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.

Since 2000, the share of people living in extreme poverty in rural China has been constantly decreasing. In February 2021, 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.

This dataset is used to investigates the local variations, determinants, effects and influence mechanisms of Health Poverty Alleviation Policy in China. The dataset contains policy data at city and provincial levels, city charateristics data, nationally survey data (CHARLS) and qualitative data.

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.

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.

This paper used the micro panel data from 2016 to 2019 of 2031 registered poor households in B Town, W County, Lu’an City of Anhui Province in China to analyze the diversified patterns and poverty alleviation effect of paired assistance based on the PSM-DID model. The empirical results show that paired assistance provided by social forces can significantly contribute to the poverty alleviation of poor households, promoting the poverty alleviation rate by 7.8%, which can be concluded through sample matching and control of relevant variables. Furthermore, based on the subsample of poor households with social assistance, we found that external social assistance subject to paired assistance can significantly improve the poverty alleviation rate of poor households by 14.26%, mainly hung on their economic base and strength of poverty alleviation.

This article compares the population agglomeration characteristics of the Xi’an metropolitan area in western China with those of metropolitan areas in other regions officially approved by the Chinese government. The kernel density estimation method and Markov chain model were used to conduct the study. The results revealed that from 2010 to 2020, the population agglomeration level of the Xi’an metropolitan area showed a trend of first increasing and then decreasing. The absolute gap in the population agglomeration level between cities within the metropolitan area gradually narrowed, and the polarization phenomenon of population agglomeration was not obvious. Compared with metropolitan agglomerations such as Nanjing, Wuhan, Fuzhou, Changsha-Zhuzhou-Xiangtan, Chongqing, and Chengdu, the Xi’an metropolitan agglomeration had a lower population agglomeration level, with a significant gap. Moreover, there was an obvious “club convergence” phenomenon in the population agglomeration levels of different urban agglomerations. The probability of the population agglomeration level remaining stable was at least 53.85%, indicating that there was a “Matthew effect” in which the rich become richer and the poor become poorer. Through the convergence models of α and β, the analysis suggested that there was no significant α convergence between the population agglomeration level of the Xi’an metropolitan agglomeration and that of other metropolitan agglomerations. Instead, there was a significant β divergence, indicating that the gap between the Xi’an metropolitan agglomeration’s population agglomeration level and that of other metropolitan agglomerations is gradually widening. An integrated theoretical framework of population agglomeration was constructed from three dimensions: producers, consumers, and social people. An empirical analysis was conducted on the causes of population agglomeration in the Xi’an metropolitan area and other metropolitan areas. The multiple regression results showed that the income level, public consumption expenditure level, education level, comfortable living environment, and educational level were important factors leading to differences in population agglomeration. The geographic detector results showed that factors in the consumer dimension were the main reasons for population agglomeration in metropolitan areas.

In the face of increasing global unsustainable risks such as poverty, hunger, and pollution. Building sustainable agriculture (SA) in the digital age is a fundamental task for human survival. Based on the coupled coordination perspective, this paper constructs an SA system that takes into account more stakeholders by considering poverty alleviation and income increase (PI), food security (FS), and green agriculture (GA) as subsystems. The impact of digital technology on SA is systematically analyzed through data from 276 prefecture-level and above cities in China from 2005 to 2020. The study shows that digital technology has a significant upgrading effect on SA and its subsystems. And digital technology is more likely to promote SA in the developed eastern region and peripheral cities. Moreover, agricultural productivity and labor productivity play a mediating mechanism in the process of digital technology for SA. Digital financial inclusion fuels the high input process of digital technology for incentivizing SA, PI, and GA, but it cannot affect the highly technical process of digital farming. Further research found that the incentives of digital technology for SA and GA are characterized by the nonlinear characteristic of increasing marginal effects. Due to the second digital divide, there is a U-shaped incentive process of digital technology for PI to fall and then rise. Finally, the spillover nature of digital technology leads to spatial spillovers in its contribution to SA development.

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

Comparative analysis of changes in counties and cities based on the EDI and EDI with EC corrected.

Comparison of the number of counties and cities by CEDI and CEDI’.