may also be considered to evaluate the performance of each entity in terms of its efficiency. Regarding individual indicators as outputs, it constructs the benchmark production frontier from observed individual indicators. A composite indicator based on BOD equals the distance between each entity’s individual indicator and the production frontier, indicating its efficiency. It is widely considered that the well-being of a country’s people stems from its productive base, which is characterized by capital assets and social infrastructures. Thus, the productive base can be considered the input used to produce well-being, which is reflected by individual indicators. Therefore, when we apply BOD to aggregate individual well-being indicators across countries, we implicitly assume that all countries have the same productive base, as BOD addresses only the output and neglects the input. This inaccurate assumption leads to a distorted performance measure. Data envelopment analysis (DEA), in which BOD has its roots, is a tool to measure the efficiency of each entity by allowing for differences in inputs as well as outputs across entities. DEA also measures efficiency by using the distance to the production frontier; however, unlike BOD, DEA constructs the production frontier more accurately by utilizing the information of inputs as well as outputs, leading to a better performance measure. We apply DEA to aggregate 11 individual well-being indicators into a composite indicator using the World Bank’s estimates of each country’s productive base. The composite indicator based on BOD is distributed similarly to and is highly correlated with the existing Human Development Indicator (HDI). It is also positively correlated with GDP per capita. On the other hand, we show that the composite indicator based on DEA is negatively correlated with HDI as well as GDP per capita.


Composite indicators Better Life Index Data envelopment analysis Benefit of the doubt approach 



This research was funded by the Ministry of the Environment, Government of Japan. The results and conclusions of this paper do not necessarily represent the views of the funding agency. I am grateful to Jiro Nemoto, Shunsuke Managi and Shigemi Kamo for their helpful comments and suggestions. I also wish to thank seminar participants in the annual meetings of the Society of Environmental Economics and Policy Studies, Tohoku University, September 2012 and the Japanese Economic Association, Kyushu Sangyo University, October, 2012 as well as Okayama University. All remaining errors are the author’s responsibility.


  1. Arrow, K., Dasgupta, P., Goulder, L., Daily, G., Ehrlich, P., Heal, G., et al. (2004). Are we consuming too much? Journal of Economic Perspectives, 18(3), 147–172.CrossRefGoogle Scholar
  2. Bogetoft, P., & Otto, L. (2011). Benchmarking with DEA, SFA, and R. New York: Springer.CrossRefGoogle Scholar
  3. Bogetoft, P. & Otto, L. (2012). Benchmarking package. Technical Report, R.Google Scholar
  4. Charnes, A., Cooper, W. W., & Rhodes, E. (1978). Measuring the efficiency of decision making units. European Journal of Operational Research, 2(6), 429–444.CrossRefGoogle Scholar
  5. Cherchye, L., Moesen, W., Rogge, N., & Van Puyenbroeck, T. (2007). An introduction to ‘benefit of the doubt’ composite indicators. Social Indicators Research, 82(1), 111–145.CrossRefGoogle Scholar
  6. Cherchye, L., Moesen, W., & Van 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
  7. Dasgupta, P. (2001). Human well-being and the natural environment. Oxford: Oxford University Press.CrossRefGoogle Scholar
  8. Despotis, D. K. (2005a). A reassessment of the human development index via data envelopment analysis. Journal of the Operational Research Society, 56(8), 969–980.CrossRefGoogle Scholar
  9. Despotis, D. K. (2005b). Measuring human development via data envelopment analysis: the case of Asia and the Pacific. Omega, 33(5), 385–390.CrossRefGoogle Scholar
  10. Fleurbaey, M., & Gaulier, G. (2009). International comparisons of living standards by equivalent incomes. Scandinavian Journal of Economics, 111(3), 597–624.CrossRefGoogle Scholar
  11. Jones, C. I. & Klenow, P. J. (2010). Beyond GDP? Welfare across countries and time. NBER Working Paper, WP16352.Google Scholar
  12. Kunte, A., Hamilton, K., Dixon, J. & Clemens, M. (1998). Estimating national wealth: Methodology and results. Environment Department, World Bank.Google Scholar
  13. 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
  14. Mahlberg, B. & Obersteiner, M. (2001). Remeasuring the HDI by data envelopement analysis. International Institute for Applied Systems Analysis Interim Report, 01–069.Google Scholar
  15. Organization for Economic Cooperation and Development. (2008). Handbook on constructing composite indicators: Methodology and user guide. Paris: OECD Publishing.Google Scholar
  16. Organization for Economic Cooperation and Development. (2011). How’s life?: Measuring well-being. Paris: OECD Publishing.Google Scholar
  17. Schokkaert, E. (2007). Capabilities and satisfaction with life. Journal of Human Development, 8(3), 415–430.CrossRefGoogle Scholar
  18. Stiglitz, J. E., Sen, A. & Fitoussi, J.-P. (2009). Report by the commission on the measurement of economic performance and social progress. Available at:
  19. United Nations Development Program. (1990). Human development report 1990: Concept and measurement of human development. New York: Oxford University Press.Google Scholar
  20. World Bank (1997). Expanding the measure of wealth: indicators of environmentally sustainable development. Environmentally Sustainable Development Studies and Monographs Series No. 17. Washington, DC: World Bank.Google Scholar
  21. World Bank. (2006). Where is the wealth of nations?: Measuring capital for the 21st century. Washington, DC: World Bank Publications.Google Scholar
  22. World Bank. (2011). The changing wealth of nations: Measuring sustainable development in the new millennium. Washington, DC: World Bank Publications.Google Scholar
  23. Zaim, O., Färe, R., & Grosskopf, S. (2001). An economic approach to achievement and improvement indexes. Social Indicators Research, 56(June), 91–118.CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media Dordrecht 2013

Authors and Affiliations

  1. 1.Faculty of EconomicsRyukoku UniversityKyotoJapan

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