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Stochastic Dominance Approach to OECD’s Better Life Index

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  • Tahsin Mehdi

    (Ryerson University)

Abstract

Ever since the inception of OECD’s Better Life Index in 2011, a string of literature have emerged offering different aggregation procedures for the 11 dimensions of the index encompassing the broad categories of material living standards and quality of life. What is the most optimistic weighting scheme that allows more countries to achieve better measured well-being outcomes? What is the most pessimistic weighting scheme that worsens outcomes for more countries? Stochastic dominance efficiency is a data driven aggregation method that allows us to answer such questions which may be beneficial to policy makers and researchers. We offer rankings of countries across dimensions as well as rankings based on a single composite index aggregating all dimensional indicators. This type of analysis not only presents an opportunity to examine the sensitivity associated with re-weighting indicators, but this approach also reveals which indicators are driving overall improvement in measured well-being and which ones are hindering it. We find that the worst-case scenario rankings are generally more correlated with the equal-weighting scheme. And the best-case scenario weights offer a far more equal distribution of achievements across countries.

Suggested Citation

  • Tahsin Mehdi, 2019. "Stochastic Dominance Approach to OECD’s Better Life Index," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 143(3), pages 917-954, June.
  • Handle: RePEc:spr:soinre:v:143:y:2019:i:3:d:10.1007_s11205-018-2014-0
    DOI: 10.1007/s11205-018-2014-0
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    2. Pinar, Mehmet & Stengos, Thanasis & Topaloglou, Nikolas, 2020. "On the construction of a feasible range of multidimensional poverty under benchmark weight uncertainty," European Journal of Operational Research, Elsevier, vol. 281(2), pages 415-427.
    3. Ilaria Benedetti & Gianni Betti & Federico Crescenzi, 2020. "Measuring Child Poverty and Its Uncertainty: A Case Study of 33 European Countries," Sustainability, MDPI, vol. 12(19), pages 1-12, October.

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