IDEAS home Printed from https://ideas.repec.org/p/ete/ceswps/ces09.24.html
   My bibliography  Save this paper

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

Author

Listed:
  • 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).

Suggested Citation

  • 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
    as

    Download full text from publisher

    File URL: https://lirias.kuleuven.be/bitstream/123456789/253173/1/DPS0924.pdf
    Download Restriction: no
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. Inna Blam & Sergey Kovalev, 2006. "Spontaneous commercialisation, inequality and the contradictions of compulsory medical insurance in transitional Russia," Journal of International Development, John Wiley & Sons, Ltd., vol. 18(3), pages 407-423.
    2. Schmid, Friedrich & Schmidt, Rafael, 2007. "Multivariate conditional versions of Spearman's rho and related measures of tail dependence," Journal of Multivariate Analysis, Elsevier, vol. 98(6), pages 1123-1140, July.
    3. Stephane Bonhomme & Jean-Marc Robin, 2006. "Modeling Individual Earnings Trajectories Using Copulas: France, 1990–2002," Contributions to Economic Analysis, in: Structural Models of Wage and Employment Dynamics, pages 441-478, Emerald Group Publishing Limited.
    4. Michael Lokshin & Martin Ravallion, 2008. "Testing for an economic gradient in health status using subjective data," Health Economics, John Wiley & Sons, Ltd., vol. 17(11), pages 1237-1259.
    5. Cebrián, Ana C. & Denuit, Michel & Scaillet, Olivier, 2004. "Testing for Concordance Ordering," ASTIN Bulletin, Cambridge University Press, vol. 34(1), pages 151-173, May.
    6. A. B. Atkinson & F. Bourguignon, 1982. "The Comparison of Multi-Dimensioned Distributions of Economic Status," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 49(2), pages 183-201.
    7. Joe, Harry, 1990. "Multivariate concordance," Journal of Multivariate Analysis, Elsevier, vol. 35(1), pages 12-30, October.
    8. Galina Besstremyannaya, 2007. "Out-of-Pocket Health Care Expenditures by Russian Consumers with Different Health Status," Transition Studies Review, Springer;Central Eastern European University Network (CEEUN), vol. 14(2), pages 331-338, November.
    9. Marco Scarsini, 1984. "On measures of concordance," Post-Print hal-00542380, HAL.
    10. M. Taylor, 2007. "Multivariate measures of concordance," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 59(4), pages 789-806, December.
    11. Koen DECANCQ, 2010. "Copula-based orderings of multivariate dependence," Working Papers of Department of Economics, Leuven ces10.08, KU Leuven, Faculty of Economics and Business (FEB), Department of Economics, Leuven.
    12. Marc Fleurbaey & Alain Trannoy, 2003. "The impossibility of a Paretian egalitarian," Social Choice and Welfare, Springer;The Society for Social Choice and Welfare, vol. 21(2), pages 243-263, October.
    13. Colangelo, Antonio & Scarsini, Marco & Shaked, Moshe, 2006. "Some positive dependence stochastic orders," Journal of Multivariate Analysis, Elsevier, vol. 97(1), pages 46-78, January.
    14. Moulin, H & Thomson, W, 1995. "Axiomatic Analysis of Resource Allocation," RCER Working Papers 400, University of Rochester - Center for Economic Research (RCER).
    15. Valentino Dardanoni & Peter Lambert, 2001. "Horizontal inequity comparisons," Social Choice and Welfare, Springer;The Society for Social Choice and Welfare, vol. 18(4), pages 799-816.
    16. Doorslaer, Eddy van & Jones, Andrew M., 2003. "Inequalities in self-reported health: validation of a new approach to measurement," Journal of Health Economics, Elsevier, vol. 22(1), pages 61-87, January.
    17. Larry G. Epstein & Stephen M. Tanny, 1980. "Increasing Generalized Correlation: A Definition and Some Economic Consequences," Canadian Journal of Economics, Canadian Economics Association, vol. 13(1), pages 16-34, February.
    18. Henning Bunzel & Bent J. Christensen & Georges R. Neumann & Jean-Marc Robin, 2006. "Structural Models of Wage and Employment Dynamics," Post-Print hal-00308804, HAL.
    19. repec:bla:econom:v:70:y:2003:i:278:p:197-221 is not listed on IDEAS
    20. Denuit, Michel & Lambert, Philippe, 2005. "Constraints on concordance measures in bivariate discrete data," Journal of Multivariate Analysis, Elsevier, vol. 93(1), pages 40-57, March.
    21. Michael Lokshin & Martin Ravallion, 2008. "Testing for an economic gradient in health status using subjective data," Health Economics, John Wiley & Sons, Ltd., vol. 17(11), pages 1237-1259, November.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Koen Decancq & María Ana Lugo, 2009. "Measuring inequality of well-being with a correlation-sensitive multidimensional Gini index," Working Papers 124, ECINEQ, Society for the Study of Economic Inequality.
    2. 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.
    3. 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.
    4. Gajdos, Thibault & Weymark, John A., 2012. "Introduction to inequality and risk," Journal of Economic Theory, Elsevier, vol. 147(4), pages 1313-1330.
    5. Koen Decancq & Marc Fleurbaey & François Maniquet, 2019. "Multidimensional poverty measurement with individual preferences," The Journal of Economic Inequality, Springer;Society for the Study of Economic Inequality, vol. 17(1), pages 29-49, March.
    6. Meyer, Margaret & Strulovici, Bruno, 2012. "Increasing interdependence of multivariate distributions," Journal of Economic Theory, Elsevier, vol. 147(4), pages 1460-1489.
    7. Ren Mu, 2014. "Regional Disparities In Self‐Reported Health: Evidence From Chinese Older Adults," Health Economics, John Wiley & Sons, Ltd., vol. 23(5), pages 529-549, May.
    8. Ferreira Helena & Ferreira Marta, 2020. "Multivariate medial correlation with applications," Dependence Modeling, De Gruyter, vol. 8(1), pages 361-372, January.
    9. Decancq, Koen, 2012. "Elementary multivariate rearrangements and stochastic dominance on a Fréchet class," Journal of Economic Theory, Elsevier, vol. 147(4), pages 1450-1459.
    10. Asis Kumar Banerjee, 2018. "Multidimensional Indices with Data-driven Dimensional Weights: A Multidimensional Coefficient of Variation," Arthaniti: Journal of Economic Theory and Practice, , vol. 17(2), pages 140-156, December.
    11. Ferreira Helena & Ferreira Marta, 2020. "Multivariate medial correlation with applications," Dependence Modeling, De Gruyter, vol. 8(1), pages 361-372, January.
    12. Gaißer, Sandra & Ruppert, Martin & Schmid, Friedrich, 2010. "A multivariate version of Hoeffding's Phi-Square," Journal of Multivariate Analysis, Elsevier, vol. 101(10), pages 2571-2586, November.
    13. Kobus, Martyna & Kurek, Radosław, 2018. "Copula-based measurement of interdependence for discrete distributions," Journal of Mathematical Economics, Elsevier, vol. 79(C), pages 27-39.
    14. Benoît Tarroux, 2015. "Comparing two-dimensional distributions: a questionnaire-experimental approach," Social Choice and Welfare, Springer;The Society for Social Choice and Welfare, vol. 44(1), pages 87-108, January.
    15. Silvia Terzi & Luca Moroni, 2014. "A suggestion for a multivariate concordance coefficient," Departmental Working Papers of Economics - University 'Roma Tre' 0189, Department of Economics - University Roma Tre.
    16. Mhamed Mesfioui & Julien Trufin, 2022. "Bounds on Multivariate Kendall’s Tau and Spearman’s Rho for Zero-Inflated Continuous Variables and their Application to Insurance," Methodology and Computing in Applied Probability, Springer, vol. 24(2), pages 1051-1059, June.
    17. Gijbels, Irène & Kika, Vojtěch & Omelka, Marek, 2021. "On the specification of multivariate association measures and their behaviour with increasing dimension," Journal of Multivariate Analysis, Elsevier, vol. 182(C).
    18. Oliver Grothe & Fabian Kächele & Friedrich Schmid, 2022. "A multivariate extension of the Lorenz curve based on copulas and a related multivariate Gini coefficient," The Journal of Economic Inequality, Springer;Society for the Study of Economic Inequality, vol. 20(3), pages 727-748, September.
    19. FLEURBAEY, Marc & SCHOKKAERT, Erik, 2011. "Equity in health and health care," LIDAM Discussion Papers CORE 2011026, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    20. Ying Zhang & Chuancun Yin, 2014. "A new multivariate dependence measure based on comonotonicity," Papers 1410.7845, arXiv.org.

    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

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:ete:ceswps:ces09.24. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: library EBIB (email available below). General contact details of provider: https://feb.kuleuven.be/Economics/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.