Since 2000, the share of people living in extreme poverty in rural China has been constantly decreasing. In *************, the Chinese government announced that - based on the current definition of poverty - all residents in China have been relieved from extreme poverty. In the past, extreme poverty had been more common in western and central parts of China, and in these regions the number of poor households is still considerably higher today.

China's progress in poverty reduction over the last 25 years is enviable. One cannot fail to be impressed by what this vast nation of 1.3 billion people has achieved in so little time. In terms of a wide range of indicators, the progress has been remarkable. Poverty in terms of income and consumption has been dramatically reduced. Progress has also been substantial in terms of human development indicators. Most of the millennium development goals have either already been achieved or the country is well on the way to achieving them. As a result of this progress, the country is now at a very different stage of development than it was at the dawn of the economic reforms at the beginning of the 1980s. China's poverty reduction performance has been even more striking. Between 1981 and 2004, the fraction of the population consuming below this poverty line fell from 65 percent to 10 percent, and the absolute number of poor fell from 652 million to 135 million, a decline of over half a billion people. The most rapid declines in poverty, in both the poverty rate and the number of poor, occurred during the 6th, 8th, and 10th plans. During the 7th plan period the number of poor actually rose, while in the 9th plan period, the poverty rate declined only marginally. But the pace of poverty reduction resumed between 2001 and 2004 and there are indications that during the first couple of years of the 11th plan poverty has continued to decline rapidly. The most recent official estimate of rural poverty in China for 2007 puts the number of poor at 14.79 million, or less than 2 percent of the rural population. While there is no official urban poverty line, estimates by others have found poverty levels in urban areas to be negligible using an urban poverty line that is comparable to the official poverty line for rural areas. These estimates thus suggest that only about 1 percent of China's population is currently in extreme poverty. Notwithstanding this tremendous success, the central thesis of this report is that the task of poverty reduction in many ways continues and in some respects has become more demanding.

In 2024, the average annual per capita disposable income of rural households in China was approximately ****** yuan, roughly ** percent of the income of urban households. Although living standards in China’s rural areas have improved significantly over the past 20 years, the income gap between rural and urban households is still large. Income increase of China’s households From 2000 to 2020, disposable income per capita in China increased by around *** percent. The fast-growing economy has inevitably led to the rapid income increase. Furthermore, inflation has been maintained at a lower rate in recent years compared to other countries. While the number of millionaires in China has increased, many of its population are still living in humble conditions. Consequently, the significant wealth gap between China’s rich and poor has become a social problem across the country. However, in recent years rural areas have been catching up and disposable income has been growing faster than in the cities. This development is also reflected in the Gini coefficient for China, which has decreased since 2008. Urbanization in China The urban population in China surpassed its rural population for the first time in 2011. In fact, the share of the population residing in urban areas is continuing to increase. This is not surprising considering remote, rural areas are among the poorest areas in China. Currently, poverty alleviation has been prioritized by the Chinese government. The measures that the government has taken are related to relocation and job placement. With the transformation and expansion of cities to accommodate the influx of city dwellers, neighboring rural areas are required for the development of infrastructure. Accordingly, land acquisition by the government has resulted in monetary gain by some rural households.

Per capita gross domestic product (GDP) of cities in China varies tremendously, mainly depending on the location of the city. Cities with the highest per capita GDP are mainly to be found in coastal provinces in East China and in South China, like Guangdong province. The poorest cities are located in the still less developed western parts of China, like Gansu province, or in the Chinese rust belt in Northeastern China, like Heilongjiang province.

Statistics of spatial relative poverty in various regions in China.

This report and related data update district-level poverty maps for Laos using the small area estimation (SAE) technique and the most recent Lao Expenditure and Consumption Survey 2018–2019 (LECS 6) and the Population and Housing Census 2015 (PHC 4). On the one hand, LECS collects detailed information on household expenditures required for estimating monetary poverty but limits poverty estimation below the provincial level. On the other hand, PHC collects data from every household but does not include household expenditures as this data is generally too costly and time-consuming to include. The SAE technique combines two sources of data and produces monetary poverty indicators at the district level. This report presents the SAE results as well as poverty estimates and poverty maps at the district level. The three key findings are: (i) there is a large variation in poverty rates across districts within the same province; (ii) poverty is high in districts located in mountainous areas bordering Vietnam and low in districts located on the Mekong River plain and areas bordering China; and (iii) districts with the highest number of poor people are mainly located in Savannakhet, Oudomxay, and Saravan.

In 2024, the annual per capita gross domestic product (GDP) in different provinces, municipalities, and autonomous regions in China varied from approximately 228,200 yuan in Beijing municipality to roughly 52,800 yuan in Gansu province. The average national per capita GDP crossed the threshold of 10,000 U.S. dollars in 2019 and reached around 95,700 yuan in 2024. Regional economic differences in China The level of economic development varies considerably in different parts of China. Four major geographic and economic regions can be discerned in the country: The economically advanced coastal regions in the east, less developed regions in Northeast and Central China, and the developing regions in the west. This division has deep historical roots reflecting the geography of each region and their political past and present. Furthermore, regional economic development closely correlates with regional urbanization rates, which closely resembles the borders of the four main economic regions. Private income in different parts of China Breaking the average income figures further down by province, municipality, or autonomous region reveals that the average disposable income in Shanghai or Beijing is on average more than three times higher than in Tibet or Gansu province. In rural areas, average disposable income is often only between one third and one half of that in urban areas of the same region. Accordingly, consumer expenditure per capita in urban areas reaches the highest levels in Shanghai, Beijing, and the coastal regions of China.

Abstract copyright UK Data Service and data collection copyright owner. This study investigates the alarming rise of urban poverty in China; in particular the patterns of urban poverty and the institutional causes are examined. The researchers look for evidence of institutional innovations that have emerged as individuals and organisations seek to negotiate more secure access to vital civic goods and services. A case study approach was used due to the complexity of the issue and the size of the Chinese urban population. Six cities were chosen and four neighbourhoods in each city were investigated. These cities were distributed in the costal, central and western region respectively, including Guangzhou, Nanjing, Harbin, Wuhan, Kumin, and Xi’an. Further information is available from the ESRC Award webpage. Main Topics: The questionnaire has sections on:demographic informationhousehold income and expendituresocial benefits/welfarehousingemployment situationneighbourhood profilecommuting and relocation One-stage stratified or systematic random sample Face-to-face interview

There are significant differences in energy footprints among individual households. This study uses an environmentally extended input-output approach to estimate the per capita household energy footprint (PCHEF) of 10 different income groups in China’s 30 provinces and analyzes the heterogeneity of household consumption categories, and finally measures the energy equality of households in each province by measuring the energy footprint Gini coefficient (EF-Gini). It is found that the energy footprint of the top 10% income households accounted for about 22% of the national energy footprint in 2017, while the energy footprint of the bottom 40% income households accounted for only 24%. With the growth of China’s economy, energy footprint inequality has declined spatially and temporally. Firstly, wealthier coastal regions have experienced greater convergence in their energy footprint than poorer inland regions. Secondly, China’s household EF-Gini has declined from 0.38 in 2012 to 0.36 in 2017. This study shows that China’s economic growth has not only raised household income levels, but also reduced energy footprint inequality.

This paper develops a multidimensional poverty index (MPI) evaluation system using multiple measures. We use the China Family Panel Study (CFPS) data to build balanced panel data from 2012 to 2018. Employing the probit model to analyze the impact of land transfer on relative poverty incidence, as well as utilizing the two-way fixed effects model and the logit model, we approach the issue from the perspective of multidimensional relative poverty identification. Our study indicates a decrease in relative poverty among rural households since 2012. Nonetheless, the overall incidence of relative poverty among rural households in China remains high at 20.6%, highlighting the severity of this issue in rural China. Moreover, we examine the heterogeneity of the poverty reduction effects of land transfer-in and land transfer-out. Land transfer can significantly reduce the incidence of relative poverty among rural households, with distinct mechanisms for land transfer-in and land transfer-out. Land transfer-in primarily reduces the relative poverty incidence of rural households through the education, housing, and land dimensions, while land transfer-out focuses on the quality-of-life dimension. Overall, land transfer-out has a more significant poverty reduction effect than land transfer-in. Furthermore, our study reveals that the reduction effect of land transfer on the incidence of relative poverty among rural households persists for at least two years, but by the fourth year, this effect disappears.

China's dramatic economic and educational changes over the past 20 years have stimulated concerns about the education of children in rural areas. Recent empirical studies give evidence of growing disparities in educational opportunities between urban and rural areas and socio-economic and geographic inequities in basic-level educational participation within rural areas. These studies also point to a persisting gender gap in enrollment and to the disproportionate impact of poverty on girls' educational participation (Hannum 1998b; Zhang 1998). This study focused on the influence of poverty on the schooling of 11 to 14 year-old children in rural Gansu, an interior province in Northwest China characterized by high rates of rural poverty and a substantial dropout problem. Substantively, this study was innovative in adopting an integrated approach: it focused on the community, family, and school contexts in which children are educated. Methodologically, the study combined information on children's academic performance and school characteristics, with a household-based sample that allowed examination of the academic experiences of children who have left the education system as well as those who have persisted in it. Finally, the project was the baseline wave for the first large-scale, longitudinal study devoted to education and social inequality conducted in rural China. Results of this study contribute to an understanding of basic social stratification processes and provide insights for developing intervention strategies to improve educational access and effectiveness in rural China. Wave 1 of this study (2000) has been archived and is available for download at ICPSR-DSDR. For information about Waves 2-4 (2004, 2007, 2009), please see the Gansu Survey of Children and Families Web site.

This paper develops a multidimensional poverty index (MPI) evaluation system using multiple measures. We use the China Family Panel Study (CFPS) data to build balanced panel data from 2012 to 2018. Employing the probit model to analyze the impact of land transfer on relative poverty incidence, as well as utilizing the two-way fixed effects model and the logit model, we approach the issue from the perspective of multidimensional relative poverty identification. Our study indicates a decrease in relative poverty among rural households since 2012. Nonetheless, the overall incidence of relative poverty among rural households in China remains high at 20.6%, highlighting the severity of this issue in rural China. Moreover, we examine the heterogeneity of the poverty reduction effects of land transfer-in and land transfer-out. Land transfer can significantly reduce the incidence of relative poverty among rural households, with distinct mechanisms for land transfer-in and land transfer-out. Land transfer-in primarily reduces the relative poverty incidence of rural households through the education, housing, and land dimensions, while land transfer-out focuses on the quality-of-life dimension. Overall, land transfer-out has a more significant poverty reduction effect than land transfer-in. Furthermore, our study reveals that the reduction effect of land transfer on the incidence of relative poverty among rural households persists for at least two years, but by the fourth year, this effect disappears.

This statistic shows the inequality of income distribution in China from 2005 to 2023 based on the Gini Index. In 2023, China reached a score of ************ points. The Gini Index is a statistical measure that is used to represent unequal distributions, e.g. income distribution. It can take any value between 1 and 100 points (or 0 and 1). The closer the value is to 100 the greater is the inequality. 40 or 0.4 is the warning level set by the United Nations. The Gini Index for South Korea had ranged at about **** in 2022. Income distribution in China The Gini coefficient is used to measure the income inequality of a country. The United States, the World Bank, the US Central Intelligence Agency, and the Organization for Economic Co-operation and Development all provide their own measurement of the Gini coefficient, varying in data collection and survey methods. According to the United Nations Development Programme, countries with the largest income inequality based on the Gini index are mainly located in Africa and Latin America, with South Africa displaying the world's highest value in 2022. The world's most equal countries, on the contrary, are situated mostly in Europe. The United States' Gini for household income has increased by around ten percent since 1990, to **** in 2023. Development of inequality in China Growing inequality counts as one of the biggest social, economic, and political challenges to many countries, especially emerging markets. Over the last 20 years, China has become one of the world's largest economies. As parts of the society have become more and more affluent, the country's Gini coefficient has also grown sharply over the last decades. As shown by the graph at hand, China's Gini coefficient ranged at a level higher than the warning line for increasing risk of social unrest over the last decade. However, the situation has slightly improved since 2008, when the Gini coefficient had reached the highest value of recent times.

With rising social inequality in China, housing insecurity in informal migrant settlements known as chengzhongcun (urban villages) became a significant issue. In the suburbs of Beijing, former villages are turned into migrants' production sites; in the peri-urban areas of Shanghai, co-renting in the same room has become highly controversial; in Guangzhou, urban villages are becoming a 'thriving' world of their own, lacking basic infrastructure. Are these migrant settlements slums? According to the operational definition by UN-HABITAT, these settlements can indeed be viewed as slums. How different are they from slums in other developing countries? The project investigates the dynamics of migrant village formation, examine redevelopment practices and policies, and to identify the scope for progressive upgrading as an alternative approach. The project samples 15 migrant villages in three major cities (Beijing, Shanghai and Guangzhou) in China and applies qualitative and quantitative methods to identify the housing tenure, socioeconomic profiles, landlords' self construction tactics, migrants' coping strategies, and existing and new institutions as appropriate vehicles for in-situ redevelopment. The project aims to inform Chinese policy makers and provide learning feedback to the wider international development community, offering new experiences in coping with the 'challenge of slums'. The data was collected through face to face interview in Beijing, Shanghai and Guangzhou in 2010. For each city, 20 'urban villages' were randomly selected from the list of villages. 20 households were randomly selected by way of a random start address with fixed intervals. This address-based approach is widely used in Chinese household surveys because there is no official list for migrants. The address-based approach is able to account for the migrant population better than other household registers. In total, we collected 1208 valid questionnaires.

Principal Component Analysis Data,Based on the this analysis, the impacts of various factors on the vulnerability of social ecosystems are analyzed.

Abstract

The World Bank is interested in gauging the views of clients and partners who are either involved in development in China or who observe activities related to social and economic development. The World Bank Country Assessment Survey is meant to give the Bank's team that works in China, more in-depth insight into how the Bank's work is perceived. This is one tool the Bank uses to assess the views of its critical stakeholders. With this understanding, the World Bank hopes to develop more effective strategies, outreach and programs that support development in China. The World Bank commissioned an independent firm to oversee the logistics of this effort in China.

The survey was designed to achieve the following objectives: - Assist the World Bank in gaining a better understanding of how stakeholders in China perceive the Bank; - Obtain systematic feedback from stakeholders in China regarding: · Their views regarding the general environment in China; · Their perceived overall value of the World Bank in China; · Overall impressions of the World Bank as related to programs, poverty reduction, personal relationships, effectiveness, knowledge base, collaboration, and its day-to-day operation; and · Perceptions of the World Bank's communication and outreach in China. - Use data to help inform the China country team's strategy.

Geographic coverage

National

Analysis unit

Stakeholder

Universe

Stakeholders of the World Bank in China

Kind of data

Sample survey data [ssd]

Sampling procedure

December 2011 thru March 2012, 518 stakeholders of the World Bank in China were invited to provide their opinions on the Bank's assistance to the country by participating in a country survey. Participants in the survey were drawn from among employees of a ministry or ministerial department of central government; local government officials or staff; project management offices at the central and local level; the central bank; financial sector/banks; NGOs; regulatory agencies; state-owned enterprises; bilateral or multilateral agencies; private sector organizations; consultants/contractors working on World Bank supported projects/programs; the media; and academia, research institutes or think tanks.

Mode of data collection

Face-to-face [f2f]

Research instrument

The Questionnaire consists of 8 Sections: 1. Background Information: The first section asked respondents for their current position; specialization; familiarity, exposure to, and involvement with the Bank; and geographic location.

1. General Issues facing China: Respondents were asked to indicate what they thought were the most important development priorities, which areas would contribute most to poverty reduction and economic growth in China, as well as rating their perspective on the future of the next generation in China.

2. Overall Attitudes toward the World Bank: Respondents were asked to rate the Bank's overall effectiveness in China, the extent to which the Bank's financial instruments meet China's needs, the extent to which the Bank meets China's need for knowledge services, and their agreement with various statements regarding the Bank's programs, poverty mission, relationships, and collaborations in China. Respondents were also asked to indicate the areas on which it would be most productive for the Bank to focus its resources and research, what the Bank's level of involvement should be, and what they felt were the Bank's greatest values and greatest weaknesses in its work.

3. The Work of the World Bank: Respondents were asked to rate their level of importance and the Bank's level of effectiveness across fifteen areas in which the Bank was involved, such as helping to reduce poverty and encouraging greater transparency in governance.

4. The Way the World Bank does Business: Respondents were asked to rate the Bank's level of effectiveness in the way it does business, including the Bank's knowledge, personal relationships, collaborations, and poverty mission.

5. Project/Program Related Issues: Respondents were asked to rate their level of agreement with a series of statements regarding the Bank's programs, day-to-day operations, and collaborations in China.

6. The Future of the World Bank in China: Respondents were asked to rate how significant a role the Bank should play in China's development and to indicate what the Bank could do to make itself of greater value and what the greatest obstacle was to the Bank playing a significant role in China.

7. Communication and Outreach: Respondents were asked to indicate where they get information about development issues and the Bank's development activities in China, as well as how they prefer to receive information from the Bank. Respondents were also asked to indicate their usage of the Bank's website and PICs, and to evaluate these communication and outreach efforts.

Response rate

A total of 207 stakeholders participated in the country survey (40%).

ObjectiveThis study investigates the determinants of medical impoverishment among China's rural near-poor, aiming to enhance public health services and establish preventative and monitoring systems.MethodsUsing China Family Panel Studies and World Bank methods, we categorized rural populations and calculated their 2020 Poverty Incidence (PI) and Poverty Gap (PG), with impoverishing health expenditures (IHE) as the primary indicator. We analyzed the data from 2016 to 2020 using a conditional fixed-effects multinomial logit model and 2020 logistic regression to identify factors influencing medical impoverishment risk.Results(1) In 2020, the near-poor in China faced a PI of 16.65% post-health expenditures, 8.63 times greater than the non-poor's PI of 1.93%. The near-poor's Average Poverty Gap (APG) was CNY 1,920.67, notably surpassing the non-poor's figure of CNY 485.58. Health expenses disproportionately affected low-income groups, with the near-poor more prone to medical impoverishment. (2) Disparities in medical impoverishment between different economic household statuses were significant (P < 0.001), with the near-poor being particularly vulnerable. (3) For rural near-poor households in China, those with over six members faced a lower risk of medical impoverishment compared to those with three or fewer. Unmarried individuals had a 7.1% reduced risk of medical impoverishment relative to married/cohabiting counterparts. Unemployment was associated with a 9% increased risk. A better self-rated health status was linked to a lower probability of IHE, with the “very healthy” reporting a 25.8% lower risk than those “unhealthy.” Chronic disease sufferers in the near-poor and non-poor categories were at an increased risk of 12 and 1.4%, respectively. Other surveyed factors, including migrant status, age, insurance type, gender, educational level, and recent smoking or drinking, were not statistically significant (P > 0.05).ConclusionRural near-poor in China are much more susceptible to medical impoverishment, influenced by specific socio-economic factors. The findings advocate for policy enhancements and health system reforms to mitigate health poverty. Further research should extend to urban areas for comprehensive health poverty strategy development.

Based on the characteristics of underdeveloped areas, this paper selects the panel data of 15 underdeveloped counties in Anhui Province from 2013 to 2019 and uses the panel threshold model to empirically analyze the sustainability of rural tourism development. The results show that: (1) Rural tourism development has a non-linear positive impact on poverty alleviation in underdeveloped areas and has a double threshold effect. (2) When the poverty rate is used to express the poverty level, it can be found that the development of rural tourism at a high level can significantly promote poverty alleviation. (3) When the number of poor people is used to express the poverty level, it can be found that the poverty reduction effect shows a marginal decreasing trend with the phased improvement of the development level of rural tourism. (4) The degree of government intervention, industrial structure, economic development, and fixed asset investment play a more significant role in poverty alleviation. Therefore, we believe that we need to actively promote rural tourism in underdeveloped areas, establish a mechanism for the distribution and sharing of rural tourism benefits, and form a long-term mechanism for rural tourism poverty reduction.

The dataset underpins a study on "Social Capital and the Effectiveness of Land Use Policies: Evidence from Rural China," drawing from the 17 Provinces Rural Land Survey by Renmin University of China. This research navigates the intricacies of land use policy effectiveness in rural China, underpinned by the significant reforms initiated by the 1986 Constitution allowing transactions of land use rights. These reforms enabled local governments to lease land use rights to the private sector, significantly contributing to fiscal revenues and fostering economic development and urban expansion at an impressive rate. However, this rapid transformation introduced several challenges, including legal, social, and environmental issues centered around land use policies. The study delves into the consequences of these reforms, such as the technical efficiency impacts on livestock grazing in Tibet versus the degradation of ecosystem services in Inner Mongolia, and the negative effects of full-scale land relocation practices on organic fertilizer usage. The complexity of redeveloping brownfields in rural areas and the crucial role of rural land tenure in investment, productivity, and participation in the land rental market are also highlighted. The effectiveness of land use policies has thus become a focal point for scholarly investigation, particularly regarding the impact on rural residents, who are critical stakeholders in the reform process. Central to this exploration is the concept of social capital, defined as the network of relationships among people who live and work in a particular society, enabling society to function effectively. Social capital, encompassing elements such as trust, social networks, and norms, plays a pivotal role in encouraging environmental restoration and climate change adaptation efforts. This has been observed not only in China but globally, suggesting a move towards behavioral land use policies that leverage social capital for cost-effective and sustainable outcomes. These policies aim to influence behaviors through intrinsic motivations rather than through monetary incentives or legal mandates, which often entail significant public expenditure and administrative costs. The data seeks to advance the discourse on land use policy by proposing a comprehensive analytical framework that includes various forms of social capital and measures policy outcomes both in the short and long term. Employing an innovative empirical strategy, the study addresses endogeneity issues and aims to provide a nuanced understanding of the relationship between social capital and land use policy outcomes. The findings suggest that social capital has a contextually dependent effect on policy effectiveness, varying across different policy objectives and stages of policy evaluation. This research underscores the importance of incorporating multiple dimensions of social capital into policy analysis and design, offering insights that could guide sustainable urbanization and rural development efforts.Although China has almost eliminated urban poverty, the total number of Chinese citizens in poverty remains at 82 million, most of which are rural residents. The development of rural finance is essential to preventing the country from undergoing further polarization because of the significant potential of such development to facilitate resource interflows between rural and urban markets and to support sustainable development in the agricultural sector. However, rural finance is the weakest point in China's financial systems. Rural households are more constrained than their urban counterparts in terms of financial product availability, consumer protection, and asset accumulation. The development of the rural financial system faces resistance from both the demand and the supply sides. The proposed project addresses this challenge by investigating the applications of a proven behavioural approach, namely, Libertarian Paternalism, in the development of rural financial systems in China. This approach promotes choice architectures to nudge people into optimal decisions without interfering with the freedom of choice. It has been rigorously tested and warmly received in the UK public policy domain. This approach also fits the political and cultural background in China, in which the central government needs to maintain a firm control over financial systems as the general public increasingly demands more freedom. Existing behavioural studies have been heavily reliant on laboratory experiments. Although the use of field studies has been increasing, empirical evidence from the developing world is limited. Meanwhile, the applications of behavioural insights in rural economic development in China remains an uncharted territory. Rural finance studies on the household level are limited; evidence on the role of psychological and social factors in rural households' financial decisions is scarce. The proposed project will bridge this gap in the literature. The overarching research question of this project is whether and how behavioural insights can be used to help rural residents in China make sound financial decisions, which will ultimately contribute to the sustainable economic development in China. The research will be conducted through field experiments in rural China. By relying on field evidences, the project team will develop policy tools and checklists for policy makers to help rural households make sound financial decisions. Two types of tools will be developed for policy makers, namely, "push" tools that aim to achieve short-term policy compliance among rural households so that they can break out of the persistent poverty cycle and "pull" tools that can reduce fraud, error, and debt among rural households to prevent them from falling back into poverty. Finally, the project team will also use the research activities and findings as vehicles to engage and educate rural residents, local governments, regulators, and financial institutions. Standard and good practice will be proposed to interested parties for the designs of good behavioural interventions; ethical guidelines will be provided to encourage good practice. This important step ensures that the findings of this project will benefit academia and practice, with long-lasting, positive impacts. The findings will benefit researchers in behavioural finance and economics, rural economics, development economics, political sciences, and psychology. The findings of and the engagement in this project will help policy makers to develop cost-effective behavioural change policies. Rural households will benefit by being nudged into sound financial decisions and healthy financial habits. The project will provide insights on how to leverage behavioural insights to overcome persistent poverty in the developing world. Therefore, the research will be of interest to communities in China and internationally. We collected data by including a special module in the 17 Provinces Rural Land Survey administrated by Renmin University of China. This survey is a joint research project between Renmin University of China and the Rural Development Institute (RDI) in the US conducted since 1999. A total of seven rounds of surveys have been conducted since then, and we obtained our data from the latest round completed in 2016.

As the primary goal of the 17 Sustainable Development Goals (SDGs), poverty eradication is still one of the major challenges faced by countries around the world, and relative poverty is a comprehensive poverty pattern triggered by the superposition of economic, social, and environmental dimensions. Therefore, Therefore, this paper introduces the perspective of coupled coordination to consider the formation of relative poverty, constructs indicators in three major dimensions: economic, social, and environmental, proposes a fast and more accurate method of identifying relative poverty in a region by using machine learning, measures the degree of coupled coordination of China’s relatively poor provinces using a coupled coordination model and analyzes the relationship with the level of relative poverty, and puts forward suggestions for poverty management on this basis using typology classification. The results of the study show that: 1) the fusion of data crawlers, remote sensing space, and other multi-source data to construct the dataset and propose a fast and efficient regional relative poverty identification method based on big data with low comprehensive cost and high identification accuracy of 0.914. 2) Currently, 70.83% of the economic-social-environmental systems of the relatively poor regions are in the dysfunctional type and are in a state of disordered development and malignant constraints. The regions showing coupling disorders are mainly clustered in the three southern prefectures of Xinjiang, Qinghai, Gansu, Yunnan, and Sichuan, and their spatial distribution is relatively concentrated. 3) The types of poverty and their coupled and coordinated development in each region show large spatial variability, requiring differentiated poverty eradication countermeasures tailored to local conditions to achieve sustainable regional economic-social-environmental development.