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Measurement of Social Welfare and Inequality in Presence of Partially-ordered Variables

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Abstract
We address the question of the measurement of social welfare and inequalities in the context of partially-ordered health variables. We propose a general framework based on the assumption that the distribution of well-being states forms an m-dimensional Boolean lattice. To this end, the distribution of well-being states is constructed based on the prevalence of a finite number of illnesses where each state represents the number of illnesses an individual may suffer from. The implementation of the framework involves breaking down the Boolean lattice into a set of linear extensions where all health states become fully ordered. The linear extensions account for all possible ordering of the health states based on the depth of health problems (i.e., the severity of health conditions). Having constructed these linear extensions, we then proceed on ranking distributions in terms of welfare by applying appropriate dominance criteria and employ aggregate metrics to provide a numerical representation of the social welfare and inequality associated with each distribution. An illustrative application of the methodology is provided.

Suggested Citation

  • Mohammad Abu-Zaineh & Sameera Awawda, 2022. "Measurement of Social Welfare and Inequality in Presence of Partially-ordered Variables," AMSE Working Papers 2231, Aix-Marseille School of Economics, France.
    • Handle: RePEc:aim:wpaimx:2231
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    References listed on IDEAS

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    1. Caulier, Jean-François & Mauleon, Ana & Vannetelbosch, Vincent, 2015. "Allocation rules for coalitional network games," Mathematical Social Sciences, Elsevier, vol. 78(C), pages 80-88.
    2. Abul Naga, Ramses H. & Yalcin, Tarik, 2008. "Inequality measurement for ordered response health data," Journal of Health Economics, Elsevier, vol. 27(6), pages 1614-1625, December.
    3. Frank A. Cowell & Emmanuel Flachaire, 2017. "Inequality with Ordinal Data," Economica, London School of Economics and Political Science, vol. 84(334), pages 290-321, April.
    4. Makdissi, Paul & Yazbeck, Myra, 2014. "Measuring socioeconomic health inequalities in presence of multiple categorical information," Journal of Health Economics, Elsevier, vol. 34(C), pages 84-95.
    5. Paul Makdissi & Myra Yazbeck, 2017. "Robust rankings of socioeconomic health inequality using a categorical variable," Health Economics, John Wiley & Sons, Ltd., vol. 26(9), pages 1132-1145, September.
    Full references (including those not matched with items on IDEAS)

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    More about this item

    Keywords

    boolean lattice; Hammond dominance; ordinal inequality; partially-ordered variables; stochastic dominance; welfare function;
    All these keywords.

    JEL classification:

    • D63 - Microeconomics - - Welfare Economics - - - Equity, Justice, Inequality, and Other Normative Criteria and Measurement
    • I14 - Health, Education, and Welfare - - Health - - - Health and Inequality
    • I15 - Health, Education, and Welfare - - Health - - - Health and Economic Development
    • O5 - Economic Development, Innovation, Technological Change, and Growth - - Economywide Country Studies

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