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Article

Multi-Dimensional Decomposition, Measurement, and Governance Mechanism of Relative Poverty in Chinese Households under the Goal of Common Prosperity: Empirical Analysis Based on CFPS2020 Data

1
School of Public Administration, Northwest University, Xi’an 710127, China
2
School of Foreign Languages, University of Electronic Science and Technology, Chengdu 611731, China
*
Author to whom correspondence should be addressed.
Sustainability 2024, 16(12), 5181; https://doi.org/10.3390/su16125181
Submission received: 20 April 2024 / Revised: 8 June 2024 / Accepted: 12 June 2024 / Published: 18 June 2024
(This article belongs to the Section Sustainable Urban and Rural Development)

Abstract

:
From the perspective of household productivity, this paper analyzes the capital composition of the household and the formation mechanism of relative poverty. Based on the CFPS data in 2020, it uses the Alkire–Foster (AF) index to measure the breadth and depth of relative poverty in different regions and puts forward its governance mechanism. The results show that there are significant differences between urban and rural areas and among different regions. The relative poverty incidence rate is mainly concentrated in four indicators, accounting for 30.8% of the total number of indicators. From high to low, the incidences of relative poverty in a single dimension include financial assets, livelihood assets, health, and employment levels. The breadth is mainly reflected in economic capital, health, employment, and education level. The depth is reflected in financial assets, health level, and social network indicators. Except for the social capital dimension, the poverty in rural areas is higher than urban areas, and the central and western regions are higher than the eastern regions, showing a distinct characteristic of imbalanced urban–rural and regional development. This paper proposes the relative poverty governance mechanism of households’ capital accumulation, urban–rural integrated development and regional coordinated development.

1. Introduction

In 2020, China has made great achievements in absolute poverty alleviation, achieved the first Centennial goal of building a moderately prosperous society in an all-round way, and started a new journey for the second Centennial goal. After entering a well-off society, people have a stronger desire for a better life and have more expectations for more equitable, full, and sustainable development. At the same time, the problem of unbalanced and inadequate development has become increasingly prominent, and income inequality and polarization are also on the rise [1,2]. To promote common prosperity, continue to reduce polarization, expand middle-income groups, improve the livelihood capabilities of low-income groups, and gradually solve the problem of unbalanced and inadequate development, so that people can have more sense of gain, happiness, and security in the process of development is an important part of realizing sustainable development in an all-round way. To achieve common prosperity is consistent with the development goal of alleviating relative poverty, making relatively poor groups continue to transition to the average living standard of society, so as to expand the middle-income groups. Therefore, achieving common prosperity is the ultimate goal of solving relative poverty, and solving relative poverty is an effective means to achieve common prosperity.
In October 2019, the Fourth Plenary Session of the 19th CPC Central Committee formally proposed the issue of addressing relative poverty. On 6 April 2021, China’s State Council Information Office issued a white paper titled “Poverty Alleviation: China’s Experience and Contribution”, stating that China achieved the goal of eliminating extreme poverty. The 98.99 million people in rural areas who were living below the current poverty threshold all shook off poverty by the end of 2020. After 2020, poverty governance will focus on relative poverty, the governance goal will change from mainly solving income poverty to solving multidimensional poverty, the governance direction will change from focusing on rural areas to urban–rural coordination, and the driving force of poverty reduction will shift to paying equal attention to external support and endogenous motivation. The policy support will shift to both security and development and continue to improve the livelihood capability and quality of life of the relatively poor. Therefore, the research objective of this paper is to explore the governance mechanism of relative poverty, and based on this objective, three research questions could be proposed. (1) From the perspective of household productivity, what dimensions and indicators should be reflected in identifying the relative poverty household? (2) How to measure multidimensional relative poverty of households? And which indicators have an important impact on causing relative poverty? (3) What is a reasonable governance mechanism for relative poverty?

2. Literature Review

With the continuous deepening of research on poverty, people have found that explaining poverty from a single dimension of basic income that meets survival needs is no longer enough to cover the true content of poverty. Especially after solving basic survival problems, people’s demands for social welfare and self-development continue to expand to multiple dimensions. Amartya Sen, as the founder of the multidimensional poverty theory, believes that freedom is the highest value standard for human development and the capabilities to lead the kind of lives that people have reason to value. A person’s capabilities refer to the various functionings that are accessible for that person. The deprivation of basic capabilities is reflected in premature mortality, significant undernourishment, persistent morbidity, widespread illiteracy, and other failures, rather than merely in low income [3]. In this sense, human development and improvement of quality of life are multidimensional enhancements and empowerment. Crossing the poverty line alone does not reduce the additional implicit costs for poverty alleviation populations in accessing social resources, and may even lead to their return to poverty due to lack of capabilities or rights. Some scholars also believe that the core view of multidimensional poverty is that human poverty is not only income poverty, but also includes poverty in other objective indicators such as drinking water, roads, sanitation facilities, and subjective perceptions of welfare [4]. Therefore, poverty is essentially a social representation of multidimensional deprivation of human development and well-being. Regarding the measurement of multidimensional poverty, Alkire and Foster elaborated on the measurement method of multidimensional poverty [5,6,7], identifying three dimensions of health, education, and standard of living, as well as ten indicators, and assigning equal weights to each dimension.
The research of multidimensional poverty deepens people’s understanding of the nature of poverty, and also provides effective ideas for poverty governance in various countries. In terms of research methods and dimension selection, Duclos et al. assessed issues involved in the measurement of multidimensional poverty, in particular the soundness of the various “axioms” and properties often imposed on poverty indices [8]. Ciani et al. adopted a fuzzy sets approach to measure multidimensional poverty in eight Mediterranean countries during 2007 to 2015 [9]. Nicholas et al. developed a multidimensional poverty measure that can identify and be decomposed based on the proportion of the poverty score attributable to deprivation concentration within periods and dimensions [10]. Burchi focused on two central challenges: the identification of the best theoretical framework and the selection of poverty dimensions, and proposed a new solution to the problem of how to select dimensions of poverty [11]. Gordon thought that concepts like poverty, human rights, or mathematical ability can only be measured indirectly by using suitable indicators and adopting a latent variable approach [12]. Cacabelos et al. concluded the increase in multidimensional poverty in the period studied, both in incidence and in intensity, regardless of the selected threshold [13]. In terms of research subjects, White provided a comprehensive overview of the construction of the Multidimensional Poverty Index (MPI), offering a comprehensive analysis of multidimensional poverty in a number of developed economies [14]. Tripathi et al. studied multidimensional poverty in India, and pointed out that lack of education of the household members made the highest contribution to poverty, followed by income, and standard of living in India [15]. Bandola-Gill made an inquiry into the measurement of multidimensional poverty in Sustainable Development Goal 1 (“End poverty in all its forms everywhere”) [16]. Pradhan et al. examined multidimensional child poverty (MCP) trends and tracked efforts to reduce child poverty at the national level across geographic regions, castes, and religious groups [17].
Chinese scholars have actively explored and studied poverty issues from a multidimensional perspective and put forward effective policy suggestions. In terms of research methods, mainly based on the AF method, some scholars introduced methods such as the artificial neural network methods, the BP neural network model, the ELES method, and so on, to measure multidimensional poverty situation in different areas and groups [18,19,20]. In terms of dimension setting, Song et al. measured poverty among elderly people in urban and rural areas of China from four dimensions: economic level, health level, living standard, and social integration [21]. Wang proposed that China’s formulation of relative poverty standards can incorporate economic dimensions, social development dimensions, and ecological environment related indicators into an analytical framework for multidimensional poverty [22]. Tan advocated the development of a relative poverty standard system consisting of multiple criteria, including minimum secure, numerical, proportional, multidimensional, and shared prosperity indicators, supported by the concepts of relative poverty, multidimensional poverty, and shared prosperity [23]. Wang et al. constructed multidimensional poverty measurement indicators for households from six dimensions: income, health, education, employment, social security, and living environment [24]. On the formation and governance mechanism of poverty, they found that regional development imbalance has a significant impact on multidimensional poverty. The farmers who engage in diversified operations and non-agricultural employment have a lower incidence of multidimensional relative poverty. Also, education is the most important factor in alleviating poverty. At the same time, they suggested adopting a relative poverty targeting mechanism that combines regional and individual targeting, urban and rural targeting, and key areas and populations targeting [24,25,26,27].
Overall, the multidimensional poverty theory and measurement methods have made great progress in measuring the multidimensional degree of poverty in China. Many achievements can be compared and exchanged with the international academic community, providing auxiliary references for establishing a more comprehensive poverty monitoring, prevention, and assistance system in the new era. Moreover, the setting of dimensional indicators has expanded from basic needs to fair, high-quality, and sustainable public service development requirements, and the threshold setting is often closely related to the country’s economic development level and poverty governance policies. However, there are still difficulties in measuring multidimensional poverty, such as how to set and empower indices, and how to define the interrelationships between indicators in each dimension, which is the focus of this paper.

3. Multidimensional Decomposition of Relative Poverty from Household Productivity

3.1. Household Productivity

As the basic unit of human social life, the household is the main organizational form for each individual to obtain care and welfare in the life cycle, and it is also an important trade-off content of their decision-making behavior of avoiding or taking risks. From Booth, Rowntree, and Townsend’s social survey of poverty in Britain to Sen and Banerjee’s poverty studies in South Asia and Africa, poverty and its nature have not been defined in isolation from households [28,29,30,31,32]. The UK, America, Australia, and other Western developed countries also set relative poverty standards with the household as the basic unit, and set poverty standards in different years according to the level of regional economic development, family size, and characteristics of members. Duncan et al. pointed out that a complete poverty theory should be based on the household, which should be a complex multi-connected theoretical organism including family composition, family income, property accumulation, transfer plan, and macro economy [33].
The productive capacity is the determinant of the household’s escape from poverty. In classical economics, the household was regarded as a consumption unit, while Becker believed that in addition to being a consumption unit, the household was also a production unit composed of multiple individuals. Different members input production factors such as commodities, time, money, and skills will generate joint utility, which mainly includes utility derived from household outputs such as children, commodities, prestige, health, and pleasures of the senses [34]. Household members make rational allocation according to the capital stock of the household so as to maximize the utility, so the capital stock of the household at a given time determines the productive capacity, as well as decision-making behavior and future expectations. Households’ lack of capital stock leads to inadequate productive investment and, in turn, an inability to raise incomes and living standards.
As for a household, firstly, material production is the most basic practical activity of production, which is a social practice carried out by household members to meet their livelihood needs, and its level is constrained by the household’s economic capital. Secondly, population production is a fundamental prerequisite and necessary condition for social existence and development. Its level of productivity determines the quality of household members, and it exhibits different levels of health at different stages of life. Members sustained health can avoid the risk of poverty, improve their quality of life, and increase the time and opportunities for household members to create and accumulate wealth. Thirdly, the growth of household members into a labor force with certain knowledge, skills, ways of thinking, values, and social experiences is mainly realized through education and training. This is the main way of human capital accumulation and an important manifestation of households’ productive capacity. Poor households are unable to afford the increasing high investment in education, resulting in the lack of human capital of households. Finally, with social development and the advancement of technology, the ways and scope of people’s participation in social production and cooperation are constantly expanding. Household social capital plays an important role in helping households improve their production capacity and obtain social benefits. Household members with poor social capital cannot effectively share the benefits of economic and social development and are more likely to fall into a state of poverty and social exclusion. Sen argues that social exclusion is part of capacity poverty and can lead to other deprivations that further limit our life opportunities [35]. The four types of household capital together determine the capability of household members to obtain life needs and accumulate wealth.

3.2. The Capital Composition of Household Productivity

Economic capital is the core content and material basis of household productivity, and it is the material guarantee for members to maintain their livelihood and achieve sustainable development. Household economic capital comprises productive capital, housing, savings, and various types of asset equities. Additionally, it includes basic living materials that are essential for maintaining the sustainability of household livelihoods [36,37]. The lack of economic capital leads to the fragility of household members in obtaining livelihood income, seeking employment, and a healthy life. Specifically, it manifests in low income, inability to meet the average social demand, incompetence to obtain information effectively and integrate into social life actively, and ultimately encountering a sense of frustration in social life.
Health capital affects the labor time and production costs in the production process. Maintaining a certain level of health capital stock for a long time will bring sustained material and spiritual benefits to the household and its members. The opportunity cost of investing in health maintenance for relatively impoverished populations is too high, resulting in more time being devoted to work to obtain income and goods, which compresses health investment and leisure time, ultimately damaging physical health and increasing the cost of maintaining health. Grossman believed that personal health is a capital stock that depreciates with age. To increase the length of life and obtain more income, it is necessary to increase health investment to supplement capital loss. Therefore, the individual’s demand for medical services will increase with age [38]. The health damage, disability, or premature death of individuals will result in the loss of working time and future benefits, increase medical costs, and impose material and mental burdens on other household members.
Human capital affects the employment quality and income level, and generates positive incentives among intergenerational members, which is an important component of their livelihood capabilities. The human capital theory of American economists Schultz and Becker suggests that human capital is mainly accumulated through education investment to improve population quality [39]. According to Becker’s theory, people with higher marginal returns on human capital investment are more motivated to invest in education, and those with stronger abilities will invest more in human capital. Therefore, reducing the cost of educational investment, especially by enjoying fair educational opportunities and resources, and strengthening employment services and policy support, is conducive to stimulate the driving force of human capital investment and prevent intergenerational transmission of poverty. For households, the length of education, educational investment, accessibility of resources, and employment level of its members are important components of human capital.
Social capital is informal forms of organizations based on social relationships, networks, and associations, which can achieve knowledge sharing, mutual trust, social norms, and rules, and provide the ability and opportunities to generate income, enabling individuals to access and use resources embedded in social networks [40]. Social capital involves interconnected networks of relationships between individuals and groups, levels of trust that characterize these ties, and resources or benefits that are gained and transferred by virtue of social ties and social participation. The insufficient capital stock for relatively poor households to participate in social transactions, coupled with poor risk carrying capacity, unequal information acquisition, and high transaction costs, objectively hinder the reciprocal relationship between relatively poor groups and other social groups.
Economic capital, health capital, human capital, and social capital collectively reflect the level of household productivity. The stock of the four types of capital, as well as their interaction, determine the capability of household members to obtain life needs and accumulate wealth.

4. The Measurement of Multidimensional Relative Poverty in Households

4.1. Measurement Methods

The AF method, also known as the dual-cutoff method, sets two cutoff values for identifying unidimensional and multidimensional poverty. Let y = y i j denote the n × d matrix. Any element y i j in y represents the value of the ith household in the jth dimension, i = 1,2 , , n ; j = 1,2 , , d . The row vector y i represents the values of the ith household across all dimensions, while the column vector y . j represents the values of different households in dimension j. Now, a cutoff value z j (the deprivation cutoffs) is first set for each dimension to identify poverty in a single dimension and z is the row vector of deprivation cutoffs. If the value of household i in the jth dimension is y i j < z j , then the household is identified as poor in this dimension and assigned a value of 1. On the contrary, if the value of household i in the jth dimension is y i j z j , then the household is non-poor in this dimension and it is assigned a value of 0, so as to form a deprivation matrix g 0 = g j 0 . From matrix g 0 , we can construct a column vector I that aggregates the dimensions of household i suffering from relative poverty. Meanwhile, let g i j 1 = g i j 0 · z j y i j z j to form a matrix g i j 1 , representing the poverty distance of household i on dimension j. In addition, set the cutoff value k (the multidimensional poverty cutoff) for multidimension, with a value range of [0, 1], indicating the ratio of the number of dimensions that household i is deprived of to the total number of dimensions. Assuming that the total number of dimensions is 10, k = 0.3 means that any three dimensions of household i are deprived. It should be pointed out that when k = 1 d , it is the union approach, which means that household i is identified to be relatively poor if there is at least one dimension in which the household is deprived. When k = 1 , it is the intersection approach, which identifies household i as being relatively poor only if the household is deprived in all dimensions. Meanwhile, set weights w j for each dimension. Then, adding deprivation scores across all dimensions can yield the total deprivation value c i k for the ith household, that is, c i k = j = 1 d g i j 0 w j . When the total deprivation value for the ith household c i k k , the ith household is the multidimensional relative poverty household, and q i k = 1 . When the total deprivation value c i k of this household is less than k, it is considered a non-multidimensional relative poverty household, with q i k = 0 . The identified impoverished households not only include welfare deficiency scores on a single index, but also integrate information on deprivation in multidimensional indicators. This improves the accuracy of poverty identification and effectively overcomes the problem of excessive and insufficient scale caused by union and intersection methods in identifying poverty.
After identifying the deprivation values of each dimension indicator, the multidimensional comprehensive index can be obtained by dimension aggregation. The multidimensional relative poverty incidence H is the ratio of multidimensional relative poverty population to the total population, also known as the FGT index [41], and q is the number of the multidimensional relative poverty households using the dual cutoff approach, as shown in Equation (1):
H = q n = 1 n i = 1 n q i k
However, the shortcoming is that it is not sensitive to the distribution of poverty and the depth of deprivation. Therefore, Alkire and Foster proposed a multidimensional relative poverty breadth index M 0 , which is modified by the average deprivation share A, as shown in Equation (2):
M 0 = H A = 1 n i = 1 n c i k
M 0 is composed of the product of H and A, and the equation for average deprivation share is A = 1 q i = 1 n c i k . When c i k k , c i k = j = 1 d g i j 0 w j , and when c i k < k , c i k = 0 . Based on this, the average deprivation share of multidimensional relative impoverished households can be obtained. M 0 is sensitive to the incidence and breadth of multidimensional poverty, as if the ith household is deprived in an additional dimension, A will increase, and M 0 will also increase, but it still cannot reflect the deep information and welfare inequality of impoverished households. On the basis of the multidimensional poverty breadth index, M 0 is further adjusted with the average poverty gap G to obtain the multidimensional relative poverty depth index M 1 , as shown in Equation (3):
M 1 = H A G
In Equation (3), G = g i j 1 g i j 0 , representing average poverty gap between the actual level and cutoff value of impoverished households in various dimensions. Meanwhile, the multidimensional relative poverty index can be decomposed by group and dimension to obtain the contribution rates of each group and dimension, to further identify the impact of each group or dimension indicator on household poverty. The equation for decomposing the multidimensional relative poverty index by group at the cutoff value of k is as follows:
M k = i = 1 u n i n M i
In Equation (4), u represents the number of groups divided according to different standards, n i n represents the proportion of the sample size of group i to the total sample size n, and M i is the multidimensional relative poverty index of group i. The equation for decomposing by dimension indicators is:
M k = 1 n d i = 1 n c i k = 1 n d i = 1 n j = 1 d g i j 0 w j = j = 1 d 1 n d i = 1 n g i j 0 w j
In Equation (5), 1 n d i = 1 n g i j 0 w j represents the poverty index of dimension j, from which the contribution rate of dimension j in the multidimensional relative poverty index c i k can be obtained, as shown in Equation (6):
C j k = 1 n d i = 1 n g i j 0 w j 1 n d i = 1 n c i k = i = 1 n g i j 0 w j i = 1 n c i k
The above equations can be used to measure multidimensional relative poverty, and the following section explains the main materials required for this study.

4.2. Data Sources, Indicator Construction, and Weight Setting

The research data in this paper comes from the China Family Panel Studies (CFPS), conducted by the Institute of Social Science Survey (ISSS) at Peking University in 2020 [42]. CFPS, as a national and comprehensive social tracking survey project, includes data and information on communities, households, and individuals, comprehensively reflecting the development and changes in China’s society, economy, population, education, and health. As in 2020, China had completed the task of lifting the absolute poor out of poverty, and poverty governance began to focus on relative poverty. This paper selects data from 2020 for measurement and analysis, to provide theoretical reference for relative poverty governance after 2020.
Firstly, households’ economic capital is measured by four indicators: the per-capita net income of households, financial assets, livelihood assets, and housing expenses. The per-capita net income of households is one of the most intuitive indicators of households’ economic level, and the widening income gap significantly exacerbates the multidimensional poverty situation of households [43]. Household financial assets can bring investment and interest income to households, and their good liquidity is conducive to enhancing their capabilities to cope with unpredictable risks. Durable goods can deliver useful services to a consumer through repeated use over an extended period of time, and the flow of services from durables must be valued and comprised in the welfare [44,45]. Therefore, the total value of “durable goods” is used to represent the livelihood asset status of a household. In addition, a good living environment and conditions can bring a healthy and happy life experience and provide the base from which people live their lives, connecting them to work, education, services, and their communities. This sub item is measured by “housing expenses” (including rent, water and electricity, fuel, and property costs). According to the China Statistical Yearbook 2021, the per capita housing consumption expenditure of Chinese residents was CNY 5215, accounting for 24.6% of the per capita consumption expenditure, and it had been fluctuating between 21% and 25% from 2015 to 2020. The household poverty line in the UK is also set by deducting the housing cost, so housing expenditure is an important content of the household welfare and economic capability. The cutoff value of each indicator of household economic capital is set at 40% of the median of urban and rural, respectively.
In the dimension of health capital, the cutoff value of health level is that at least one household member self-evaluates themselves as unhealthy. The cutoff value for health security indicators is set at least one household member aged 16 and above who has not participated in medical insurance [24]. According to the measurement standards of the World Health Organization (WHO), the normal range of BMI for a healthy physique is 18.5–24.99. Therefore, the cutoff for a healthy physique is set as at least one household member aged 16 and above with a BMI less than 18.5 [46,47,48].
The core indicator of human capital is the employment level of household members. At least one household member aged 16–60 who is unemployed or exits the labor market can be considered deprived of this indicator. Given the significant gap in educational attainment between generations, the education level of household members is only measured by the average educational attainment of adult population aged 16–60. If the average length of education is below 6 years, it is considered that the household is relatively poor. The level of information acquisition is an important manifestation of household human capital. Based on the questionnaire items related to online learning, entertainment, and WeChat use, a mean of less than 3 is considered relative deprivation [49,50,51].
The dimension of social capital includes three indicators: social network, social trust, and social participation. The social network is measured by cash gift expenditure, and the lower the expenditure level, the less social network resources there are. If the household does not pay cash gift, it is considered relatively deprived. The cutoff value for social trust is set as the average trust level (0–10) of household members towards neighbors, strangers, and doctors being less than 5. Social participation is measured by the average level of household members’ participation in political parties or social organizations, and not participating in any parties or organization is considered relative deprivation [52,53,54].
In addition, the weight setting of each indicator is crucial for the calculation of the multidimensional poverty index. Currently, most scholars adopt Alkire and Foster’s equal weight method [4,55]. This method is easy to operate, but it is difficult to accurately reflect the differences between indicators. Meanwhile, there are also a few researchers who have explored non-equal weight methods, mainly including principal component analysis [56,57,58], entropy weight [59,60,61], artificial neural network [18], etc. To compensate for the disadvantage of original data information loss caused by the equal weight method, and to objectively reflect the true changes in the data, based on the binary data of the multidimensional poverty deprivation matrix, this research calculates the weights of each indicator using the entropy method. The calculation process of entropy method weight is as follows. (1) Data standardization, positive indicator u i j = X i j m i n X i j m a x X i j m i n X i j ; negative indicator u i j = m a x X i j X i j m a x X i j m i n X i j . (2) Calculate the proportion of ith sample values in the sum of all sample values in the jth indicator, p i j = u i j i = 1 n u i j , 0 p i j 1 , i = 1,2 , , n , j = 1,2 , , d . (3) Calculate the entropy value of jth indicator, e j = 1 ln n i = 1 n p i j ln p i j , 0 e j 1 . (4) Calculate the coefficient of variation, v j = 1 e j , 0 v j 1 . (5) Calculate the indicator weight, w j = v j j = 1 d v j . The results show that the weights of the four types of capital are human capital (0.275), economic capital (0.266), social capital (0.234), and health capital (0.226), as shown in Table 1.

4.3. Measurement Results and Discussion of Multidimensional Relative Poverty

4.3.1. Poverty Incidence below the Income Relative Poverty Line

Based on the research of Xing [62], Shen [63], and Wang [24], this paper uses the household income data of CFPS to calculate the relative poverty lines of 40%, 50%, and 60% of the median income and the incidence of poverty in urban and rural areas. Although China has lifted all the rural absolute poor people out of poverty under the current standard, the unbalanced pattern of urban–rural development has not been fundamentally changed, and there is still a large gap in living standards between urban and rural residents. Therefore, if a nationwide uniform poverty line is set, the population of relative poverty will be concentrated in rural areas, which not only puts pressure on national finances but also hinders the integration of urban and rural areas and excludes a large number of urban relatively poor from social assistance.
Table 2 shows that the ratio of the relative poverty line to the average urban subsistence allowance standard in the same year is 1.43, 1.79, and 2.15, while the ratio of the relative poverty line to the average rural subsistence allowance standard is 0.89, 1.11, and 1.33. The urban ratio is slightly higher than the rural ratio. In addition, from the perspective of relative poverty incidence, the relative poverty line calculated based on the median income of 50% and 60% is relatively high, covering a large population, which will inevitably cause fiscal pressure as a policy target. Based on CFPS data, the relative poverty line of 40% is slightly higher than the average urban subsistence allowance standard and lower than the rural standard. However, according to the Statistical Bulletin on National Economic and Social Development of RPC in 2020, the median per capita disposable income in rural areas is CNY 15,204, 40% of the median per capita income is still slightly higher than the average rural subsistence allowance standard. Therefore, 40% of the median income is the reasonable income relative poverty line. In fact, the per capita income from CFPS data is lower than the per capita income data published by the National Bureau of Statistics in 2020, so the relative poverty incidence and relative poverty population calculated based on this data are slightly higher. However, compared with the poverty rate of the developed EU countries published by the World Bank, such as Belgium, France, Germany, the Netherlands, Italy, and Portugal, which were 12–18% in 2020 [64], the relative poverty rate calculated based on this data are basically maintained within a reasonable range. Furthermore, setting the relative poverty line at 40% of the median per capita income can not only achieve a reasonable linkage with the average standard of urban and rural subsistence allowance standard, but also control the incidence of relative poverty and population size within a reasonable range, so as to adapt to the rational transformation of relative poverty governance policies and the objective conditions of economic and fiscal development of the country.

4.3.2. Single Dimensional Poverty Incidence Rate from a Multidimensional Poverty Perspective

The multidimensional relative poverty situation of households is first reflected in the absence and deprivation of a single indicator. Based on the previous discussion and the calculation of CFPS data, the relative poverty incidence rate of each indicator by urban–rural and regional single indicator is shown in Table 3.
From a national perspective, the main manifestations of relative poverty incidence exceeding 20% are financial assets, livelihood assets, health level, employment proportion, social trust, and social participation. These high indicators are not only due to historical accumulation, but also affected by the epidemic that began at the end of 2019, resulting in widespread health, employment, and social participation issues for residents. The incidence of relative poverty in information acquisition is at the lowest level. As of 2020, the urban and rural network coverage has exceeded 98%. People obtain various effective information through various multimedia devices, and communication and interaction between people are more frequent, effectively reducing the information and transaction costs of ordinary households.
From the perspective of urban and rural areas, the relative deprivation level of urban households in financial assets, livelihood assets, housing expenses, health level, health physique, and educational level is significantly lower than that in rural areas. Among them, financial assets, health level, and educational level have the most significant urban–rural disparities, which are the prominent manifestations of urban–rural economic development level and resource allocation differences. Urban households have a significant advantage in economic capital accumulation and accessibility to public service resources. In other indicators, the relative poverty level in urban areas is slightly higher than that in rural areas, with the largest gap in employment proportion. This indicates that urban households are more susceptible to the overall economic situation, and the proportion of eligible labor force unemployed or leaving the labor market is higher than that in rural areas, as shown in Figure 1.
From a regional perspective, except for livelihood assets, health security, employment proportion, and various indicators of social capital, the relative poverty incidence rates of other indicators in the eastern, central, and western regions have gradually increased, with household income, housing expenses, and educational level showing the most significant regional disparities, as shown in Figure 2. The participation rate of medical insurance in the western region is higher than that in the eastern and central regions, and the degree of relative deprivation is relatively low, which fully reflects the poverty reduction effect of “safeguarding the basic medical security” in the poverty alleviation stage of the western poverty-stricken areas. The relative poverty incidence rate of employment proportion in the central region is significantly higher than that in the eastern and western regions, indicating that the central region lacks policy support compared to the western region, and relatively lag behind the eastern region in the economic development. At the same time, the deprivation level of social capital indicators in the central and western regions is lower than that in the eastern regions, indicating that in the case of relative lack of household economic capital, people are more inclined to use and accumulate social capital to make up for it, so that the household productivity could be improved.

4.3.3. Relative Poverty Status of Multidimensional Indicators

The relative poverty status of households is more reflected in the level of deprivation on multidimensional indicators. Based on the multidimensional deprivation matrix g = g i j 0 of CFPS, the relative poverty incidence rates of urban–rural areas and regions are calculated at different numbers of indicators. In Table 4, I represents the number of relative poverty indicators of household i; I = 0 means that household i has no relative poverty in all indicators, and I = 3 means that household i has relative poverty only in three indicators.
Table 4 shows that with the number of indicators increases, the incidence of relative poverty between urban and rural areas and different regions reaches its maximum at I = 2 , and gradually decreases thereafter, as shown in Figure 3.
Overall, when I > 2 , the incidence of relative poverty gradually decreases, and by I = 5 , except for the western region, it drops to below 10%, which indicates that the relative poverty in the western region is more serious. Multidimensional relative poverty in urban and rural areas and regions is mainly concentrated within 1–4 indicators, accounting for 30.8% of the total number of indicators, with a cumulative relative poverty incidence rate of over 73%. When I > 4, the number of relatively poor households identified will gradually increase in both the breadth and depth of relative poverty. Therefore, it is reasonable to set relative poverty cutoff k as 0.3, which can effectively identify multidimensional relative poverty households. The right skewed distribution curve in Figure 3 clearly illustrates this trend of change. Generally, China’s rapid development and poverty governance practices since the reform and opening up have greatly alleviated multidimensional poverty, but the problem of imbalanced and insufficient development remains prominent, especially in important areas of people’s livelihood such as health, education, and employment.

4.3.4. Multidimensional Relative Poverty Index and Contribution Rates of Various Dimension Indicators

According to the calculation methods of multidimensional relative poverty, this paper calculates the incidence rate H, average deprivation share A, multidimensional relative poverty breadth index M 0 , and multidimensional relative poverty depth index M 1 with different cutoff value k, and decomposes the multidimensional index by urban and rural areas and different regions. Referring to the research of Alkire and Santos [65], this paper sets the cutoff value of multidimensional poverty k = 0.3 and calculates the contribution rate of each dimension indicator to the multidimensional relative poverty index, in order to more accurately identify the main causes of multidimensional relative poverty.
Table 5 lists the multidimensional relative poverty incidence rate H, average deprivation share A, multidimensional relative poverty breadth index M 0 , and multidimensional relative poverty depth index M 1 for Chinese households in 2020, divided by urban and rural areas and different regions.
According to Table 5, as the cutoff value k increases, H, M 0 , and M 1 gradually decrease. When k = 0.7 , H, M 0 , and M 1 decrease to 0, while the average deprivation share A continues to increase. Meanwhile, the decrease in poverty incidence rate is greater than the increase in average deprivation share, thus an overall trend of multidimensional poverty index decreasing with poverty incidence rate is presented.
At the national level, the relative poverty incidence rate is 0.209 when k = 0.3 . The multidimensional relative poverty breadth index and depth index are 0.083 and 0.043, respectively, and according to the China Statistical Yearbook 2021 [66], the total number of households in China in 2020 was 52.269 million, so approximately 10.93 million households are at a relatively poor level. The scale of relative poverty meets the objective conditions for relative poverty governance in the post poverty alleviation era.
From the measurement results of urban and rural areas, H, M 0 , and M 1 in urban areas are all lower than those in rural areas, and the average share of deprivation A gradually approaches equality with the decrease in poverty incidence rate. At different levels of k values, the multidimensional poverty index in rural areas is significantly higher than that in urban areas. Therefore, in the process of solidly promoting common prosperity, the governance of relative poverty in rural areas remains a key focus of policy attention, as shown in Figure 4.
From a regional perspective, at different cutoff values of k, the multidimensional relative poverty incidence rate H, breadth index M 0 , and depth index M 1 show an increasing trend from east to west. The eastern region is at a lower level compared to the whole country, while M 1 in the central region is basically equivalent to the national level. M 0 and M 1 in the western region are both at the highest level, as shown in Figure 5. At k = 0.3 , M 0 and M 1 in the western region are 0.097, and 0.049, respectively, higher than the national level. This fully demonstrates the significant differences in household productivity among the eastern, central, and western regions. Therefore, continuously promoting the accelerated development of the western region, strengthening cooperation between the east and west, and gradually narrowing the development gap are necessary actions to achieve common prosperity.
The specific reasons for the differences in multidimensional relative poverty indices between urban and rural areas and regions can be identified by analyzing the contribution rates of each dimension indicator. Table 6 shows the contribution rates of various dimension indicators in urban and rural areas and regions to the multidimensional relative poverty indices when k = 0.3 . Firstly, from a national perspective, the areas with a contribution rate of close to or higher than 10% to M 0 are household income, health level, and employment level, with the lowest being health physique and information acquisition. The indicators that contribute more than 10% to M 1 are financial assets, livelihood assets, health level, social network, and social participation, which have the most prominent impact on differences in household livelihood capabilities. In order to promote the governance of relative poverty in an orderly manner, at the macro level, it is necessary to focus on the growth of household income and the improvement of health levels and ensure the implementation of stable employment policies. At the micro level, through the reform of the financial and tax and distribution system, it is important to increase the accumulation of residents’ economic and human capital, improve household wealth stock, and gradually narrow the gap in household capital stock.
From the perspective of urban–rural differences, the highest contribution rates to the M 0 of urban households are employment proportion, health level, and household income, which are 12.5%, 11.7%, and 10.4%, respectively. The highest contribution rates of M 0 to rural households are health level, household income, and educational level, which are 14.4%, 8.8%, and 8.7%, respectively. Therefore, improving the health level of urban and rural residents, further expanding the scope of medical insurance, and improving medical insurance standards are the top priorities for relative poverty governance. At the same time, continuously improving employment levels, especially the employment rate of urban households, is a key policy focus for promoting reforms in the field of people’s livelihoods.
The contribution rate of the relative poverty depth index M 1 for urban and rural households is over 10% in terms of financial assets, livelihood assets, health level, social network, and social participation. The contribution rate of various indicators of social capital in rural households is lower than that of urban households, which is closely related to the level of rural economic development, mode of production, and lifestyle. The prominent urban–rural gap is reflected in health, employment, and education, with employment issues being prominent in urban areas and health and education issues being prominent in rural areas.
From the perspective of regional characteristics, the highest contribution rates of M 0 in the eastern region are health level, social network, employment proportion, and household income, which are 12.8%, 9.8%, 9.7%, and 9.4%, respectively. Except for social capital, the central region is the same as the eastern region, while the contribution rate of the western region is ranked from high to low in terms of health, income, and education, which clearly confirms the widespread gap between the western region and the other regions. In terms of the contribution rate of index M 1 , the eastern region is ranked from high to low in social network, social participation, financial assets, and health level. The central region is the same as the eastern region, while the western region is followed by financial assets, health level, and social participation, reaching 14.3%, 13.1%, and 10.9%, respectively. Therefore, there is not only a significant regional gap between the western region and the other regions in various indicators of economic capital and health levels, but also a significant gap within each region.
Overall, the breadth of relative poverty is mainly reflected in various indicators of economic capital, health, employment, and educational level. The depth of relative poverty is mainly reflected in financial assets, health level, and social network indicators, meanwhile showing significant regional and intra-regional disparities. This requires the governance of relative poverty to combine macro regional development policies with micro regulatory policies, and to use the accumulation of household economic capital as an effective means to enhance household productivity and provide corresponding policy support.

5. Governance Mechanism for Multidimensional Relative Poverty under the Goal of Common Prosperity

Through data analysis, there are differences in the breadth and depth of relative poverty between urban and rural areas, and different regions, with an overall significant gap. From a micro perspective, the household capital stock is efficiently allocated according to its marginal return under the market mechanism, thereby obtaining differentiated benefits. The difference in stock leads to the difference in increment, which determines the size of economic opportunities and future benefits for households and their members. From a macro historical perspective, its essence is the accumulation of poverty caused by a single or dual shortage of resource and institutional conditions at different stages of national economic development under the goal of modernization [67]. Therefore, by balancing efficiency and fairness in institutional supply, the capital stock and increment of relatively poor households should be increased, and relatively poor households should receive more policy benefits and economic opportunities. Meanwhile, the governance of relative poverty should be integrated into the macro development system of urban–rural integration and regional coordinated development. The policy opportunities and comparative advantages endowed by the national development plan should be fully utilized to accelerate the economic and social development of rural areas and the central and western regions. Further narrowing the urban–rural and regional disparities remains a priority choice for addressing relative poverty and achieving common prosperity.

5.1. Improve the Capital Accumulation Mechanism for Relatively Impoverished Households

5.1.1. Accelerate the Accumulation of Economic Capital in Relatively Impoverished Households

On the one hand, the income distribution mechanism needs to be improved. Firstly, increase the proportion of labor income in the initial distribution. The low labor and property income of rural residents is the main reason for the widening income gap between urban and rural residents. Therefore, it is necessary to actively implement the employment priority strategy, adjust the minimum wage standard in a timely manner, orderly increase the proportion of labor income in the initial distribution, and ensure the steady growth of income for relatively poor groups [68]. Secondly, improve the redistribution and adjustment mechanism of tax and social security systems. The main measures include exploring the establishment of a new type of property tax system, improving individual progressive income tax, adjusting the large income distribution gap, and reducing the tax burden on middle and low-income groups [69]. In addition, it is necessary to continuously innovate social assistance methods, moderately increase assistance standards based on local financial resources, and improve the income level of relatively impoverished populations through financing and payment mechanisms. Thirdly, leverage the role of social charity. The main measures include widely cultivating the social responsibility awareness of high-income groups and enterprises, strengthening the construction of charitable organizations, enhancing the willingness of donors to participate through institutional reform, and encouraging charitable donors to provide paired assistance to low-income groups.
On the other hand, the asset equity structure needs to be optimized. Firstly, stabilize housing prices. In the wealth of Chinese households, housing assets account for a large proportion and contribute significantly to the increase in household wealth. Therefore, stable housing prices are a basic condition for relatively poor households to maintain their household wealth and avoid debt risks. Besides, it is necessary to explore the imposition of property tax, regulate asset income, ensure the housing needs of low-income groups, and alleviate the degree of inequality in housing areas [70,71]. Secondly, deepen the reform of the land system. The measures include promoting the entry of rural collective construction land into the market, moderately releasing the use rights of homesteads and farmers’ houses, and allowing and encouraging farmers to use idle homesteads and houses to develop the service industry. Thirdly, broaden financial investment and financing channels. It is significant to actively innovate financial products suitable for middle and low-income groups, and provide more effective ways for them to preserve and increase their assets. In addition, it is needed to develop digital inclusive finance, break through spatial limitations, alleviate information asymmetry and other issues, and enhance the sustainability of financial supply [72].

5.1.2. Consolidate the Health Capital of Relatively Impoverished Households

Firstly, improve the quality of health services. The methods include deepening the construction of the public medical and health service system, continuously enriching and expanding service projects and content, improving the mechanism for raising and sharing funds, promoting balanced regional allocation of high-quality medical and health resources, increasing special medical assistance and subsidies for relatively poor households, strengthening health services for vulnerable groups, and comprehensively improving the stock of household health capital.
Secondly, establish a sound health security system. It is needed to accelerate the construction of a multi-level medical security system with basic medical security as the main body and various forms of supplementary insurance and commercial insurance as supplements. In addition, medical insurance subsidies can be provided to the relatively poor population, encouraging them to participate in commercial health insurance, strengthening health management services, and comprehensively improving their risk resistance capability.
Thirdly, optimize a healthy environment. Taking rural revitalization as an important measure to promote the improvement of urban and rural environmental sanitation, continuously improve fitness venues and facilities in rural and underdeveloped areas, and reduce the opportunity cost of people’s health investment. Other methods include promoting the construction of healthy communities, healthy villages and towns, healthy units, and healthy households, achieving harmonious development between humans and nature.

5.1.3. Enhance the Human Capital of Relatively Impoverished Households

Firstly, optimize the spatial layout of educational resources. Considering the distribution of urban and rural population, transportation resources, number of students, and development level, it is necessary to accelerate the balanced layout and orderly flow of county-level education resources. That is, education support policies should be moderately tilted towards rural and underdeveloped areas to reduce the education and living costs of relatively impoverished populations.
Secondly, improve the education assistance mechanism. We need to optimize the funding system for the entire education stage, increasing precise funding for students from relatively poor households and students with disabilities. Besides, it is essential to promote the level of precision in funding, focusing on children from relatively impoverished and marginalized households, to enhance the human capital level of relatively poor households.
Thirdly, strengthen employment and entrepreneurship services and special support. By building a high-quality employment and entrepreneurship service platform, special support will be provided to relatively poor households or households with multiple members, and multi-channel funding will be supplied to establish public welfare employment positions. Financial and tax incentives can also be used to encourage enterprises to absorb labor from relatively poor households, improving the adaptability of relatively poor households to labor market demand.

5.1.4. Expand the Social Capital of Relatively Impoverished Households

Firstly, expand social networks. It is important to encourage relatively impoverished groups to participate widely in social organizations and fully leverage their functions of cooperative production, information sharing, benefit sharing, value realization, and emotional exchange. Meanwhile, it is necessary to develop and strengthen the new rural collective economy, establish and improve cooperatives with poverty alleviation functions, widely absorb relatively poor people, and safeguard their basic employment and social security rights.
Secondly, foster social trust. These measures include improving the legal system and building a fair and just social environment. Especially, it is essential to establish and improve protection and guarantee mechanisms for socially disadvantaged groups, give priority protection in areas such as education, healthcare, employment, and social security.
Thirdly, strengthen policy information dissemination. It is needed to strengthen the construction of policy information platforms and push legal regulations and policy information related to people’s livelihood through multiple channels, so that relatively poor people can engage in social transactions and production under the condition of information equality, thereby reducing transaction costs and increasing the accumulation of social capital.

5.2. Integrated Urban–Rural Development to Alleviate Relative Poverty in Rural Areas

The relative poverty in rural areas is rooted in the dual structure and unbalanced development of urban and rural areas. Urban and rural areas are blood compatible and geographically connected communities of life. Only through urban–rural integration and mutual promotion between industry and agriculture can rural revitalization and healthy urban development be achieved [73]. Therefore, it is necessary to implement the two major strategies of rural revitalization and new urbanization, and to alleviate multidimensional relative poverty through industrial development, factor flow, public services, and green development.

5.2.1. Enhancing Household Livelihood through Industrial Development

On the one hand, the improvement of quality and efficiency of agricultural products needs to be promoted. The methods include deepening the structural reform of the agricultural supply side, adjusting and optimizing the agricultural planting and breeding structure, strengthening advantageous characteristic industries, enhancing the adaptability and flexibility of agricultural product supply, and enabling farmers to benefit from effective market supply.
On the other hand, the transfer of urban overcapacity to rural areas requires selective promotion. For China, it is essential to adapt to local conditions and combine the advantages of rural resources to select emerging industries with strong labor carrying capacity, moderate technological content, and small ecological damage to orderly transfer to rural areas, make good use of rural resource assets, explore new values and functions of agriculture, and absorb surplus urban labor.

5.2.2. Promoting Rural Capital Accumulation through Factor Flow

Firstly, establish a mechanism for rural talent cultivation and mobility. The measures include innovating and improving various forms of vocational skills and employment training mechanisms, vigorously cultivating new types of vocational talents, and guiding and supporting agricultural migrant workers to return to their hometowns for entrepreneurship and employment.
Secondly, improve the mechanism for diversified investment in rural areas. It is necessary to ensure that public finance and financial resources support key areas and weak links such as agricultural green production, sustainable development, rural living environment, and basic public services. Rural resources should be utilized effectively.
Thirdly, strengthen the introduction, innovation, and transformation of agricultural technology. Emerging technologies can promote agricultural development, cultivate agricultural professionals, and increase the accumulation of rural human capital.

5.2.3. Accumulating Rural Development Momentum through Equalization of Public Services

Based on the types of public services, funding, and supply method, while promoting the integration of basic public services between urban and rural areas, it is important to increase the supply of services such as rural education, medical care, and elderly care to meet the differentiated and high-quality service needs of people. Also, it is needed to establish and improve institutional arrangements such as the basic public service list system, institutional integration, financial support mechanism, and vulnerable group protection mechanism, in order to accumulate momentum for rural development [74].

5.2.4. Accumulating Rural Development Capital through Ecological Optimization

Firstly, taking rural revitalization as an opportunity to develop green industries. Based on the enrichment of ecological resources, layout corresponding industries and explore the potential value of historical culture, leisure and entertainment, health, and wellness carried by rural ecological resources, so as to enable the relatively poor population in rural areas to obtain actual benefits in realizing the value of ecological resources.
Secondly, it is incumbent to promote innovation in the poverty reduction system of the new rural collective economy, using it as the organizational foundation for ecological poverty alleviation, integrating dispersed resources and trading entities, and achieving the transformation of resource value and reasonable distribution of benefits [67].
Thirdly, it is compulsory to continue to promote ecological restoration projects, explore the supply mechanism of high-quality ecological products and services, achieve a positive interaction between ecological restoration and economic development, and accumulate rural natural capital.

5.3. Regional Coordinated Development Promotes the Rise of the Central and Western Regions

Regional relative poverty is one of the main manifestations of poverty at the macro level. Constrained by factor endowments, natural conditions, spatial location, and capital accumulation, the breadth and depth of multidimensional relative poverty in the central and western regions are significantly higher than those in the eastern regions, which is the result of imbalanced and insufficient regional economic development in China. The implementation of regional coordinated development strategies should focus on accelerating the development of the central and western regions, strengthening regional mutual assistance and cooperation, and deepening mechanism innovation to alleviate relative poverty in the region.

5.3.1. Promoting High-Quality Development in the Central and Western Regions

On the one hand, the development of the western region needs to continue to increase. Based on the ecological disadvantages and resource advantages of the western region, it is necessary to explore the path of green development, reduce the vulnerability of the ecological environment, and improve the efficiency of resource development and utilization. Relying on the “the Belt and Road” national strategy, it is essential to develop high-quality service industries, guide the orderly flow of production factors to the west, gradually narrow the gap between regions, and complement the weak points in the field of people’s livelihood.
On the other hand, the rise of the central region needs to be promoted. The main path includes continuously improving the independent innovation capability and industrial technology level of the central region, cultivating and developing advanced manufacturing bases, and improving the ability of new industries in the eastern region to undertake transfer and radiate to the western region. Furthermore, it can comprehensively enhance the comprehensive strength and competitiveness of the central region, and fundamentally alleviate relative poverty in the region.

5.3.2. Strengthening Regional Mutual Assistance and Cooperation

On the one hand, it is necessary to increase the cooperation between the eastern and western regions in poverty alleviation. Policy incentives can be used to encourage enterprises to invest in relatively impoverished areas in the central and western regions, orderly undertake and transfer new industries, and provide support for industrial layout, factor flow, technology support, employment promotion, and people’s livelihood improvement in the central and western regions. On the other hand, it is necessary to strengthen pairing assistance. Education, healthcare, employment, and consumption poverty alleviation can continue to be carried out, providing more educational support, medical assistance, and employment opportunities for relatively impoverished households in the central and western regions, and supporting the improvement and increase in products with distinctive characteristics in the central and western regions, as well as the expansion of sales channels.

5.3.3. Innovating Regional Collaboration Mechanism

Firstly, top-level policy support needs to be strengthened. Measures involve strengthening policy incentives and preferential policies in key areas, especially major projects and infrastructure construction in areas such as ecology, transportation, and people’s livelihoods, so as to cultivate and stimulate regional development momentum.
Secondly, the mechanism for market integration development needs to be sound. It can promote policy innovation in the orderly flow of labor between urban and rural areas and different regions and promote the urbanization process of agricultural transfer population. In addition, it is necessary to promote innovation in land rights and the system of interests, and then achieve reasonable allocation of land elements between regions.
Thirdly, the interest compensation mechanism needs to be improved. Based on geographical characteristics and location functions, it will benefit sustainable development to explore pilot ecological compensation methods and mechanisms and resource sharing and benefit sharing mechanisms, inject sustained financial support for ecological protection and restoration, guide low-income groups to participate in ecological industry development, and increase their operating and property income [75]. The above measures can help achieve mutual promotion between ecological protection and economic development and promote achieving the goal of common prosperity.

6. Conclusions

This research provides a theoretical analysis of the capital composition of household productivity, and subsequently constructs a system of indicators for household productivity. According to empirical results, there are significant differences in various dimensional indicators between urban and rural areas, between and within regions. The incidence of unidimensional poverty is mainly reflected in several aspects such as household financial assets, livelihood assets, health level, and employment proportion. The multidimensional relative poverty indices H , M 0 , and M 1 are higher in rural areas than in urban areas except for the social capital dimension, and higher in the central and western regions than in the eastern regions. Meanwhile, the main contributors to each index are economic capital, health, employment, and educational levels, with education issues being most prominent in rural and western regions. Based on the measurement results, this paper believes that the first steps are to consolidate and improve the capital stock and increment of relatively poor households and enhance the livelihood capabilities of households and their members. Additionally, policy support should be provided to relatively impoverished areas through rural revitalization strategies, new urbanization strategies, and regional coordinated development strategies, gradually achieving balanced development between urban and rural areas and different regions, and solidly advancing towards the goal of common prosperity.

Author Contributions

Conceptualization, X.H. and H.X.; methodology, X.H. and X.L.; software, X.H. and X.L.; validation, X.H., H.X. and X.L.; writing—original draft preparation, X.H.; writing—review and editing, X.L.; visualization, X.H.; supervision, H.X.; project administration, H.X. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by National Office of Philosophy and Social Sciences (2021 The National Social Science Fund of China, Major projects of social science academic societies). Grant number: 21STA002.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

The data presented in this study are available on request from the corresponding author.

Conflicts of Interest

The authors declare no conflicts of interest.

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Figure 1. Relative poverty incidence rate in urban and rural areas (%).
Figure 1. Relative poverty incidence rate in urban and rural areas (%).
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Figure 2. Regional relative poverty incidence rate (%).
Figure 2. Regional relative poverty incidence rate (%).
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Figure 3. Relative poverty incidence rate of multidimensional indicators in urban and rural areas and regions.
Figure 3. Relative poverty incidence rate of multidimensional indicators in urban and rural areas and regions.
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Figure 4. The breadth and depth of multidimensional relative poverty in urban and rural areas.
Figure 4. The breadth and depth of multidimensional relative poverty in urban and rural areas.
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Figure 5. The breadth and depth of multidimensional relative poverty in the eastern, central, and western regions.
Figure 5. The breadth and depth of multidimensional relative poverty in the eastern, central, and western regions.
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Table 1. Indicators, cutoff values, and weights of multidimensional relative poverty.
Table 1. Indicators, cutoff values, and weights of multidimensional relative poverty.
DimensionsIndicatorsCutoff ValuesWeights
Economic capital
(0.266)
Household incomeThe per-capita net income of households in urban and rural areas is below 40% of the median.0.085
Financial assetsThe total financial assets of households in urban and rural areas are below 40% of the median.0.047
Livelihood assets Household durable goods value in urban and rural areas is below 40% of the median.0.052
Housing expensesHousing expenditure in urban and rural areas is below 40% of the median.0.082
Health capital (0.226)Health levelAt least one household member rated themselves as unhealthy.0.087
Health securityAt least one household member aged 16 and above has not participated in medical insurance.0.082
Healthy physiqueAt least one household member aged 16 and above has a BMI of less than 18.5.0.057
Human capital (0.275)Employment proportionAt least one household member aged 16–60 is unemployed or has withdrawn from the labor market.0.109
Educational levelThe average length of education for household members aged 16–60 is less than 6 years.0.092
Information acquisition The average acquisition of household member information is less than 3.0.074
Social capital (0.234)Social networkThere is no gift fund expenditure in the household.0.087
Social trustThe average trust level of household members is less than 5.0.075
Social participationHousehold members have not participated in any social organizations.0.072
Table 2. Relative poverty incidence below the relative poverty line in CFPS.
Table 2. Relative poverty incidence below the relative poverty line in CFPS.
Different Proportions of Median Net Income per CapitaUrbanRural
Relative Poverty Line (CNY)The Ratio to the Average Urban Subsistence Allowance StandardIncidence of Relative Poverty (%)Relative Poverty Line (CNY)The Ratio to the Average Rural Subsistence Allowance StandardIncidence of Relative Poverty (%)
40%11,6481.4315.565300.60.8914.79
50%14,5601.7922.026625.81.1120.11
60%17,4722.1528.757950.91.3326.73
The average urban subsistence allowance standard in 2020 was CNY 8131.2 per person per year, while the average rural subsistence allowance standard was CNY 5962.3 per person per year. According to the China Statistical Yearbook 2021, the total number of urban households was 33.604 million and average household population size was 2.6, while the total number of rural households was 18.665 million and average household population size was 2.7 in 2020, by which the number of relatively poor households and the size of the population can be calculated.
Table 3. The incidence rate of single indicator relative poverty in urban and rural areas and regions of China (%).
Table 3. The incidence rate of single indicator relative poverty in urban and rural areas and regions of China (%).
DimensionsIndicatorsNationalUrbanRuralEastCentralWest
Economic capitalHousehold income16.8715.5614.7912.8416.6723.37
Financial assets36.9435.0740.7930.5339.8543.88
Livelihood assets 28.2232.8734.8728.1026.4830.08
Housing expenses17.4414.7418.5212.9118.0923.78
Health capitalHealth level30.8125.8736.5827.4231.4935.32
Health security16.8417.2316.3819.4116.7812.93
Healthy physique14.7212.7417.0412.2313.3719.94
Human capitalEmployment proportion20.5422.9517.7219.4124.6318.02
Educational level12.576.8919.228.089.8822.28
Information acquisition 6.336.386.286.146.476.52
Social capitalSocial network14.1815.0013.2219.0711.379.54
Social trust20.2621.2819.0621.1620.6718.39
Social participation21.7721.6921.8626.6919.3216.74
Table 4. Relative poverty incidence rate of multidimensional indicators in urban and rural areas and different regions (%).
Table 4. Relative poverty incidence rate of multidimensional indicators in urban and rural areas and different regions (%).
INationalUrbanRuralEastCentralWest
011.1212.919.0212.6710.938.91
119.9221.1418.5021.2020.2117.64
221.9222.2621.5121.8722.2821.61
318.0017.0019.1717.2118.1919.04
413.6112.7114.6712.8613.3115.06
58.257.369.297.547.5410.13
64.454.294.634.214.165.12
71.911.662.201.662.351.84
80.600.480.730.570.640.59
90.160.170.160.140.280.07
100.050.020.090.050.110.00
110.010.000.020.020.000.00
Table 5. Multidimensional relative poverty indices of urban and rural areas and regions with different cutoff values.
Table 5. Multidimensional relative poverty indices of urban and rural areas and regions with different cutoff values.
kNationalUrbanRural
HAM0M1HAM0M1HAM0M1
0.10.7000.2540.1780.0900.6840.2480.1700.0850.7370.2580.1900.096
0.20.4250.3200.1360.0700.3960.3190.1260.0640.4630.3200.1480.076
0.30.2090.3690.0830.0430.1880.3960.0750.0380.2990.3940.0900.047
0.40.0810.4780.0380.0200.0740.4750.0350.0190.0860.4780.0410.022
0.50.0240.5650.0140.0070.0200.5610.0110.0060.0260.5660.0150.008
0.60.0050.6680.0030.0020.0040.6520.0030.0010.0050.6690.0030.002
0.70.0010.7710.0010.0000.0000.7520.0000.0000.0010.7670.0010.001
kEastCentralWest
HAM0M1HAM0M1HAM0M1
0.10.6700.2490.1670.0870.7040.2520.1770.0870.7420.2630.1950.095
0.20.3950.3170.1250.0670.4130.3220.1330.0670.4820.3220.1550.077
0.30.1880.3950.0740.0400.2020.4000.0810.0410.2470.3930.0970.049
0.40.0720.4770.0340.0190.0790.4850.0380.0200.0960.4720.0450.023
0.50.0210.5700.0120.0060.0270.5710.0150.0080.0260.5520.0150.008
0.60.0040.6790.0030.0020.0070.6670.0040.0020.0030.6490.0020.001
0.70.0010.8080.0010.0000.0020.7520.0010.0010.0000.7150.0000.000
Table 6. The contribution rate of indicators from various dimensions of urban and rural areas and different regions to the relative poverty indices.
Table 6. The contribution rate of indicators from various dimensions of urban and rural areas and different regions to the relative poverty indices.
DimensionsIndicatorsNationalUrbanRural
M 0 M 1 M 0 M 1 M 0 M 1
Economic capitalHousehold income10.68.610.48.48.86.8
Financial assets8.213.68.013.18.213.9
Livelihood assets 7.810.88.611.98.511.1
Housing expenses8.77.77.56.48.77.3
Total35.340.734.539.834.239.1
Health capitalHealth level13.112.611.711.414.414.0
Health security6.62.26.82.46.52.2
Healthy physique3.61.63.21.33.81.7
Total23.316.421.715.124.717.9
Human capitalEmployment proportion9.84.312.55.68.63.7
Educational level7.54.95.33.08.76.1
Information acquisition 2.51.72.71.92.31.6
Total19.810.920.510.519.611.4
Social capitalSocial network7.314.18.115.77.013.5
Social trust7.24.17.74.37.44.2
Social participation7.113.77.614.87.113.8
Total21.631.923.434.821.531.5
DimensionsIndicatorsEastCentralWest
M 0 M 1 M 0 M 1 M 0 M 1
Economic capitalHousehold income9.47.310.28.612.410.1
Financial assets7.812.58.414.68.514.3
Livelihood assets 7.910.87.711.07.710.8
Housing expenses7.56.28.77.810.19.4
Total32.636.835.042.038.744.6
Health capitalHealth level12.811.913.513.213.313.1
Health security7.72.66.82.35.11.7
Healthy physique3.31.43.51.54.22.0
Total23.815.923.817.022.616.8
Human capitalEmployment proportion9.74.111.45.18.33.7
Educational level5.63.05.83.911.28.3
Information acquisition 2.21.42.61.82.61.9
Total17.58.519.810.822.113.9
Social capitalSocial network9.818.26.412.65.210.3
Social trust7.54.28.24.75.93.3
Social participation8.816.46.713.25.510.9
Total26.138.821.330.516.624.5
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He, X.; Xi, H.; Li, X. Multi-Dimensional Decomposition, Measurement, and Governance Mechanism of Relative Poverty in Chinese Households under the Goal of Common Prosperity: Empirical Analysis Based on CFPS2020 Data. Sustainability 2024, 16, 5181. https://doi.org/10.3390/su16125181

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He X, Xi H, Li X. Multi-Dimensional Decomposition, Measurement, and Governance Mechanism of Relative Poverty in Chinese Households under the Goal of Common Prosperity: Empirical Analysis Based on CFPS2020 Data. Sustainability. 2024; 16(12):5181. https://doi.org/10.3390/su16125181

Chicago/Turabian Style

He, Xuming, Heng Xi, and Xianbo Li. 2024. "Multi-Dimensional Decomposition, Measurement, and Governance Mechanism of Relative Poverty in Chinese Households under the Goal of Common Prosperity: Empirical Analysis Based on CFPS2020 Data" Sustainability 16, no. 12: 5181. https://doi.org/10.3390/su16125181

APA Style

He, X., Xi, H., & Li, X. (2024). Multi-Dimensional Decomposition, Measurement, and Governance Mechanism of Relative Poverty in Chinese Households under the Goal of Common Prosperity: Empirical Analysis Based on CFPS2020 Data. Sustainability, 16(12), 5181. https://doi.org/10.3390/su16125181

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