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Towards a Distribution-Sensitive Better Life Index: Design, Data and Implementation

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  • Koen Decancq

    (University of Antwerp)

Abstract

The Better Life Index was introduced by the OECD as a tool to chart the multi-dimensional well-being of OECD member countries, Brazil and the Russian Federation. However, the Better Life Index relies only on aggregate country-level indicators, and hence is insensitive to how multi-dimensional well-being outcomes are distributed within countries. This paper discusses how a distribution-sensitive Better Life Index could be designed and implemented. Based on five concrete recommendations for the design of the index, a family of indices is suggested. These indices are shown to be decomposable in interpretable building blocks. While a rich and comprehensive micro-level data set is necessary to implement the distribution-sensitive Better Life Index, no such data set is currently available for all OECD member countries. The paper proposes a ‘synthetic’ data set that relies on information about macro-level indicators and micro-level data from the Gallup World Poll. The implementation of the distribution-sensitive Better Life Index is illustrated with this synthetic data set. While the small sample size and other survey features of the Gallup World Poll imply a number of potential biases, illustrative calculations based on this synthetic data set indicates that, when taking distribution into account, Nordic countries are top-ranked whereas Greece, the Russian Federation and Turkey occupy the bottom positions. The results indicate sizeable losses due to multi-dimensional inequality for OECD member countries. Moreover, there are large differences in the level and composition of multi-dimensional inequality. L’Indicateur du vivre mieux a été lancé par l’OCDE dans le but de cartographier les multiples dimensions du bien-être dans les pays membres de l’OCDE, le Brasil et la Fédération de Russie. Il ne repose toutefois que sur des mesures agrégées à l’échelle nationale et ne permet donc pas de représenter comment se répartissent les différentes dimensions du bien-être à l’intérieur des pays. Ce document étudie la façon dont un Indicateur du vivre mieux tenant compte de cette répartition pourrait être élaboré et appliqué. À partir de cinq recommandations concrètes sur la conception de l’indicateur, un ensemble d’indices est proposé. Ces indices peuvent être décomposés en éléments interprétables. Un ensemble de microdonnées dense et exhaustif est nécessaire pour construire un indicateur tenant compte de la répartition des dimensions du bien-être, mais ces données ne sont pas encore disponibles pour l’ensemble des pays membres de l’OCDE. Ce document propose donc un ensemble de données « synthétique » qui s’appuie sur des informations relatives aux macro-indicateurs et aux micro-données de l’enquête Gallup World Poll. Même si l’étroitesse des échantillons et autres faiblesses méthodologiques de l’enquête Gallup World Poll peuvent entrainer des risques de biais, des mesures basées sur ces données « synthétiques » indiquent que, lorsqu’on tient compte de la répartition des dimensions du bien-être, les pays nordiques arrivent en tête, tandis que la Grèce, la Fédération de Russie et la Turquie occupent les derniers rangs. Les résultats montrent des pertes importantes dues aux inégalités dans la distribution des différentes dimensions du bien-être entre les pays membres de l’OCDE. En outre, on observe de grandes différences de niveau et de composition au regard des disparités multidimensionnelles.

Suggested Citation

  • Koen Decancq, 2015. "Towards a Distribution-Sensitive Better Life Index: Design, Data and Implementation," OECD Statistics Working Papers 2015/7, OECD Publishing.
  • Handle: RePEc:oec:stdaaa:2015/7-en
    DOI: 10.1787/5jrqppx9xh8q-en
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    Cited by:

    1. Koen Decancq, 2017. "Measuring Multidimensional Inequality in the OECD Member Countries with a Distribution-Sensitive Better Life Index," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 131(3), pages 1057-1086, April.
    2. Włodzimierz Okrasa & Dominik Rozkrut, 2018. "The Wellbeing Effect Of Community Development. Some Measurement And Modeling Issues," Statistics in Transition New Series, Polish Statistical Association, vol. 19(2), pages 359-376, June.

    More about this item

    Keywords

    well-being;

    JEL classification:

    • C43 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Index Numbers and Aggregation
    • I31 - Health, Education, and Welfare - - Welfare, Well-Being, and Poverty - - - General Welfare, Well-Being
    • O1 - Economic Development, Innovation, Technological Change, and Growth - - Economic Development

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