Multidimensional Poverty Measurement of China

Xiao-lin, Wang

doi:10.1007/978-981-19-1189-7_4

Cited by 6 publications

(11 citation statements)

References 8 publications

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“…Indicators, such as the incidence of poor health, the poverty caused by illness and catastrophic health expenditure, have been used to measure the incidence of diseases (Liu et al ., 2018). Individual factors, such as nutrition, mortality rate and medical insurance, have also been employed to evaluate health status (Alkire, 2013; Wang and Alkire, 2009). As for mental health indicators, depression, loneliness and attitude toward life have been used to measure an individual's mental health poverty (Sun and Zhang, 2018).…”

Section: Theoretical Frameworkmentioning

confidence: 99%

Health vulnerability and health poverty of rice farmers: evidence from Hubei province in China

Zhang²,

Yue³

et al. 2023

CAER

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PurposeThe purpose of this study was threefold: (1) to measure farmers' health poverty, (2) to examine the effect of health vulnerability on health poverty and (3) to identify countermeasures that may alleviate health poverty in rural China.Design/methodology/approachThis study built a health poverty measurement model based on the multi-dimensional poverty framework to evaluate farmers' health vulnerability. Further, this paper used an econometric model to assess the impact of health vulnerability on health poverty. The sample for this study comprised 1,115 rice farmers from Hubei province, China.FindingsThe medical affordability poverty ratio was 17.95%, where farmers in the low-income group faced severe medical affordability poverty (27.46%). Results from the multi-dimensional analysis showed that, the health poverty ratios were 17.95 and 30.50%, respectively. Our results indicated that climate change vulnerabilities, living habits, medical facilities and medical accessibility were positively related to health poverty, whereas the regular physical examinations reduced mental health poverty.Research limitations/implicationsBased on this study's findings, we proposed that: (1) to address illness-induced poverty among members of the agricultural community, national and provincial strategies and programs grounded on a multi-dimensional health poverty framework ought to be formulated and implemented, (2) mechanisms of health knowledge exchange may facilitate the improvement of farmers' health status, (3) robust and comprehensive metrics should be employed to understand and improve farmers' ability to absorb and mitigate the negative health impacts and (4) the improvement in both quality and quantity for medical facilities and medical affordability in the rural areas should be key priorities in governmental-wide initiatives.Originality/valueExisting studies for alleviating poverty caused by disease mainly focus on medical service support to those economic vulnerabilities after a disease happens. However, few studies have focused on the root causes of poverty caused by disease, particularly from the preventive perspective of health vulnerability. To fill this gap, this study, therefore, proposes the health poverty index and analyzes the impact of health vulnerability on health poverty.

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Section: Theoretical Frameworkmentioning

confidence: 99%

Health vulnerability and health poverty of rice farmers: evidence from Hubei province in China

Zhang²,

Yue³

et al. 2023

CAER

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“…This paper takes 12 provinces in China’s ethnic areas as the research object, draws on the three dimensions of economy, social development, and ecological environment proposed by Wang Xiaolin to construct a multidimensional relative poverty system [ 27 ], and adopts the A-F method to measure the multidimensional relative poverty index in China’s ethnic areas as well as the decomposition of the poverty index by region. Then, the entropy method is used for comprehensive evaluation, and the Gini coefficient is calculated based on the evaluation scores, and divided into three parts, namely, intra-group, inter-group, and hypervariable density, to analyze the spatial and temporal differences.…”

Section: Methodsmentioning

confidence: 99%

“…Specifically for Chinese scholars, Yao Wang reveals whether income poverty is necessarily energy poverty to test the effectiveness of domestic energy support policies targeting income-poor households, and analyzes the factors that lead to the inconsistency between these two poverty levels [ 26 ]. Based on microdata, Xiaolin Wang measures the multidimensional poverty of urban and rural households in China, arguing that provinces need to strengthen their urban anti-poverty efforts, and that multidimensional relative poverty can be disaggregated by urban and rural areas, regions, age, and gender to adopt more targeted poverty reduction policies [ 27 ].…”

Section: Introductionmentioning

confidence: 99%

Spatial and temporal differences and convergence analysis of multidimensional relative poverty in ethnic areas

Cheng,

2024

PLoS ONE

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Reducing multidimensional relative poverty is one of the important issues in the current global poverty governance field. This article takes 12 ethnic regions in China as the research object and constructs a multidimensional relative poverty measurement system. The calculated multidimensional relative poverty index is decomposed according to provinces, cities, dimensions, and indicators. Then, the Dagum Gini coefficient and convergence analysis are used to analyze spatiotemporal heterogeneity and convergence characteristics. The results show that the multi-dimensional relative poverty situation of various provinces in ethnic minority areas has improved from 2012 to 2021, among which Tibet province is the most serious and Shaanxi is the best. According to the analysis of convergence, it was observed that there is no σ-convergence of multidimensional relative poverty in ethnic areas in general, and there is absolute β-convergence in general and in the southwest and northwest regions, and there is no absolute β-convergence in the northeast region. Based on this, policy recommendations for reducing multidimensional relative poverty are proposed at the end of the article. Compared with previous studies, this article focuses on ethnic regions that are easily overlooked. Starting from the dimensions of economy, social development, and ecological environment, the poverty measurement system has been enriched.

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“…Hanandita and Tampubolon (2016) [32] selected indicators from income, health (illness, morbidity), and education (school, literacy) to research multidimensional poverty in Indonesia. Regarding the selection of multidimensional relative poverty indicators, we referred to the related research ( [33][34][35][36]. We followed the principles of scientificity, rationality, and data availability to select the indicators.…”

Section: Construction Of a Multidimensional Relative Poverty Index Sy...mentioning

confidence: 99%

Multidimensional Relative Poverty in China: Identification and Decomposition

et al. 2023

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This paper aims to study the change and decomposition of multidimensional relative poverty in China. The data we use are from the China Health and Nutrition Survey (CHNS). The data cover 12 provinces in China and span a long period, from reform to precise poverty alleviation. The results show that the multidimensional relative poverty index presents a change pattern of “gradual rise (1991–2004)-decline (2004–2011)-rise again (after 2011)”. The dimensions of education, income, and employment contribute more to multidimensional relative poverty, followed by health and living standards. Multidimensional relative poverty is more severe in rural areas, central and western regions, women, and the elderly. The “incidence of poverty effect” is the main factor in the changes in multidimensional relative poverty, and its contribution is higher than the “intensity of poverty effect”.

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Multidimensional Poverty Measurement of China

Cited by 6 publications

References 8 publications

Health vulnerability and health poverty of rice farmers: evidence from Hubei province in China

Health vulnerability and health poverty of rice farmers: evidence from Hubei province in China

Spatial and temporal differences and convergence analysis of multidimensional relative poverty in ethnic areas

Multidimensional Relative Poverty in China: Identification and Decomposition

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