Targeting Poverty and Developing Sustainable Development Objectives for the United Nation’s Countries using a Systematic Approach Combining DRSA and Multiple Linear Regressions

Jean-Charles Marin, Bryan B-Trudel, K. Zaras, M. Sylla
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引用次数: 1

Abstract

The objectives of this article is to target poverty using Dominance-based Rough Set Approach (DRSA) to help the United Nation’s Countries develop objectives for sustainable development. There are 12 variables divided into 2 perspectives. The first is an economical and technological perspective composed of 6 variables. The second is a sociological and political perspective composed of 6 variables. The methodology proposed classifies all the United Nation’s countries according to three different categories: [A] Developed countries; [B] Emerging economies that need support to acquire category A status; [C] Under Developed countries ranked the lowest and needing special support with regard to the criterion or criteria considered. Using this classification, DRSA provides decision rules to explain the classification and indicating precisely what are the conditions to be part of a higher category. Also, the results indicate what are the conditions to be part of the Under Developed countries category and therefore helps targeting poverty and proposing, at the same time, objectives to improve this classification. Finally, we used Multiple Linear Regressions with selected decision rules to test selected decision rules as the Gross National Income per capita as the dependent variable.
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用DRSA和多元线性回归相结合的系统方法确定联合国国家的贫困和可持续发展目标
本文的目标是使用基于优势的粗糙集方法(DRSA)来帮助联合国各国制定可持续发展目标。12个变量分为2个视角。第一个是由6个变量组成的经济和技术视角。第二个是由6个变量组成的社会学和政治视角。所提出的方法将联合国所有国家分为三类:[A]发达国家;[B]需要支持获得A类地位的新兴经济体;[C]根据所考虑的标准,欠发达国家排名最低,需要特别支持。使用这种分类,DRSA提供了决策规则来解释分类,并精确地指出哪些条件是成为更高类别的一部分。此外,研究结果还指出了哪些条件可以成为欠发达国家类别的一部分,从而有助于确定贫困目标,同时提出改进这一分类的目标。最后,我们使用选择决策规则的多元线性回归来检验选择的决策规则作为人均国民总收入作为因变量。
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