9 datasets found
  1. Per capita gross domestic product (GDP) in China 2024, by region

    • statista.com
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    Statista, Per capita gross domestic product (GDP) in China 2024, by region [Dataset]. https://www.statista.com/statistics/1093666/china-per-capita-gross-domestic-product-gdp-by-province/
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    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    2024
    Area covered
    China
    Description

    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.

  2. Variable selection and descriptive statistics.

    • plos.figshare.com
    xls
    Updated Sep 19, 2025
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    Huali Jin; Chao Han (2025). Variable selection and descriptive statistics. [Dataset]. http://doi.org/10.1371/journal.pone.0332740.t001
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    xlsAvailable download formats
    Dataset updated
    Sep 19, 2025
    Dataset provided by
    PLOShttp://plos.org/
    Authors
    Huali Jin; Chao Han
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    Enhancing the eco-efficiency of grain production is a critical avenue for ensuring food security and ecological sustainability. This study employs a global super-efficiency SBM model incorporating undesirable outputs, combined with the life cycle assessment method, to comprehensively measure the eco-efficiency of grain production in 31 Chinese provinces and municipalities from 2000 to 2022. Furthermore, we conduct a comprehensive analysis of the distributional dynamics and key driving factors of the eco-efficiency of grain production. The findings indicate that: (1) The overall level of eco-efficiency in China’s grain production is relatively low, exhibiting significant regional disparities. The spatial pattern follows the gradient of “major grain-producing regions> production-sales balance regions> the major grain-consuming regions,” with most provinces yet to reach the efficiency frontier. (2) The eco-efficiency of grain production in China generally exhibits an upward trend, although there are indications of spatial polarization, evident “club convergence” characteristics, and a notable “positive spillover” effect. (3) The eco-efficiency of grain production in China is influenced by a complex interplay of factors, including economic, social, technological, demographic, and natural elements. The gross total agricultural output, water resources endowment, and structure of agricultural production emerge as the critical driving factors, manifesting the Matthew effect of “the rich getting richer and the poor getting poorer.” The findings of this study provide a foundation for the refinement of sustainable grain production policies and the promotion of green agricultural transformation.

  3. Chinese cities with largest and smallest per capita GDP 2021

    • statista.com
    Updated Nov 29, 2025
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    Statista (2025). Chinese cities with largest and smallest per capita GDP 2021 [Dataset]. https://www.statista.com/statistics/1183530/china-city-comparison-largest-and-smallest-per-capita-gross-domestic-product-gdp/
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    Dataset updated
    Nov 29, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    2021
    Area covered
    China
    Description

    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.

  4. S1 Data -

    • plos.figshare.com
    xlsx
    Updated Oct 2, 2024
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    Yumeng Zhang; Chongyang Zhong; Yin Wang (2024). S1 Data - [Dataset]. http://doi.org/10.1371/journal.pone.0311291.s002
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    xlsxAvailable download formats
    Dataset updated
    Oct 2, 2024
    Dataset provided by
    PLOShttp://plos.org/
    Authors
    Yumeng Zhang; Chongyang Zhong; Yin Wang
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    As the largest developing country, China has accumulated enormous material wealth since its reform and opening-up policy. How to effectively evaluate the level of well-being in China has become a meaningful research endeavor. Using the entropy method, Dagum Gini coefficient and Logarithmic Mean Divisia Index (LMDI) decomposition methods, the study examines the spatial and temporal distribution characteristics, spatial differences and driving effects of provincial well-being levels from 2007 to 2020. The results of this study suggest that the level of well-being as a whole, as well as in the eastern, central and western regions increased significantly over the period, with an “east-to-west decreasing” distribution in China. In terms of the pattern of inter-provincial distribution, although the level of well-being in the central and western regions has improved at a faster rate, most provinces in the eastern region have always been among the leading teams on the path of livelihood development. There is still enormous room for improvement in the level of well-being in the central and western provinces. The overall differences in the development of well-being in China, as well as intra-regional and inter-regional differences among the three major regions, showed a narrowing trend. Intra-regional differences in the development of well-being are greatest in the western region, and inter-regional differences in the development of well-being are greatest in the eastern and western regions. Inter-regional differences are the main reason for the spatial differences in well-being among China’s provinces. The combination of economic, social, ecological and technological effects has led to a gradual increase in the level of well-being over the sample period. Among them, economic, social and technological effects have a clear positive driving effect on the increase of well-being levels, while ecological effect have a certain negative driving influence.

  5. Absolute β convergence results.

    • plos.figshare.com
    xls
    Updated Jan 29, 2025
    + more versions
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    Ke Liu; Xu Bo; Wang Zhaoping; Ran Du; Chen Heng (2025). Absolute β convergence results. [Dataset]. http://doi.org/10.1371/journal.pone.0316385.t004
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    xlsAvailable download formats
    Dataset updated
    Jan 29, 2025
    Dataset provided by
    PLOShttp://plos.org/
    Authors
    Ke Liu; Xu Bo; Wang Zhaoping; Ran Du; Chen Heng
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    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.

  6. Per capita disposable income of households in China 1990-2024

    • statista.com
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    Statista, Per capita disposable income of households in China 1990-2024 [Dataset]. https://www.statista.com/statistics/278698/annual-per-capita-income-of-households-in-china/
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    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    China
    Description

    In 2024, the average annual per capita disposable income of households in China amounted to approximately 41,300 yuan. Annual per capita income in Chinese saw a significant rise over the last decades and is still rising at a high pace. During the last ten years, per capita disposable income roughly doubled in China. Income distribution in China As an emerging economy, China faces a large number of development challenges, one of the most pressing issues being income inequality. The income gap between rural and urban areas has been stirring social unrest in China and poses a serious threat to the dogma of a “harmonious society” proclaimed by the communist party. In contrast to the disposable income of urban households, which reached around 54,200 yuan in 2024, that of rural households only amounted to around 23,100 yuan. Coinciding with the urban-rural income gap, income disparities between coastal and western regions in China have become apparent. As of 2023, households in Shanghai and Beijing displayed the highest average annual income of around 84,800 and 81,900 yuan respectively, followed by Zhejiang province with 63,800 yuan. Gansu, a province located in the West of China, had the lowest average annual per capita household income in China with merely 25,000 yuan. Income inequality in China The Gini coefficient is the most commonly used measure of income inequality. For China, the official Gini coefficient also indicates the astonishing inequality of income distribution in the country. Although the Gini coefficient has dropped from its high in 2008 at 49.1 points, it still ranged at a score of 46.5 points in 2023. The United Nations have set an index value of 40 as a warning level for serious inequality in a society.

  7. Urbanization rate in China 2023, by region

    • statista.com
    Updated Nov 11, 2024
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    Statista (2024). Urbanization rate in China 2023, by region [Dataset]. https://www.statista.com/statistics/1088173/china-urbanization-rate-by-region-province/
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    Dataset updated
    Nov 11, 2024
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    2023
    Area covered
    China
    Description

    In 2023, the urbanization rate in different provinces of China varied between 89.5 percent in Shanghai municipality and 38.9 percent in Tibet. The national average urbanization rate reached around 66.2 percent in 2023. Urbanization and economic development During China’s rapid economic development, the share of people living in cities increased from only 19.4 percent in 1980 to nearly 64 percent in 2020. Urbanization rates are now coming closer to those in developed countries. However, the degree of urbanization still varies significantly between different regions in China. This correlates generally with the level of economic development across different regions in China. In eastern Chinese regions with high personal income levels and high per capita GDP, more inhabitants are living in cities than in the countryside. Influence of geography Another reason for different urbanization rates lies in the huge geographic differences of regions in China. Basically, those regions with a low population density often also display lower urbanization rates, because their inhabitants live more scattered across the land area. These differences will most probably remain despite further economic progress.

  8. WWII: pre-war GDP of selected countries and regions 1938

    • statista.com
    Updated Jan 1, 1998
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    Statista (1998). WWII: pre-war GDP of selected countries and regions 1938 [Dataset]. https://www.statista.com/statistics/1334182/wwii-pre-war-gdp/
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    Dataset updated
    Jan 1, 1998
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    1938
    Area covered
    World
    Description

    In 1938, the year before the Second World War, the United States had, by far, the largest economy in the world in terms of gross domestic product (GDP). The five Allied Great Powers that emerged victorious from the war, along with the three Axis Tripartite Pact countries that were ultimately defeated made up the eight largest independent economies in 1938.

    When values are converted into 1990 international dollars, the U.S. GDP was over 800 billion dollars in 1938, which was more than double that of the second largest economy, the Soviet Union. Even the combined economies of the UK, its dominions, and colonies had a value of just over 680 billion 1990 dollars, showing that the United States had established itself as the world's leading economy during the interwar period (despite the Great Depression).

    Interestingly, the British and Dutch colonies had larger combined GDPs than their respective metropoles, which was a key motivator for the Japanese invasion of these territories in East Asia during the war. Trade with neutral and non-belligerent countries also contributed greatly to the economic development of Allied and Axis powers throughout the war; for example, natural resources from Latin America were essential to the American war effort, while German manufacturing was often dependent on Swedish iron supplies.

  9. Urban and rural population of China 2014-2024

    • statista.com
    Updated Jan 15, 2025
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    Statista (2025). Urban and rural population of China 2014-2024 [Dataset]. https://www.statista.com/statistics/278566/urban-and-rural-population-of-china/
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    Dataset updated
    Jan 15, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    China
    Description

    In 2024, about 943.5 million people lived in urban regions in China and 464.8 million in rural. That year, the country had a total population of approximately 1.41 billion people. As of 2024, China was the second most populous country in the world. Urbanization in China Urbanization refers to the process by which people move from rural to urban areas and how a society adapts to the population shift. It is usually seen as a driving force in economic growth, accompanied by industrialization, modernization and the spread of education. Urbanization levels tend to be higher in industrial countries, whereas the degree of urbanization in developing countries remains relatively low. According to World Bank, a mere 19.4 percent of the Chinese population had been living in urban areas in 1980. Since then, China’s urban population has skyrocketed. By 2024, about 67 percent of the Chinese population lived in urban areas. Regional urbanization rates In the last decades, urbanization has progressed greatly in every region of China. Even in most of the more remote Chinese provinces, the urbanization rate surpassed 50 percent in recent years. However, the most urbanized areas are still to be found in the coastal eastern and southern regions of China. The population of Shanghai, the largest city in China and the world’s seventh largest city ranged at around 24 million people in 2023. China’s urban areas are characterized by a developing middle class. Per capita disposable income of Chinese urban households has more than doubled between 2010 and 2020. The emerging middle class is expected to become a significant driver for the continuing growth of the Chinese economy.

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Statista, Per capita gross domestic product (GDP) in China 2024, by region [Dataset]. https://www.statista.com/statistics/1093666/china-per-capita-gross-domestic-product-gdp-by-province/
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Per capita gross domestic product (GDP) in China 2024, by region

Explore at:
11 scholarly articles cite this dataset (View in Google Scholar)
Dataset authored and provided by
Statistahttp://statista.com/
Time period covered
2024
Area covered
China
Description

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.

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