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Testing for the implicit weights of the dimensions of the Human Development Index using stochastic dominance

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  • Pinar, Mehmet
  • Stengos, Thanasis
  • Topaloglou, Nikolas

Abstract

In 2010, United Nations’ Development Programme changed the indicators used to obtain education and income indices in the Human Development Index (HDI). In this paper, we use the Stochastic Dominance Efficiency methodology to evaluate the implicit weights of the dimensions used in the new measurement of the HDI. We find, contrary to the earlier literature, that the implicit weight attached to the education dimension is relatively low suggesting that it is relatively harder to achieve high scores in this dimension compared to other dimensions.

Suggested Citation

  • Pinar, Mehmet & Stengos, Thanasis & Topaloglou, Nikolas, 2017. "Testing for the implicit weights of the dimensions of the Human Development Index using stochastic dominance," Economics Letters, Elsevier, vol. 161(C), pages 38-42.
    • Handle: RePEc:eee:ecolet:v:161:y:2017:i:c:p:38-42
    DOI: 10.1016/j.econlet.2017.09.023
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    References listed on IDEAS

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    1. Oliver Linton & Esfandiar Maasoumi & Yoon-Jae Whang, 2005. "Consistent Testing for Stochastic Dominance under General Sampling Schemes," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 72(3), pages 735-765.
    2. Mehmet Pinar & Thanasis Stengos & Nikolas Topaloglou, 2013. "Measuring human development: a stochastic dominance approach," Journal of Economic Growth, Springer, vol. 18(1), pages 69-108, March.
    3. Ravallion, Martin, 2012. "Troubling tradeoffs in the Human Development Index," Journal of Development Economics, Elsevier, vol. 99(2), pages 201-209.
    4. Alkire, Sabina & Santos, Maria Emma, 2014. "Measuring Acute Poverty in the Developing World: Robustness and Scope of the Multidimensional Poverty Index," World Development, Elsevier, vol. 59(C), pages 251-274.
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    Cited by:

    1. Qiuxia Yang, 2020. "Fiscal Transparency and Public Service Quality Association: Evidence from 12 Coastal Provinces and Cities of China," JRFM, MDPI, vol. 14(1), pages 1-14, December.
    2. Mehmet Pinar, 2022. "Choquet-Integral Aggregation Method to Aggregate Social Indicators to Account for Interactions: An Application to the Human Development Index," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 159(1), pages 1-53, January.
    3. Omrani, Hashem & Alizadeh, Arash & Amini, Mohaddeseh, 2020. "A new approach based on BWM and MULTIMOORA methods for calculating semi-human development index: An application for provinces of Iran," Socio-Economic Planning Sciences, Elsevier, vol. 70(C).
    4. Umberto Lucia & Debora Fino & Giulia Grisolia, 2022. "A thermoeconomic indicator for the sustainable development with social considerations," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 24(2), pages 2022-2036, February.
    5. Mehmet Pinar, 2019. "Multidimensional Well-Being and Inequality Across the European Regions with Alternative Interactions Between the Well-Being Dimensions," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 144(1), pages 31-72, July.
    6. Umberto Lucia & Giulia Grisolia, 2021. "The Gouy-Stodola Theorem—From Irreversibility to Sustainability—The Thermodynamic Human Development Index," Sustainability, MDPI, vol. 13(7), pages 1-13, April.
    7. Mehmet Pinar & Thanasis Stengos & Nikolas Topaloglou, 2022. "Stochastic dominance spanning and augmenting the human development index with institutional quality," Annals of Operations Research, Springer, vol. 315(1), pages 341-369, August.
    8. Tahsin Mehdi, 2019. "Stochastic Dominance Approach to OECD’s Better Life Index," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 143(3), pages 917-954, June.
    9. Wang, Hanjie & Feil, Jan-Henning & Yu, Xiaohua, 2023. "Let the data speak about the cut-off values for multidimensional index: Classification of human development index with machine learning," Socio-Economic Planning Sciences, Elsevier, vol. 87(PA).
    10. Panagiotis Ravanos & Giannis Karagiannis, 2021. "A VEA Benefit-of-the-Doubt Model for the HDI," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 155(1), pages 27-46, May.
    11. Giovanni Bernardo & Irene Brunetti & Mehmet Pinar & Thanasis Stengos, 2021. "Measuring the presence of organized crime across Italian provinces: a sensitivity analysis," European Journal of Law and Economics, Springer, vol. 51(1), pages 31-95, February.
    12. Pinar, Mehmet & Stengos, Thanasis & Topaloglou, Nikolas, 2020. "On the construction of a feasible range of multidimensional poverty under benchmark weight uncertainty," European Journal of Operational Research, Elsevier, vol. 281(2), pages 415-427.
    13. Stephen Morse, 2020. "To Rank or Not to Rank with Indices? That Is the Question," Sustainability, MDPI, vol. 12(14), pages 1-20, July.
    14. Tahsin Mehdi, 2019. "Stochastic Dominance Approach to Measuring Child Development," Child Indicators Research, Springer;The International Society of Child Indicators (ISCI), vol. 12(5), pages 1567-1588, October.

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    More about this item

    Keywords

    Well-being; Human development; Composite indices; Nonparametric stochastic dominance;
    All these keywords.

    JEL classification:

    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • I31 - Health, Education, and Welfare - - Welfare, Well-Being, and Poverty - - - General Welfare, Well-Being
    • O15 - Economic Development, Innovation, Technological Change, and Growth - - Economic Development - - - Economic Development: Human Resources; Human Development; Income Distribution; Migration

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