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.

Poverty rate at national poverty line of China plummeted by 100.00% from 0.6 % in 2019 to 0.0 % in 2020. Since the 43.05% drop in 2010, poverty rate at national poverty line sank by 100.00% in 2020. National poverty rate is the percentage of the population living below the national poverty line. National estimates are based on population-weighted subgroup estimates from household surveys.

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.

Actual value and historical data chart for China Poverty Headcount Ratio At National Poverty Line Percent Of Population

This statistic illustrates the number of rural residents in China living below the poverty line in selected years from 2000 to 2020. Since 2000, 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.

China Poverty Gap at $6.85 a Day: 2017 PPP: % data was reported at 3.500 % in 2021. This records a decrease from the previous number of 5.900 % for 2020. China Poverty Gap at $6.85 a Day: 2017 PPP: % data is updated yearly, averaging 22.900 % from Dec 1990 (Median) to 2021, with 19 observations. The data reached an all-time high of 72.800 % in 1990 and a record low of 3.500 % in 2021. China Poverty Gap at $6.85 a Day: 2017 PPP: % data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s China – Table CN.World Bank.WDI: Social: Poverty and Inequality. Poverty gap at $6.85 a day (2017 PPP) is the mean shortfall in income or consumption from the poverty line $6.85 a day (counting the nonpoor as having zero shortfall), expressed as a percentage of the poverty line. This measure reflects the depth of poverty as well as its incidence.;World Bank, Poverty and Inequality Platform. Data are based on primary household survey data obtained from government statistical agencies and World Bank country departments. Data for high-income economies are mostly from the Luxembourg Income Study database. For more information and methodology, please see http://pip.worldbank.org.;;The World Bank’s internationally comparable poverty monitoring database now draws on income or detailed consumption data from more than 2000 household surveys across 169 countries. See the Poverty and Inequality Platform (PIP) for details (www.pip.worldbank.org).

The average for 2020 based on 54 countries was 19.31 percent. The highest value was in the Gambia: 53.4 percent and the lowest value was in China: 0 percent. The indicator is available from 2000 to 2023. Below is a chart for all countries where data are available.

China Proportion of People Living Below 50 Percent Of Median Income: % data was reported at 11.600 % in 2021. This records a decrease from the previous number of 11.900 % for 2020. China Proportion of People Living Below 50 Percent Of Median Income: % data is updated yearly, averaging 15.100 % from Dec 1990 (Median) to 2021, with 19 observations. The data reached an all-time high of 19.500 % in 2010 and a record low of 8.900 % in 1990. China Proportion of People Living Below 50 Percent Of Median Income: % data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s China – Table CN.World Bank.WDI: Social: Poverty and Inequality. The percentage of people in the population who live in households whose per capita income or consumption is below half of the median income or consumption per capita. The median is measured at 2017 Purchasing Power Parity (PPP) using the Poverty and Inequality Platform (http://www.pip.worldbank.org). For some countries, medians are not reported due to grouped and/or confidential data. The reference year is the year in which the underlying household survey data was collected. In cases for which the data collection period bridged two calendar years, the first year in which data were collected is reported.;World Bank, Poverty and Inequality Platform. Data are based on primary household survey data obtained from government statistical agencies and World Bank country departments. Data for high-income economies are mostly from the Luxembourg Income Study database. For more information and methodology, please see http://pip.worldbank.org.;;The World Bank’s internationally comparable poverty monitoring database now draws on income or detailed consumption data from more than 2000 household surveys across 169 countries. See the Poverty and Inequality Platform (PIP) for details (www.pip.worldbank.org).

China Poverty Gap at $3.65 a Day: 2017 PPP: % data was reported at 0.000 % in 2021. This stayed constant from the previous number of 0.000 % for 2020. China Poverty Gap at $3.65 a Day: 2017 PPP: % data is updated yearly, averaging 7.600 % from Dec 1990 (Median) to 2021, with 19 observations. The data reached an all-time high of 51.500 % in 1990 and a record low of 0.000 % in 2021. China Poverty Gap at $3.65 a Day: 2017 PPP: % data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s China – Table CN.World Bank.WDI: Social: Poverty and Inequality. Poverty gap at $3.65 a day (2017 PPP) is the mean shortfall in income or consumption from the poverty line $3.65 a day (counting the nonpoor as having zero shortfall), expressed as a percentage of the poverty line. This measure reflects the depth of poverty as well as its incidence.;World Bank, Poverty and Inequality Platform. Data are based on primary household survey data obtained from government statistical agencies and World Bank country departments. Data for high-income economies are mostly from the Luxembourg Income Study database. For more information and methodology, please see http://pip.worldbank.org.;;The World Bank’s internationally comparable poverty monitoring database now draws on income or detailed consumption data from more than 2000 household surveys across 169 countries. See the Poverty and Inequality Platform (PIP) for details (www.pip.worldbank.org).

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 dataset provides annual data on key economic, social, and environmental indicators affecting poverty levels in Pakistan from the year 2000 to 2023. It includes crucial variables such as GDP growth rate, inflation, unemployment, poverty headcount ratio, agricultural growth, government social spending, external debt, and climate-related disasters. The dataset highlights significant trends, including the economic impact of the 2010 floods, COVID-19 pandemic (2020–2022), and the 2022 economic crisis. It serves as a valuable resource for researchers, policymakers, and analysts studying poverty dynamics and economic development in Pakistan.

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.

China eliminated rural poverty under current poverty standards in 2020. However, compared with rural poverty, urban poverty in China has been somewhat neglected. This paper aims to discover the changes and determinants of multidimensional urban poverty in Shandong Province, a representative province in Eastern China. Using a nationally representative panel dataset, the China Family Panel Studies, and the Dual Cutoff method, this study creates a multidimensional poverty index with four dimensions and 11 indicators to measure urban poverty in Shandong Province. This paper discovers that while the incidence of multidimensional urban poverty in Shandong Province decreased from 47.62% in 2010 to 36.45% in 2018, the intensity of multidimensional poverty only decreased from 41.27% to 37.25%, which indicates the inadequacy of urban anti-poverty efforts in Shandong Province. This paper also uses logistic regression to identify the determinants of multidimensional urban poverty. The findings suggest that income, health, drinking water, and durable goods are the main determinants of multidimensional urban poverty in Shandong Province. Based on these findings, this study provides targeted recommendations for future urban anti-poverty policies in Shandong Province.

China Social Assistance: Number of Urban and Rural Poverty-stricken People data was reported at 4,788.000 Unit th in Mar 2025. This records a decrease from the previous number of 4,797.000 Unit th for Dec 2024. China Social Assistance: Number of Urban and Rural Poverty-stricken People data is updated quarterly, averaging 4,673.000 Unit th from Sep 2017 (Median) to Mar 2025, with 31 observations. The data reached an all-time high of 4,797.000 Unit th in Dec 2024 and a record low of 4,374.000 Unit th in Mar 2020. China Social Assistance: Number of Urban and Rural Poverty-stricken People data remains active status in CEIC and is reported by Ministry of Civil Affairs. The data is categorized under China Premium Database’s Socio-Demographic – Table CN.GH: Civil Affairs Statistics.

Chine: Poverty, percent of population: Pour cet indicateur, La Banque mondiale fournit des données pour la Chine de 2000 à 2020. La valeur moyenne pour Chine pendant cette période était de 11.65 pour cent avec un minimum de 0 pour cent en 2020 et un maximum de 49.8 pour cent en 2000.

In 2024, the gross domestic product (GDP) of China amounted to around 18.7 trillion U.S. dollars. In comparison to the GDP of the other BRIC countries India, Russia and Brazil, China came first that year and second in the world GDP ranking. The stagnation of China's GDP in U.S. dollar terms in 2022 and 2023 was mainly due to the appreciation of the U.S. dollar. China's real GDP growth was 5.4 percent in 2023 and 5.0 percent in 2024. In 2024, per capita GDP in China reached around 13,300 U.S. dollars. Economic performance in China Gross domestic product (GDP) is a primary economic indicator. It measures the total value of all goods and services produced in an economy over a certain time period. China's economy used to grow quickly in the past, but the growth rate of China’s real GDP gradually slowed down in recent years, and year-on-year GDP growth is forecasted to range at only around four percent in the years after 2024. Since 2010, China has been the world’s second-largest economy, surpassing Japan.China’s emergence in the world’s economy has a lot to do with its status as the ‘world’s factory’. Since 2013, China is the largest export country in the world. Some argue that it is partly due to the undervalued Chinese currency. The Big Mac Index, a simplified and informal way to measure the purchasing power parity between different currencies, indicates that the Chinese currency yuan was roughly undervalued by 38 percent in 2024. GDP development Although the impressive economic development in China has led millions of people out of poverty, China is still not in the league of industrialized countries on the per capita basis. To name one example, the U.S. per capita economic output was more than six times as large as in China in 2024. Meanwhile, the Chinese society faces increased income disparities. The Gini coefficient of China, a widely used indicator of economic inequality, has been larger than 0.45 over the last decade, whereas 0.40 is the warning level for social unrest.

By the end of 2020, with all rural residents living in poverty under the current standard lifted out of absolute poverty, marking a new phase in China’s anti-poverty efforts with new pursuit of the consolidation and expansion of poverty alleviation achievements in the effective connection with rural revitalization. The development and improvement of funding mechanisms for rural preschool education are crucially important to further promoting rural development. Employing an input-oriented three-stage DEA model and the Malmquist index, this study conducts a static and dynamic analysis of resource allocation performance in rural preschool education across 30 provinces in China (excluding Tibet, Hong Kong, Macao, and Taiwan). The findings reveal that random factors and environmental variables lead to an underestimation of rural preschool education investment performance. Secondly, economically developed regions are not necessarily equipped with higher performance in rural preschool education investment as regional differences stem from the combined effects of various economic, agglomeration, demographic, and scale factors across different areas of the country. Finally, based on these empirical results, this paper proposes policy recommendations to enhance resource allocation performance in China’s rural preschool education.

The COVID-19 pandemic, which began in China in late 2019, and subsequently spread across the world during the first several months of 2020, has had a dramatic impact on all facets of life. At the same time, it has not manifested in the same way in every nation. Some countries experienced a large initial spike in cases and deaths, followed by a rapid decline, whereas others had relatively low rates of both outcomes throughout the first half of 2020. The United States experienced a unique pattern of the virus, with a large initial spike, followed by a moderate decline in cases, followed by second and then third spikes. In addition, research has shown that in the United States the severity of the pandemic has been associated with poverty and access to health care services. This study was designed to examine whether the course of the pandemic has been uniform across America, and if not how it differed, particularly with respect to poverty. Results of a random intercept multilevel mixture model revealed that the pandemic followed four distinct paths in the country. The least ethnically diverse (85.1% white population) and most rural (82.8% rural residents) counties had the lowest death rates (0.06/1000) and the weakest link between deaths due to COVID-19 and poverty (b = 0.03). In contrast, counties with the highest proportion of urban residents (100%), greatest ethnic diversity (48.2% nonwhite), and highest population density (751.4 people per square mile) had the highest COVID-19 death rates (0.33/1000), and strongest relationship between the COVID-19 death rate and poverty (b = 46.21). Given these findings, American policy makers need to consider developing responses to future pandemics that account for local characteristics. These responses must take special account of pandemic responses among people of color, who suffered the highest death rates in the nation.

Note: PKTKDQ: if the county is the national-level poor county or contiguous areas of dire poverty, PKTKDQ = 1, else PKTKDQ = 0; LSZCQ: if the county is the main grain producing areas, LSZCQ = 1; if the county is the grain production balance areas, LSZCQ = 2; Urb_average nighttime light intensity of the region; AgrMachPower_2: the amount of the total power of agricultural machinery; FertilizerConsm_2: the amount of fertilizer used in agricultural production within the year; L4: Findep, financial dependence; L5: Degreefs, degree of regional financial strain; K1: Inflevel, regional informatization level; L2_wan: GDPper, GDP per capita; L6_w: Finagg, financial agglomeration; aggregate_baifenyi: DFIia, the index aggregate of digital financial inclusion index/100; coverage_breadth_baifenyi: DFIcb ...

每天生活费不足2.15美元的贫困人口比例：2017 PPP：占人口百分比在12-01-2021达0.000%，相较于12-01-2020的0.000%保持不变。每天生活费不足2.15美元的贫困人口比例：2017 PPP：占人口百分比数据按年更新，12-01-1990至12-01-2021期间平均值为8.300%，共19份观测结果。该数据的历史最高值出现于12-01-1990，达72.000%，而历史最低值则出现于12-01-2021，为0.000%。CEIC提供的每天生活费不足2.15美元的贫困人口比例：2017 PPP：占人口百分比数据处于定期更新的状态，数据来源于World Bank，数据归类于全球数据库的中国 – Table CN.World Bank.WDI: Social: Poverty and Inequality。