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Abstract While it is widely accepted that poverty is multidimensional, debates over how it is best measured continue. This paper examines whether different measurements of poverty provide different implications from a policy perspective. Using probit models applied to household level data it examines the correlates of both income poverty and multidimensional poverty in the context of Sri Lanka. Results suggest that the two measures of poverty share many of the same correlates. Age of the household head, education, marital status, employment, access to agricultural land and the receipt of remittances are important across the two poverty measures. However, there are important differences with respect to the signs of the coefficients on household size and ethnicity variables. Further, the magnitude of the associations of independent variables with poverty vary considerably across the two measures. Policy recommendations are provided.
Deyshappriya et al. (Mon,) studied this question.