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A Discriminant Analysis To The Quantification Of Human Development Index Under Economic Inequality

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  • Irina GEORGESCU
  • Ane-Mari ANDRONICEANU
  • Jani KINNUNEN

Abstract

This paper is concerned with a quantitative approach to the determinants of human development index, namely GDP per capita, Net Income GINI index, Wealth GINI index and poverty rate. For year 2018 and 98 world countries we apply multiple discriminant analysis to predict four classes of human development index. The discriminant analysis achieved 83.7% accuracy for the discriminant model with unequal apriori probabilities. One conclusion of the model is that GDP per capita has no discriminating power in the model, overall. Another conclusion is that from three discriminant functions retained, the first one discriminates best.

Suggested Citation

  • Irina GEORGESCU & Ane-Mari ANDRONICEANU & Jani KINNUNEN, 2020. "A Discriminant Analysis To The Quantification Of Human Development Index Under Economic Inequality," Proceedings of the INTERNATIONAL MANAGEMENT CONFERENCE, Faculty of Management, Academy of Economic Studies, Bucharest, Romania, vol. 14(1), pages 1053-1062, November.
    • Handle: RePEc:rom:mancon:v:14:y:2020:i:1:p:1053-1062
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    5. Irina Georgescu & Jani Kinnunen, 2021. "The Digital Effectiveness on Economic Inequality: A Computational Approach," Springer Proceedings in Business and Economics, in: Alina Mihaela Dima & Fabrizio D'Ascenzo (ed.), Business Revolution in a Digital Era, pages 223-239, Springer.
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