2018
DOI: 10.3329/jbau.v16i1.36493
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Factors affecting poverty in rural Bangladesh: An analysis using multilevel modelling

Abstract: Poverty is a multi-faced problem in the developing world and it is much more complex in rural settings. Hence, policy formulation based on national level studies sometimes fails to find remedies of rural poverty. Thus, the present study aims to identify the determinants of poverty in rural Bangladesh using the nationally representative Household Income and Expenditure Survey (HIES) 2010 data. The HIES follows a hierarchical structure hence, two-level random intercept binary logistic regression models were used… Show more

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Cited by 20 publications
(16 citation statements)
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References 23 publications
(23 reference statements)
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“…The education level of the head of the household, household size, the number of dependents in the households and illness are widely recognized as the determinants of overall poverty in Bangladesh. 55 , 56 We found similar determinants of impoverishment for OOP payments in the current study. Khan et al and Mirelman et al found an association between chronic disease and overall poverty in rural Bangladesh.…”
Section: Discussionsupporting
confidence: 83%
“…The education level of the head of the household, household size, the number of dependents in the households and illness are widely recognized as the determinants of overall poverty in Bangladesh. 55 , 56 We found similar determinants of impoverishment for OOP payments in the current study. Khan et al and Mirelman et al found an association between chronic disease and overall poverty in rural Bangladesh.…”
Section: Discussionsupporting
confidence: 83%
“…(2016) and Imam et al. (2018) in the context of Pakistan and Bangladesh, we are using multilevel logistic regression. However, this model is modified with the inclusion of within‐between specifications (Bell and Jones, 2015).…”
Section: Methodsmentioning
confidence: 99%
“…In contrary to this, Metalign (2005); Sepahvand (2009); Mohammed (2017); Imam et al (2018) reported that education has got a significant correlation with poverty where schooling increases household welfare by 8.5% and helps to escape from poverty. As per Ayalneh et al (2003) promoting the household head by one level of education will reduce the risk of poverty by nearly 6%.…”
Section: Education Of Household Headsmentioning
confidence: 95%
“…According to the findings of Metalign (2005); Ayalneh and Korf (2009); Shete (2010); Dawit et al (2011); Mohammed (2017); Imam, Islam, and Hossain (2018) as the number of family in the household increases the probability of rural poor increases. Similarly, Dawit et al (2011) stated that small family size increases the probability of a household to be non-poor where a unit increase in the family size reduced the probability of being non-poor by 0.11.…”
Section: Sex Of Household Headmentioning
confidence: 99%