Multidimensional Poverty: Complementary Measure to Absolute and Relative Poverty

Muhammad Hanif Othman, Zouhair Mohd Rosli and Mohd Hilal Muhammad
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Muhammad Hanif Othman: Faculty of Business and Management, Universiti Teknologi MARA (UiTM) Kedah, 08400 Merbok Kedah Malaysia.
Zouhair Mohd Rosli: DM Analytics Sdn Bhd
Mohd Hilal Muhammad: Faculty of Computer and Mathematical Sciences, Universiti Teknologi MARA (UiTM) Kedah, 08400 Merbok Kedah Malaysia.

International Journal of Research and Innovation in Social Science, 2024, vol. 8, issue 9, 3838-3846

Abstract: Poverty is a complex issue that involves more than just income levels, affecting various aspects of life such as health, education, and living conditions. The ongoing discussion about how to measure poverty, whether through absolute or relative terms, reflects the challenges in assessing it. Absolute poverty is based on a set standard that focuses on meeting basic needs for survival, while relative poverty looks at income disparities within a society. This study explores existing research on multidimensional poverty and examines the debate between absolute and relative poverty measures, considering their respective advantages and disadvantages. A notable conclusion from the research is that multidimensional poverty indices (MPIs), like the Multidimensional Poverty Index, provide a broad view of deprivation by including multiple factors. MPIs help policymakers design more targeted interventions in areas such as education, healthcare, and living standards. However, absolute poverty measures, such as the World Bank’s $1.90-per-day threshold, are still essential for tracking extreme poverty in developing nations, offering a clear benchmark for international comparisons. In contrast, relative poverty measures are particularly relevant in wealthier nations, where inequality and social exclusion are more prominent factors in poverty. This study highlights gaps in how these different approaches are integrated and calls for further research to improve models that address both absolute and relative poverty. The findings suggest that combining multidimensional, absolute, and relative poverty measures is important for fully understanding poverty and creating effective strategies to reduce it, adapted to the needs of specific regions and contexts.

Date: 2024
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