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Even though poverty is a social and economic phenomenon, it is nonetheless important to investigate the multidimensional character of poverty in the Global South. Hence, this study is an effort to determine the multidimensional poverty status in rural Bangladesh, decompose poverty, and investigate risk factors for poverty. To achieve the goal, primary data were collected from 350 rural farm households through the random sampling technique. The Alkire-Foster (A-F) method of multidimensional poverty estimation was applied considering four dimensions of deprivation. It was found that 11% of rural households were multidimensionally poor, whereas the multidimensional headcount of poor was 23% and their average intensity of poverty was 47%. When their poverty was decomposed, it was evidenced that the standard of living dimension has the highest contribution among the four dimensions to poverty. The result from 'indicator-wise decomposition' found that job seeking was the highest contributing indicator to poverty followed by school dropout and type of cooking fuel. A binomial logit regression model was used to explore the risk factors of poverty. Regression results revealed that larger household size has significantly increased the risk while, more income-earning persons, ownership of large livestock, and crop farming could significantly reduce the risk of poverty in rural farm households. The study findings could be used to implement a sustainable poverty reduction strategy. Also, the contextual factors need to be considered in poverty estimation and policy intervention should be implemented in such a way where the contribution of the dimensions and indicators of poverty get prime focus.
Haque et al. (Thu,) studied this question.