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Poverty is no longer a problem of income alone. Healthy poverty and capacity poverty have become key factors affecting the poverty reduction effectiveness. Based on “double cut-offs” multidimensional poverty identification method of Alkire and Foster (J Public Econ 95(7–8): 476–487, 2011), this paper proposes a “triple cut-offs” identification meth...
Citations
... The economic factors influencing household poverty levels mainly include net income per capita [25,26], out-of-pocket healthcare payments, and health insurance [10]. From the perspective of regional development, economic factors affecting the overall poverty status of an area also include the gross regional product (or per capita gross regional product), the proportion of agricultural output value to the total output value of the region, the proportion of non-agricultural industries, per capita annual savings, and per capita disposable income and consumption expenditure [4,12,20,27]. ...
... China's experience in poverty alleviation governance has also proven that eliminating poverty relies on intellectual support, with education being the best intellectual investment [29,30]. The chronic poverty reduction effect of medical insurance makes a significant contribution to the overall chronic multidimensional poverty reduction among rural residents in China [26]. Households lacking labor and livelihood skills and capabilities are at higher risk of falling back into poverty [25]. ...
... Additionally, social support can mitigate the impact of poverty on the psychological health of left-behind children [33]. Research on China's poverty relapse issue has found that the poverty level of rural households is higher than that of urban households [28], and the poverty return index in rural and western regions is higher than that in urban areas and other regions of China [26]. The urbanization rate, number of rural employees, number of welfare institutions, and road network density are all major obstacles to vulnerability to poverty relapse in rural areas [27]. ...
According to the strategic plan for rural revitalization and the consolidation of poverty alleviation achievements, this research has developed an evaluation indicator system encompassing three dimensions: environment, social support, and economic resilience, viewed through a sustainable development lens. This system is designed to gauge the capacity to forestall a relapse into poverty in ecologically fragile regions and can also serve as a foundation for the government to establish a comprehensive early-warning and monitoring system. An integrated approach, combining the TOPSIS and entropy methods, was employed to assess the capability to prevent a recurrence of poverty based on data from Enshi Tujia and Miao Autonomous Prefecture spanning 2016 to 2022. Subsequently, the obstacle degree model was utilized to pinpoint critical barriers to enhancing its capability to mitigate the risk of reverting to poverty. The findings clearly indicated that, compared to other regions, Enshi City and Lichuan City maintained the most robust comprehensive capabilities to avert poverty recurrence between 2016 and 2022. Furthermore, the evaluation of capabilities across various dimensions revealed that, with the exception of Enshi City, other counties and cities demonstrated lower capacities in the environmental, social support, and economic resilience dimensions. Moreover, in 2020, the capabilities of all counties and cities deteriorated, and the capabilities under the dimensions of social support and economic resilience had not returned to their former levels by 2022, suggesting that the social and economic systems are susceptible to emergency public crises. A spatiotemporal analysis of the factors impeding the enhancement of capabilities in the counties and cities of Enshi Prefecture showed that the inhibiting factors varied by region, with the most prevalent obstacles stemming from economic resilience. In terms of environmental dimensions, the total regional water supply played a pivotal role in Enshi Prefecture. There was a pronounced regional disparity in the development of capabilities to prevent the recurrence of poverty, and the evolution of systems, such as the environment, social support, and economic resilience, was markedly uncoordinated. Finally, strategic recommendations and measures were formulated to bolster the capabilities to avert returning to poverty in ecologically fragile areas across these three dimensions.
... This gap is primarily attributed to the low incomes of rural residents, rather than the high incomes of urban residents. Additionally, it is worth noting that the disparity within the countryside is not primarily caused by wealthy farmers being excessively rich, but rather by the fact that poor farmers have very low incomes (Li, 2017;Zhu et al., 2019;Zhou et al., 2021;Peng et al., 2022a) At the same time, the rural collective economy development policy plays a crucial role in increasing farmers' income and reducing the disparity between urban and rural areas (Deng et al., 2023). Rural collective economy refers to the economic organization development form in which the collective organization and its members implement various forms of cooperation in production, supply, and marketing under the premise of rational utilization of collective resource elements. ...
The rural collective economy plays a crucial role in achieving the common prosperity of farmers, revitalizing the countryside, and modernizing agriculture in China. This paper analyses the impact and internal mechanism of the policy on the level of common prosperity, using provincial panel data from China from 2011 to 2020. Additionally, it investigates whether the rapid development of the rural collective economy takes into account both economic growth and income distribution. The findings demonstrate that the policy significantly enhances the common prosperity of farmers and rural areas. These conclusions remain valid even after considering the endogeneity problem and conducting robustness tests using the time-varying difference-in-differences model. Furthermore, the intermediary effect model reveals that the increase in the rate of farmland transfer and the proportion of scale operation play crucial roles in transmitting the benefits of the policy to achieve common prosperity. The result of the heterogeneity analysis indicates that the marginal decline of policy effect has a greater impact on the enhancement of rural collective economy in the less developed provinces of the central and western regions in China, compared to the developed provinces of the eastern region. These findings have targeted policy significance for promoting the sustainable development of agricultural and rural areas.
... Literature [11] suggests that health poverty and ability poverty have become the key factors affecting the effectiveness of poverty reduction, combines Foster's chronic thinking to construct a chronic multidimensional poverty reduction index, and designs a multidimensional poverty reduction effect of the "triple cut-off" identification method to comprehensively and systematically measure the effectiveness of China's multidimensional poverty reduction in terms of poverty alleviation and return to poverty. Literature [12], in order to study the quantitative measurement of multidimensional poverty regression in Chinese rural households, combined the worker neural network and multidimensional measurement model to assess the dynamic evolution of multidimensional regression poverty in rural households in China, showed that the per capita annual net income is the main factor leading to the decline of the multidimensional poverty rate, and put forward relative recommendations. ...
In order to achieve comprehensive poverty eradication, this paper analyzes the general structure of the poverty return early warning mechanism and the operation idea under the perspective of rural revitalization and explores the methods and systems of emergency decision-making for poverty return early warning. At the same time, based on the dynamics and scientific quantifiability, we have constructed the poverty return early warning indicator system, established the alarming degree of poverty return early warning, and combined the principal component analysis method and fuzzy comprehensive evaluation method. The empirical design is carried out on the basis of the design of the poverty return warning evaluation index system; the weight coefficients are derived from the principal component factors, and the fuzzy comprehensive score is calculated. The results show that the overall poverty return risk score is S={0.21, 0.27, 0.19, 0.18, 0.15}, and the risk early warning fuzzy evaluation value is 0.27, which is 87.4 points, and belongs to mild risk.
... There are no uniform and clear rules for determining the weight of each dimension and index. Referring to most literature [56,57], we adopt the method of dimension equal weight; that is, the weight of each dimension is equal, and the weight of indicators in each dimension is equal. ...
(1) Background: Poverty eradication is the common goal and challenge of human development. Livelihood capital is the basis for poor families to escape poverty and is also the key to enhancing the ability for sustainable development. (2) Methods: Using data from the 2018 China Family Panel Studies (CFPS), this paper empirically examines the impact of livelihood capital on poverty alleviation. In addition, the mediating effect of land transfer is explored. (3) Results: The results show that human, physical, financial, and social capital all have a significant positive impact on poverty alleviation, while natural capital has a significant negative impact on poverty alleviation. Moreover, land transfer plays a partial mediating role in the relationship between livelihood capital and poverty alleviation. (4) Conclusions: Based on the above findings, we suggest that the government formulate targeted poverty alleviation policies according to rural households’ livelihood capital endowment characteristics, reasonably guide the land flow, and achieve sustainable poverty reduction.
... This risk is often associated with various factors, such as economic instability, natural disasters, or health crises, and can be influenced by the availability and effectiveness of social safety nets and poverty reduction policies (Li Q. et al., 2022;Xu and Yang, 2022). In the past, re-poverty was primarily regarded as a byproduct of poverty, receiving little attention (Li et al., 2016;Zhou, Cai, and Zhong, 2021). However, as global poverty alleviation efforts progress and the number of impoverished individuals significantly decreases, stabilizing the economic status of households that have escaped poverty and preventing re-poverty have become pressing concerns for both governments and the academic community . ...
In the context of China’s comprehensive poverty alleviation efforts, this study explores the differences in the re-poverty risk between households that have been lifted out of poverty before and after policy withdrawal, as well as the sensitivity of different family types to their livelihood capital. The study used data from 45,141 out-of-poverty households in Yucheng County, Henan Province, from 2016 to 2020, and combined the poverty vulnerability theory and short-fall risk method to evaluate the re-poverty risk. The Tobit model was used to explore the influence of livelihood capital on the re-poverty risk. The study found that the overall re-poverty risk is 1.13%, which increases to 18.09% after direct poverty alleviation policy is withdrawn. The risk of working families is significantly lower than farming families. All kinds of livelihood capital significantly reduce the re-poverty risk, with natural capital playing the most significant role. For different family types, the marginal contribution of financial capital to reducing the re-poverty risk is relatively larger in working households, while that of natural capital is larger in farming households. Specifically, labor capacity, arable land area, local leaders, and loans have a more significant inhibitory effect on the re-poverty risk. These findings provide valuable insights for formulating policies related to increasing household income and preventing the occurrence of re-poverty.
... There have been remarkable achievements in global poverty reduction since it has steadily decreased over the past two decades [1][2][3][4]. However, these hard−won gains are not easy to maintain [5] because various factors (e.g., withdrawal of aid, disease, regional conflicts, international tensions, economic recession, and climate change, etc.) may cause those just climbing out of poverty to fall back once again [6][7][8][9]. Especially the recent outbreak of the COVID-19 pandemic has been serving as a brake in overcoming poverty by posing a more serious threat to low-income groups [10,11]. Non-pharmaceutical interventions to restrict contagion, including border controls, social distancing, and mobility restrictions [12][13][14], resulted in shrinking market demand [15] and a shortage of job opportunities, which damaged their livelihoods, in turn intensifying poverty re-entry [11]. ...
Many poverty−alleviation−relocation projects in China resort to tourism to sustain immigrants’ livelihood in new communities. However, how tourism contributes to poverty elimination and maintaining gains is yet to be discovered. Based on the sustainable livelihood concept, this study constructs a three-dimensional index system to evaluate livelihood sustainability and identify potential factors in three relocated tourism communities. Results show that most resettled residents have median-level livelihood sustainability. Livelihood capital, strategies, and environment contribute to livelihood sustainability in decreasing order. Regarding livelihood modes, tourism−led livelihood takes the first position in terms of supporting livelihood sustainability, followed by outside−work−led, local−work−led, and government subsidy−led livelihoods. Regarding obstacle factors, annual household income, number of household workers, and education levels are shared by relocated households across different livelihood modes. Aside from policy suggestions on survey sites, this study provides a holistic framework and enlightens the generalizable paradigm to the analysis of sustained livelihood via tourism development in relocated communities.
... The first dimension selected is income. An assessment of the effectiveness of multidimensional poverty alleviation in China shows that long-term poverty alleviation targeting net income per capita contributes significantly to long-term multidimensional poverty alleviation among Chinese rural residents as a whole (38). This suggests that income continues to have a significant impact on poverty in rural China. ...
Introduction
This paper examined the impact of public long-term care insurance (LTCI) pilots in China on the multidimensional poverty status of middle-aged and older adults.
Methods
Using panel data from the China Health and Retirement Longitudinal Survey, we utilized LTCI pilots conducted in different cities from 2012 to 2018 and assessed the impact of LTCI using a difference-in-differences strategy.
Results
We found that the implementation of LTCI reduces the multidimensional poverty of middle-aged and older adults and their likelihood of future multidimensional poverty. LTCI coverage was also associated with a reduction in the likelihood that middle-aged and older adults in need of care fall into income poverty, living consumption poverty, health poverty, and social participation poverty.
Discussion
From a policy perspective, the findings of this paper suggest that the establishment of an LTCI system can improve the poverty of middle-aged and older adults in several ways, which has important implications for the development of LTCI systems in China and other developing countries.
... For example, Zhou and Jiang improved the A-F Method, and proposed a new "multidimensional poverty-returning index" based on "three cut-offs." Their approach focuses on measuring the multiple poverty returning of urban and rural families, and rural migrant workers in China, able to effectively identify the internal changes of poverty (Jiang & Zheng, 2017;Zhou et al., 2020). However, such approach assigns equal weight to each dimension, neglecting the complex features of each dimension, such as discreteness and nonlinearity. ...
... Deprivation of any two is identified as poverty. In this paper, based on CFPS questionnaire for families, adults whose health condition is below 4 are identified as impoverished; seniors over 65 years old whose BMI is below 18.5 and children under seven years old with weight-for-height less than the difference between mean value and a standard deviation are malnutritional on WHO standards (Zhou et al., 2020); households whose proportion of OOP healthcare payment in nonfood consumption expenditure surpasses 40% are poor (Zhang & Yao, 2020); households in which no one has access to any type of health insurance-a basic guarantee for rural households to cover large medical expenses-are poor. ...
... First, adult health, health insurance, annual net income per capita, and OOP healthcare payment had relatively high return-to-poverty rates, most of them exceed 10%, the results were in line with the findings of Zhou (Zhou et al., 2020) and Jiang (Jiang & Zheng, 2017), proving to be a priority of poverty alleviation in the future. High poverty-returning rate may come from the following reasons: First, impoverished people lag in self-improvement ability or determination, making it hard for them to shake off poverty and get rich, so they will fall back to poverty once favorable policies are removed. ...
Existing studies rarely focus on the quantitative measurement of the multi-dimensional return to poverty in Chinese rural households. Therefore, this paper assessed the dynamic evolution of multidimensional return to poverty in Chinese rural households based on the China family panel studies during 2010–2018, applied methods like artificial neural network and multi-dimensional measurement model. Here are the results: (1) Chinese rural households’ multidimensional return-to-poverty index dropped significantly from 0.0567 in 2012 to 0.0425 in 2018, mainly due to the decreased poverty returning rate. (2) Annual net income per capita was a major contributor to the decrease of multidimensional return to poverty, followed by four indicators in health dimension—adult health, out of pocket healthcare payment, health insurance, and senior and children health. (3) Chinese rural households’ multidimensional return-to-poverty index manifested great spatial heterogeneity—increasing from Eastern China, to Central China, then to Western China. In the end, this paper proposed policy suggestions on preventing poverty returning and promoting common prosperity.
... However, they are prone to small sample bias and the omission of unobservable variables that also causes bias in the cross-regional analysis, thereby affecting the reliability of conclusions to a certain extent [52]. Moreover, compared with a single scheme, multilayer medical security delivers a more significant effect in poverty reduction [53]. Since few scholars have paid attention to the empirical research of multi-layer medical security policies [54], this study used more comprehensive multi-period data to probe the effect of a TMS policy on the VEP of rural registered poor households. ...
China launched the “critical battle against poverty” nationwide in 2012. As its main battlefield, Yunnan province promulgated the “triple medical security” (TMS) policy in 2017. This study, based on the pooled cross-section database of 2015–2020 of registered poor households in Yunnan province, employed the logit model to examine the effect of TMS on the vulnerability as expected poverty (VEP) of these households. It found that increasing the reimbursement rates for overall medical expenses and inpatient expenses and decreasing the proportion of out-of-pocket medical payment to income reduced the VEP; increases in the number of sick people in the family increased its VEP, and although the increase in the reimbursement rate for overall medical expenses or for inpatient expenses partially offset the VEP caused by the increase in the number of chronically ill people in the family, the VEP caused by the increase in the number of critically ill people would increase in the short term with the increase in the reimbursement rate for overall medical expenses or for inpatient expenses. The findings help improve policies concerning the medical security and health of the rural poor population, providing theoretical reference and practical guidance for future research.
... At present, the government often uses the income poverty standard to calculate the headcount ratio to measure poverty. e poverty index is a static measure of a household's well-being at a particular time [10]. ere are limitations in antipoverty policies made by the government based on the incidence of poverty. ...
Drawing on three-wave panel data from China Family Panel Studies (CFPS) of 2014, 2016, and 2018, this paper measures rural households’ vulnerability to relative poverty using the three-stage feasible generalized least squares (FGLS) model. We analyze the impact of human capital on vulnerability to relative poverty by using the two-way fixed-effected model and panel quantile regression. Empirical results exhibited that labor force migration, health, education, and working experience all have a negative effect on vulnerability to relative poverty. Labor force migration has the greatest negative effect among the four factors. Heterogeneity analysis results exhibited that labor force migration has the biggest negative effect in the east region. Health and education have the greatest negative impact in the central region. Labor force migration, health, work experience, and education have a greater effect on nonpoor households than on poor households.
