Intensity and Determinants of Rural Migrant Workers’ Multidimensional Poverty in China

Dan Xu, Dongshen Luo, Xiu He, Tingting Lin, Chengchao Wang

Abstract


Multidimensional poverty of rural migrant workers is become an important component of urban poverty of China, accompanied by large-scale rural-urban migration during past decades. However, less studies have been conducted to explore the poverty of rural-urban migrant workers. The study intends to fill the gap by investigating multidimensional poverty of rural migrant workers based on a case study in Fuzhou City, Southeast China. The Alkire–Foster method and a logistic regression modeling are adopted to examine the magnitude and determinants of multidimensional poverty. Four dimensions and ten indicators are selected for measurements of multidimensional poverty. About seventy three percent of the sample households (n=319) are found to experience multidimensional poverty, which is remarkably higher than previous studies. Especially, the deprivation incidence of dwelling conditions and working conditions which were neglected in previous studies, was remarkable high. Spatial heterogeneity of multidimensional poverty has been highlighted in our study. The incidence of multidimensional poverty in 'village in the city' is the highest, following by suburban areas and town center (k=0.33). Results also reveal that income and living standards are two most important contributors of overall poverty. The important determinants of multidimensional poverty are as follows: occupational skills, migration type, occupational type, social integration, and expenditure on social activities. The results confirmed that low skills, low social integration in cities, and poor social capital are key determinants of rural migrant workers’ poverty in urban areas of China. Finally, some policy implications for poverty alleviation of rural migrant workers are presented in the study.


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DOI: https://doi.org/10.20849/ajsss.v9i4.1449

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Asian Journal of Social Science Studies  ISSN 2424-8517 (Print)  ISSN 2424-9041 (Online)  

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