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Multidimensional welfare distributions: empirical application to household panel data from Vietnam

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  • Patricia Justino

Abstract

This article explores the empirical application of theoretical multidimensional welfare distribution analysis techniques to real household welfare distributions. The article operationalizes recent conceptual developments in multidimensional distribution theory and assesses their usefulness for the measurement of multidimensional household inequality. The results strongly highlight the importance of bringing nonmonetary aspects of household welfare into the forefront of inequality analysis. Agreement over the various approaches to the measurement of multidimensional inequality entails, however, nontrivial decisions that may limit the practical usefulness of these measures. We suggest that the use of multidimensional inequality ranges and the application of restrictive dominance criteria to multidimensional welfare distributions may open significant scope for further developments in the empirical analysis of multidimensional inequality.

Suggested Citation

  • Patricia Justino, 2012. "Multidimensional welfare distributions: empirical application to household panel data from Vietnam," Applied Economics, Taylor & Francis Journals, vol. 44(26), pages 3391-3405, September.
    • Handle: RePEc:taf:applec:44:y:2012:i:26:p:3391-3405
    DOI: 10.1080/00036846.2011.577014
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    Cited by:

    1. Alexandre BERTHE, 2016. "Inequalities in the access to water and sanitation services in the North and the Nordeste of Brazil: what lessons for social justice?," Cahiers du GREThA (2007-2019) 2016-07, Groupe de Recherche en Economie Théorique et Appliquée (GREThA).
    2. Philipp Poppitz, 2017. "Can subjective data improve inequality measurement? A multidimensional index of economic inequality," Working Papers 446, ECINEQ, Society for the Study of Economic Inequality.
    3. Phuc Phan & Martin O’Brien, 2019. "Multidimensional Wellbeing Inequality in a Developing Country: A Case Study of Vietnam," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 145(1), pages 157-183, August.
    4. Philipp Poppitz, 2019. "Can Subjective Data Improve the Measurement of Inequality? A Multidimensional Index of Economic Inequality," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 146(3), pages 511-531, December.
    5. Bartels Charlotte & Stockhausen Maximilian, 2017. "Children’s Opportunities in Germany – An Application Using Multidimensional Measures," German Economic Review, De Gruyter, vol. 18(3), pages 327-376, August.
    6. Thi Kim Thanh Bui & Guido Erreygers, 2020. "Multidimensional Inequality in Vietnam, 2002–2012," Economies, MDPI, vol. 8(2), pages 1-31, April.
    7. Foster,James E. & Lokshin,Michael M., 2024. "Multidimensional and Specific Inequalities," Policy Research Working Paper Series 10748, The World Bank.
    8. Long Yang & Haiyang Lu & Meng Li, 2023. "Multidimensional Inequality and Subjective Well-Being in China: A Generalized Ordered Logit Model Analysis," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 165(3), pages 1021-1052, February.
    9. Nicholas Rohde & Ross Guest, 2013. "Multidimensional Racial Inequality in the United States," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 114(2), pages 591-605, November.

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