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Copula-based measurement of dependence between dimensions of well-being

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  • Koen DECANCQ

Abstract

Well-being consists of many dimensions such as income, health and education. A society exhibits greater dependence between its dimensions of well-being when the positions of the individuals in the different dimensions are more aligned or correlated. Differences in dependence may lead to very different societies, even when the dimension-wise distributions are identical. I propose to use a copula-based framework to order societies with respect to their dependence. A class of measures of dependence is derived to which the multidimensional rank correlation coefficient belongs. I illustrate the usefulness of the approach by showing that Russian dependence between three dimensions of well-being has increased significantly between 1995 and 2003. Unfortunately, the aspect of dependence is missed by all composite well-being measures based on dimension-specific summary statistics such as the popular Human Development Index (HDI).

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  • Koen DECANCQ, 2009. "Copula-based measurement of dependence between dimensions of well-being," Working Papers of Department of Economics, Leuven ces09.24, KU Leuven, Faculty of Economics and Business (FEB), Department of Economics, Leuven.
  • Handle: RePEc:ete:ceswps:ces09.24
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    Cited by:

    1. Koen Decancq & Marc Fleurbaey & Erik Schokkaert, 2017. "Wellbeing Inequality and Preference Heterogeneity," Economica, London School of Economics and Political Science, vol. 84(334), pages 210-238, April.
    2. Kateryna Tkach & Chiara Gigliarano, 2018. "Multidimensional poverty measurement: dependence between well-being dimensions using copula function," RIEDS - Rivista Italiana di Economia, Demografia e Statistica - The Italian Journal of Economic, Demographic and Statistical Studies, SIEDS Societa' Italiana di Economia Demografia e Statistica, vol. 72(3), pages 89-100, July-Sept.
    3. Maria Ana Lugo & Koen Decancq, 2009. "Measuring Inequality of Well-Being with a Correlation-Sensitive Multidimensional Gini Index," Economics Series Working Papers 459, University of Oxford, Department of Economics.
    4. Koen Decancq & Annemie Nys, 2021. "Growing Up In A Poor Household In Belgium: A Rank-Based Multidimensional Perspective On Child Well-Being," Working Papers 2104, Herman Deleeck Centre for Social Policy, University of Antwerp.
    5. Iryna Kyzyma & Alessio Fusco & Philippe Van Kerm, 2022. "Distributional Change: Assessing the Contribution of Household Income Sources," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 84(1), pages 158-184, February.
    6. 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.
    7. Giovanna Scarcilli, 2024. "Studying the evolution of cumulative deprivation among European countries with a copula-based approach," Working Papers 667, ECINEQ, Society for the Study of Economic Inequality.
    8. Rolf Aaberge & Anthony B. Atkinson & Sebastian Königs, 2018. "From classes to copulas: wages, capital, and top incomes," The Journal of Economic Inequality, Springer;Society for the Study of Economic Inequality, vol. 16(2), pages 295-320, June.
    9. Francisco H. G. Ferreira & Maria Ana Lugo, 2013. "Multidimensional Poverty Analysis: Looking for a Middle Ground," The World Bank Research Observer, World Bank, vol. 28(2), pages 220-235, August.
    10. Maike Hohberg & Francesco Donat & Giampiero Marra & Thomas Kneib, 2021. "Beyond unidimensional poverty analysis using distributional copula models for mixed ordered‐continuous outcomes," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 70(5), pages 1365-1390, November.
    11. Silvia Terzi & Luca Moroni, 2022. "Local Concordance and Some Applications," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 161(2), pages 457-470, June.
    12. Koen Decancq, 2020. "Measuring cumulative deprivation and affluence based on the diagonal dependence diagram," METRON, Springer;Sapienza Università di Roma, vol. 78(2), pages 103-117, August.
    13. Koen Decancq, 2023. "Cumulative deprivation: identification and aggregation," Chapters, in: Udaya R. Wagle (ed.), Research Handbook on Poverty and Inequality, chapter 4, pages 52-67, Edward Elgar Publishing.
    14. Lidia Ceriani & Chiara Gigliarano, 2020. "Multidimensional Well-Being: A Bayesian Networks Approach," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 152(1), pages 237-263, November.
    15. Koen Decancq, 2020. "Bad news does not come alone: Cumulative deprivation in Belgium," Working Papers 2007, Herman Deleeck Centre for Social Policy, University of Antwerp.
    16. Koen Decancq & Erik Schokkaert, 2016. "Beyond GDP: Using Equivalent Incomes to Measure Well-Being in Europe," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 126(1), pages 21-55, March.
    17. Suman Seth, 2013. "A class of distribution and association sensitive multidimensional welfare indices," The Journal of Economic Inequality, Springer;Society for the Study of Economic Inequality, vol. 11(2), pages 133-162, June.
    18. César Garcia-Gomez & Ana Pérez & Mercedes Prieto-Alaiz, 2022. "The evolution of poverty in the EU-28: a further look based on multivariate tail dependence," Working Papers 605, ECINEQ, Society for the Study of Economic Inequality.
    19. Kateryna Tkach & Chiara Gigliarano, 2022. "Multidimensional Poverty Index with Dependence-Based Weights," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 161(2), pages 843-872, June.
    20. Martyna Kobus & Radoslaw Kurek, 2017. "Copula-based measurement of interdependence for discrete distributions," Working Papers 431, ECINEQ, Society for the Study of Economic Inequality.
    21. Kobus, Martyna & Kurek, Radosław, 2018. "Copula-based measurement of interdependence for discrete distributions," Journal of Mathematical Economics, Elsevier, vol. 79(C), pages 27-39.
    22. Antonella D’agostino & Giovanni De Luca & Dominique Guégan, 2023. "Estimating Lower Tail Dependence Between Pairs of Poverty Dimensions in Europe," Review of Income and Wealth, International Association for Research in Income and Wealth, vol. 69(2), pages 419-442, June.
    23. César García‐Gómez & Ana Pérez & Mercedes Prieto‐Alaiz, 2021. "Copula‐based analysis of multivariate dependence patterns between dimensions of poverty in Europe," Review of Income and Wealth, International Association for Research in Income and Wealth, vol. 67(1), pages 165-195, March.
    24. Aristidis K. Nikoloulopoulos & Peter G. Moffatt, 2019. "Coupling Couples With Copulas: Analysis Of Assortative Matching On Risk Attitude," Economic Inquiry, Western Economic Association International, vol. 57(1), pages 654-666, January.

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    More about this item

    Keywords

    copula; complex inequality; concordance; HDI; multidimensional inequality; Russia; well-being.;
    All these keywords.

    JEL classification:

    • D31 - Microeconomics - - Distribution - - - Personal Income and Wealth Distribution
    • D63 - Microeconomics - - Welfare Economics - - - Equity, Justice, Inequality, and Other Normative Criteria and Measurement
    • I31 - Health, Education, and Welfare - - Welfare, Well-Being, and Poverty - - - General Welfare, Well-Being
    • O50 - Economic Development, Innovation, Technological Change, and Growth - - Economywide Country Studies - - - General

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