An Analysis of the Factors Affecting Rural Multidimensional Poverty??q??q Based on the Theory of Family Life Cycle

Peng, Jiquan; Liu, Wenbin; Qin, Xiaodi; Wu, Haitao

doi:10.2991/snce-18.2018.239

Cited by 2 publications

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“…Moreover, it is advisable to consider children’s age as the different stages of life associated with diverse levels of expenditure required by childcare. The Rural reside children reported higher poverty compared to urban reside children, which is in line with previous studies [ 29 , 30 , 53 , 56 , 57 ], where rural children experienced more poverty compared to urban mainly due to the information constraints in the rural area. Mother age, maternal education, and belonging to a wealthier quintile were significantly associated with child poverty.…”

Section: Discussionsupporting

confidence: 91%

Prevalence and correlates of multidimensional child poverty in India during 2015–2021: A multilevel analysis

et al. 2022

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Despite increasing research and programs to eradicate poverty, poverty still exists and is a far greater concern for children than adults, leading child poverty to become a political, economic, and social issue worldwide and in India. The current study aims to find variations in the prevalence of child poverty and associated factors in India during 2015–21. In the current study, we used two consecutive rounds of the National Family Health Survey (NFHS-4, 2015–16 & NFHS-5, 2019–21) to estimate child poverty (aged 0–59 months) using the Alkire-Foster method. The multilevel logistic regression analyses were performed to find the important cofounder and cluster level variation in child poverty. The results show that about 38 percent of children were multidimensionally poor in 2015–16, which reduced to 27 percent in 2019–21. The decomposition analysis suggests that contribution of nutrition domain to child poverty increases over time, whereas the standard of living substantially declines from NFHS-4 to NFHS-5. The multilevel analysis results show that the age and sex of the child, age and years of schooling of the mother, children ever born, religion, caste, wealth quintile and central, northeast, north and west regions are significantly associated with child poverty over time. Further, the variance participation coefficient statistics show that about 12 percent of the variation in the prevalence of child poverty could be attributed to differences at the community level. The prevalence of child poverty significantly declines over time, and the community-level variation is higher than the district-level in both surveys. However, the community-level variation shows increases over time. The finding suggests a need to improve the nutritional status and standard of living of most deprived households by promoting a child-centric and dimension-specific approach with more focus on PSU-level intervension should adopt in order to lessen child poverty in India.

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Section: Discussionsupporting

confidence: 91%

Prevalence and correlates of multidimensional child poverty in India during 2015–2021: A multilevel analysis

et al. 2022

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“…The limitations and potential of the model's new approach were also explored in their study. Peng et al . (2018) employ the A-F multidimensional poverty approach to measure the multidimensional poverty of families at different stages of the family life cycle, based on survey data from 2,680 rural households in Hubei Province, China, using the Glick Family Life Cycle Model.…”

Section: Literature Reviewmentioning

confidence: 99%

Measurement and difference analysis of multidimensional poverty of floating population

Bhuiyan

Liu

Meng

2023

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PurposeAt present, the scale of China's floating population has reached 376 million people. Compared with the local inhabitants, the poverty problem of the floating population is more complex, and this problem should also attract the attention of all sectors of society. This paper aims to measure and analyze the multidimensional poverty of the floating population in China.Design/methodology/approachThe data used in this paper are the data of the China Migrants Dynamic Survey (CMDS) in China. This survey is a large-scale national migratory population sampling survey organized by the China National Health Commission, covering 31 provinces (autonomous regions and cities) and other autonomous regions. This paper uses the dynamic monitoring and Alkire and Foster (A-F) method to study the multidimensional poverty problem of the floating population.FindingsThis study finds that income poverty is no longer the main type of poverty faced by the floating population. The multidimensional poverty of the floating population mainly occurs in the social security and education dimensions, of which social security has become the most severe poverty dimension of the floating population. From the perspective of group differences, compared with the floating population in urban areas, the multidimensional poverty of migrant workers is more serious. However, the poverty of migrant workers is mainly concentrated in one-dimensional poverty and two-dimensional poverty.Social implicationsIn the future, the authors should focus on the social security of the floating population in the place of influx and the education of the floating population.Originality/valueThrough the review of the existing literature, the authors find that the current research on the multidimensional poverty of the floating population is mainly concentrated on the migrant worker groups that move from rural areas to urban areas. However, insufficient attention is paid to the urban floating population groups moving between cities.

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An Analysis of the Factors Affecting Rural Multidimensional Poverty??q??q Based on the Theory of Family Life Cycle

Cited by 2 publications

References 2 publications

Prevalence and correlates of multidimensional child poverty in India during 2015–2021: A multilevel analysis

Prevalence and correlates of multidimensional child poverty in India during 2015–2021: A multilevel analysis

Measurement and difference analysis of multidimensional poverty of floating population

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