24 datasets found
  1. Chinese cities with the highest GDP in 2023

    • statista.com
    Updated Nov 27, 2024
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    Statista (2024). Chinese cities with the highest GDP in 2023 [Dataset]. https://www.statista.com/statistics/278939/chinese-cities-with-the-highest-gdp/
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    Dataset updated
    Nov 27, 2024
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    2023
    Area covered
    China
    Description

    In 2023, Shanghai was the city with the largest GDP in China, reaching a value added of approximately 4.7 trillion yuan. The four Chinese first-tier cites Beijing, Shanghai, Shenzhen, and Guangzhou had by far the strongest economic performance. Development of Chinese cities Rapid urbanization and economic growth have reshaped all Chinese cities since the economic opening up of China. While the first-tier cities have overall benefitted most from this development, the last two decades have seen many second-tier cities catching up. For many years already, growth rates in Qingdao, Hangzhou, Changsha, and Zhengzhou have been higher than in Shanghai or Beijing.This development was driven by lower costs in smaller cities, a specialization of their economies, and political measures to support inland cities and ease the pressure on the largest municipalities. Today, per capita GDP in cities such as Suzhou, Nanjing, and Shenzhen is already higher than in Beijing or Shanghai. Future perspectives Competition between cities will further change China’s urban landscape in the future. Medium-sized cities that can provide an attractive economic environment have the potential to grow their economy at a faster pace, attract immigration, and further increase their relative importance. Cities that are losing their competitive edge, however, like Shenyang, Dalian, and other cities in the northeastern rustbelt, are increasingly confronted by economic stagnation and demographic decline.

  2. Leading billionaire cities 2025

    • statista.com
    Updated Jun 23, 2025
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    Statista (2025). Leading billionaire cities 2025 [Dataset]. https://www.statista.com/statistics/299494/billionaires-top-cities/
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    Dataset updated
    Jun 23, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    2025
    Area covered
    Worldwide
    Description

    According to the Hurun Global Rich List 2025, the city with the highest number of billionaires in 2025 was New York. In detail, *** billionaires resided in the American city. Furthermore, ** billionaires lived in London, while Shanghai had a billionaire population of ** individuals. New York was the only city in the world with more than 100 billionaires that year. Mega-cities of the world A large number of the world’s billionaires are concentrated in a select number of the world’s mega-cities. This has as much to do with the location of their wealth, business interests, and further earning potential, as does the quality of life in those cities. A look at the most significant industries in the global billionaire production line helps to explain the prominence of the traditional capitals of global business including New York, London and Hong Kong. The place of many Chinese cities on the list can in part be explained by the strong performance of industrial conglomerates from the country in recent years. Economic growth in China While New York is the city with the highest number of billionaires, China now boasts the most billionaires of any country in the world. However, ***** of the top ten wealthiest billionaires still came from the United States as of 2025.

  3. Number of super rich people in Greater China in 2024, by city

    • statista.com
    Updated Apr 7, 2025
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    Statista (2025). Number of super rich people in Greater China in 2024, by city [Dataset]. https://www.statista.com/statistics/239091/number-of-super-rich-people-in-china-by-city/
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    Dataset updated
    Apr 7, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    Jan 2024
    Area covered
    China
    Description

    This statistic shows the number of super rich households in Greater China as of January 2024, by city. In January 2024, approximately 19,000 households owning assets of 100 million Chinese yuan or more existed in Beijing.

  4. Number of millionaires in Greater China in 2024, by city

    • statista.com
    Updated Jul 11, 2025
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    Statista (2025). Number of millionaires in Greater China in 2024, by city [Dataset]. https://www.statista.com/statistics/1257972/number-of-millionaires-in-china-by-city/
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    Dataset updated
    Jul 11, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    Jan 2024
    Area covered
    Taiwan, China
    Description

    In January 2024, approximately ******* hoseholds in Beijing owned assets worth *********** yuan ore more. Beijing, Shanghai, and Hong Kong were home to by far the highest number of millionaires in Greater China.

  5. China CN: GDP: per Capita: Guangdong: Zhanjiang

    • ceicdata.com
    Updated Mar 12, 2018
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    CEICdata.com (2018). China CN: GDP: per Capita: Guangdong: Zhanjiang [Dataset]. https://www.ceicdata.com/en/china/gross-domestic-product-prefecture-level-city-per-capita
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    Dataset updated
    Mar 12, 2018
    Dataset provided by
    CEIC Data
    License

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

    Time period covered
    Dec 1, 2012 - Dec 1, 2023
    Area covered
    China
    Variables measured
    Gross Domestic Product
    Description

    CN: GDP: per Capita: Guangdong: Zhanjiang data was reported at 53,757.127 RMB in 2023. This records an increase from the previous number of 52,786.547 RMB for 2022. CN: GDP: per Capita: Guangdong: Zhanjiang data is updated yearly, averaging 25,317.762 RMB from Dec 2000 (Median) to 2023, with 24 observations. The data reached an all-time high of 53,757.127 RMB in 2023 and a record low of 6,230.589 RMB in 2000. CN: GDP: per Capita: Guangdong: Zhanjiang data remains active status in CEIC and is reported by Zhanjiang Municipal Bureau of Statistics. The data is categorized under China Premium Database’s National Accounts – Table CN.AE: Gross Domestic Product: Prefecture Level City: per Capita.

  6. GDP per capita of major cities in China 2021

    • statista.com
    Updated Jul 7, 2025
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    Statista (2025). GDP per capita of major cities in China 2021 [Dataset]. https://www.statista.com/statistics/1181453/china-per-capita-gross-domestic-product-gdp-of-major-cities/
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    Dataset updated
    Jul 7, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    2021
    Area covered
    China
    Description

    In 2021, the highest per capita gross domestic product (GDP) of major cities in China had been reached in Beijing, amounting to about ******* yuan per person. Per capita GDP of cities may vary largely in China, from ** to ** thousand yuan in smaller and remote cities in the countryside to nearly ******* yuan in large cities.

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

    • statista.com
    Updated Dec 10, 2024
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    Statista (2024). 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
    Dec 10, 2024
    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.

  8. China CN: GDP: per Capita: Yunnan: Kunming

    • ceicdata.com
    Updated Aug 26, 2023
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    CEICdata.com (2023). China CN: GDP: per Capita: Yunnan: Kunming [Dataset]. https://www.ceicdata.com/en/china/gross-domestic-product-prefecture-level-city-per-capita/cn-gdp-per-capita-yunnan-kunming
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    Dataset updated
    Aug 26, 2023
    Dataset provided by
    CEIC Data
    License

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

    Time period covered
    Dec 1, 2010 - Dec 1, 2021
    Area covered
    China
    Variables measured
    Gross Domestic Product
    Description

    GDP: per Capita: Yunnan: Kunming data was reported at 85,146.000 RMB in 2021. This records an increase from the previous number of 80,571.000 RMB for 2020. GDP: per Capita: Yunnan: Kunming data is updated yearly, averaging 19,866.000 RMB from Dec 1978 (Median) to 2021, with 31 observations. The data reached an all-time high of 85,146.000 RMB in 2021 and a record low of 415.000 RMB in 1978. GDP: per Capita: Yunnan: Kunming data remains active status in CEIC and is reported by Kunming Municipal Bureau of Statistics. The data is categorized under China Premium Database’s National Accounts – Table CN.AE: Gross Domestic Product: Prefecture Level City: per Capita.

  9. Ranking of the 22 richest people in China as of 2024

    • statista.com
    Updated Apr 2, 2024
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    Statista (2024). Ranking of the 22 richest people in China as of 2024 [Dataset]. https://www.statista.com/statistics/278457/ranking-of-the-25-richest-people-in-china/
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    Dataset updated
    Apr 2, 2024
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    Jan 15, 2024
    Area covered
    China
    Description

    As of January 2024, Zhong Shanshan topped the list of the richest people in China with a net worth of 63 billion U.S. dollars. Huang Zheng, founder of Pinduoduo, and Ma Huateng, founder of the IT giant Tencent, came in second and third respectively, while Ma Yun, founder of the IT giant Alibaba, fell back to the tenth place.

    Ultra-high net worth individuals (UHNWI) in China

    Net worth refers to the amount of value by which an individual’s assets exceed their liabilities. It is usually cited to demonstrate the economic position of a person. Following China’s extensive economic development over the past two decades, the number of wealthy people had been rapidly growing as well. According to Hurun Research Institute, Greater China was the region with the largest number of billionaires worldwide as of 2024, with a total number of 814 billionaires. As of January 2022, the number of millionaires had amounted to approximately 20,400 people in Beijing alone. Unsurprisingly, the majority of high-net worth individuals lives in one of the four first-tier cities Beijing, Shanghai, Guangzhou, and Shenzhen.

    Chinese billionaire's sources of wealth

    Chinese millionaires have accumulated their wealth primarily as private entrepreneurs. Most of the people listed among the 20 wealthiest Chinese in 2024 had owned their own companies. Zhong Shanshan, who topped the list of richest people in China in 2024, has made his fortune as founder of the beverage company Nongfu Spring.

  10. China CN: GDP: Hubei: Huangshi

    • ceicdata.com
    Updated Dec 15, 2024
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    CEICdata.com (2024). China CN: GDP: Hubei: Huangshi [Dataset]. https://www.ceicdata.com/en/china/gross-domestic-product-prefecture-level-city/cn-gdp-hubei-huangshi
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    Dataset updated
    Dec 15, 2024
    Dataset provided by
    CEIC Data
    License

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

    Time period covered
    Dec 1, 2012 - Dec 1, 2023
    Area covered
    China
    Variables measured
    Gross Domestic Product
    Description

    GDP: Hubei: Huangshi data was reported at 210.896 RMB bn in 2023. This records an increase from the previous number of 204.151 RMB bn for 2022. GDP: Hubei: Huangshi data is updated yearly, averaging 53.057 RMB bn from Dec 1991 (Median) to 2023, with 31 observations. The data reached an all-time high of 210.896 RMB bn in 2023 and a record low of 2.838 RMB bn in 1991. GDP: Hubei: Huangshi data remains active status in CEIC and is reported by Huangshi Municipal Bureau of Statistics. The data is categorized under China Premium Database’s National Accounts – Table CN.AE: Gross Domestic Product: Prefecture Level City.

  11. China Average Wage: On Duty: Liaoning: Anshan

    • ceicdata.com
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    CEICdata.com, China Average Wage: On Duty: Liaoning: Anshan [Dataset]. https://www.ceicdata.com/en/china/average-wage-on-duty-prefecture-level-city/average-wage-on-duty-liaoning-anshan
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    Dataset provided by
    CEIC Data
    License

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

    Time period covered
    Dec 1, 2011 - Dec 1, 2022
    Area covered
    China
    Variables measured
    Wage/Earnings
    Description

    Average Wage: On Duty: Liaoning: Anshan data was reported at 79,137.000 RMB in 2022. This records an increase from the previous number of 76,692.000 RMB for 2021. Average Wage: On Duty: Liaoning: Anshan data is updated yearly, averaging 30,432.650 RMB from Dec 1996 (Median) to 2022, with 27 observations. The data reached an all-time high of 79,137.000 RMB in 2022 and a record low of 5,451.000 RMB in 1996. Average Wage: On Duty: Liaoning: Anshan data remains active status in CEIC and is reported by Anshan Municipal Bureau of Statistics. The data is categorized under China Premium Database’s Labour Market – Table CN.GG: Average Wage: On Duty: Prefecture Level City.

  12. China CN: Property Price: Guangdong: Meizhou

    • ceicdata.com
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    CEICdata.com, China CN: Property Price: Guangdong: Meizhou [Dataset]. https://www.ceicdata.com/en/china/property-price-prefecture-level-city/cn-property-price-guangdong-meizhou
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    Dataset provided by
    CEIC Data
    License

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

    Time period covered
    Dec 1, 2011 - Dec 1, 2022
    Area covered
    China
    Variables measured
    Price
    Description

    Property Price: Guangdong: Meizhou data was reported at 5,546.751 RMB/sq m in 2022. This records a decrease from the previous number of 5,842.439 RMB/sq m for 2021. Property Price: Guangdong: Meizhou data is updated yearly, averaging 4,329.444 RMB/sq m from Dec 2003 (Median) to 2022, with 20 observations. The data reached an all-time high of 6,488.366 RMB/sq m in 2018 and a record low of 854.000 RMB/sq m in 2003. Property Price: Guangdong: Meizhou data remains active status in CEIC and is reported by Meizhou Municipal Bureau of Statistics. The data is categorized under China Premium Database’s Price – Table CN.PE: Property Price: Prefecture Level City.

  13. Per capita gross domestic product (GDP) in China 2023, by region

    • statista.com
    Updated Oct 10, 2024
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    Statista (2024). Per capita gross domestic product (GDP) in China 2023, by region [Dataset]. https://www.statista.com/statistics/1093666/china-per-capita-gross-domestic-product-gdp-by-province/
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    Dataset updated
    Oct 10, 2024
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    2023
    Area covered
    China
    Description

    In 2023, the annual per capita gross domestic product (GDP) in different provinces, municipalities, and autonomous regions in China varied from approximately 200,300 yuan in Beijing municipality to roughly 47,900 yuan in Gansu province. The average national per capita GDP crossed the threshold of 10,000 U.S. dollars in 2019 and reached around 89,400 yuan in 2023. 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.

  14. T

    GDP PER CAPITA by Country in ASIA

    • tradingeconomics.com
    csv, excel, json, xml
    Updated May 26, 2017
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    TRADING ECONOMICS (2017). GDP PER CAPITA by Country in ASIA [Dataset]. https://tradingeconomics.com/country-list/gdp-per-capita?continent=asia
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    json, csv, xml, excelAvailable download formats
    Dataset updated
    May 26, 2017
    Dataset authored and provided by
    TRADING ECONOMICS
    License

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

    Time period covered
    2025
    Area covered
    Asia
    Description

    This dataset provides values for GDP PER CAPITA reported in several countries. The data includes current values, previous releases, historical highs and record lows, release frequency, reported unit and currency.

  15. T

    GDP by Country in ASIA

    • tradingeconomics.com
    csv, excel, json, xml
    Updated Jun 20, 2025
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    TRADING ECONOMICS (2025). GDP by Country in ASIA [Dataset]. https://tradingeconomics.com/country-list/gdp?continent=asia
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    xml, json, csv, excelAvailable download formats
    Dataset updated
    Jun 20, 2025
    Dataset authored and provided by
    TRADING ECONOMICS
    License

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

    Time period covered
    2025
    Area covered
    Asia
    Description

    This dataset provides values for GDP reported in several countries. The data includes current values, previous releases, historical highs and record lows, release frequency, reported unit and currency.

  16. c

    GCRF Centre for Sustainable, Healthy and Learning Cities and Neighbourhoods:...

    • datacatalogue.cessda.eu
    • beta.ukdataservice.ac.uk
    Updated Jun 14, 2025
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    Wang, Y; Kintrea, K; Osborne, M; Schweisfurth, M; Mitchell, R; Kamete, A; Yao, J; Stewart, A; Ahmad, S; Young, G; Nesterova, Y; Everatt, D; Lynge, H; Abrahams, C; Turok, I; Scheba, A; Visagie, J; Manirakiza, V; Malonza, J; Nduwayezu, G; Mugabe, L; Nsabimana, A; Rutayisire, P; Nzayirambaho, M; Njunwa, J; Levira, F, Ifakara Health Institute; Moshi, I, Ifakara Health Institute; Msuya, I, Ifakara Health Institute; Kundu, D, National Institute of Urban Affairs; Sharma, P, National Institute of Urban Affairs; Debnath; Roy, S, Khulna University; Sowgat, T, Khulna University; ISLAM; Shakil, I, Khulna University; Reyes, M; Gamboa, M; Rivera, R; Caluag, A; Manlapas, I; Racoma, D; Sun, T, Nankai University; Zhai, L, Nankai University; Li, C, Nankai University; Liu, Y, Nankai University; Wang, C, Nankai University; Zhang, L, Nankai University; Sun, X, Nankai University; Bhandari, R; Baffoe, G; Victoria, L; Jinqiao, L (2025). GCRF Centre for Sustainable, Healthy and Learning Cities and Neighbourhoods: Household Survey and Neighbourhood Focus Group Data from Seven Asian and African Countries, 2021-2022 [Dataset]. http://doi.org/10.5255/UKDA-SN-855998
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    Dataset updated
    Jun 14, 2025
    Dataset provided by
    University of the Witwatersrand
    China
    Tanzania
    Chester University
    T
    University of Glasgow
    Centre for Neighbourhood Studies
    Human Sciences Research Council
    University of Rwanda
    York University
    Bangladesh
    India
    Authors
    Wang, Y; Kintrea, K; Osborne, M; Schweisfurth, M; Mitchell, R; Kamete, A; Yao, J; Stewart, A; Ahmad, S; Young, G; Nesterova, Y; Everatt, D; Lynge, H; Abrahams, C; Turok, I; Scheba, A; Visagie, J; Manirakiza, V; Malonza, J; Nduwayezu, G; Mugabe, L; Nsabimana, A; Rutayisire, P; Nzayirambaho, M; Njunwa, J; Levira, F, Ifakara Health Institute; Moshi, I, Ifakara Health Institute; Msuya, I, Ifakara Health Institute; Kundu, D, National Institute of Urban Affairs; Sharma, P, National Institute of Urban Affairs; Debnath; Roy, S, Khulna University; Sowgat, T, Khulna University; ISLAM; Shakil, I, Khulna University; Reyes, M; Gamboa, M; Rivera, R; Caluag, A; Manlapas, I; Racoma, D; Sun, T, Nankai University; Zhai, L, Nankai University; Li, C, Nankai University; Liu, Y, Nankai University; Wang, C, Nankai University; Zhang, L, Nankai University; Sun, X, Nankai University; Bhandari, R; Baffoe, G; Victoria, L; Jinqiao, L
    Time period covered
    Jul 1, 2021 - Mar 30, 2022
    Area covered
    Africa, South Africa, Tanzania, India, People's Republic of China, Rwanda, Bangladesh, Philippines
    Variables measured
    Individual, Household
    Measurement technique
    In each country the study selected one large city and one smaller regional cities as case studied. Within each case study cities, neighbourhoods were categorised roughly into five income and wealth bands: the rich, upper middle income, middle income, lower middle and low income neighbourhoods. A household survey was carried out face to face by trained interviewers with a random adult member of the household. A common questionnaire was designed and adopted by all teams. The sample was distributed in the city to representative the five neighbourhood types. The survey was followed by focus group interviews. A carefully designed and agreed common interview guide was used by all team. The target was one focus group for a sample neighbourhood in each income band in each city. Focus groups were recorded, all transcripts were translated into English for analysis.
    Description

    In order to bring a thorough and comprehensive understanding of social, economic and environmental sustainability challenges faced by cities and local communities in the developing countries, the SHLC team conducted a major household survey followed by a neighbourhood focus group interview in seven Asian and African countries from late 2021 to early 2022. In each country the study includes two case study cities: one large city and one smaller regional cities. Within each case study cities, neighbourhoods were identified and categorised into five income and wealth bands: the rich, upper middle income, middle income, lower middle and low income neighbourhoods.

    A household survey was carried out face to face by trained interviewers with a random adult member of the household. The 20 page common questionnaire was designed and adopted by all teams, which cover topics of housing, residence, living conditions, migration, education, health, neighbourhood infrastructure, facilities, governance and relations, income and employments, gender equality and impacts from Covid-19. The sample was distributed in the city to representative the five neighbourhood types. The survey was completed in 13 of the 14 case study cities (fieldwork in Chongqing in China was delayed by the Covid-19 lockdowns and implemented in August 2023). The target sample for each city was 1000; the total sample in the database (SPSS and STATA) include 14245 households.

    The survey was followed by focus group interviews. A carefully designed and agreed common interview guide was used by all team. The target was to have one focus group for one neighbourhood in each income band in each city. A total of 74 focus group interviews were conducted (Fieldwork in Datong and Chongqing in China was delayed). The transcripts are the qualitative data shared here.

    The Centre for Sustainable, Healthy and Learning Cities and Neighbourhoods (SHLC) was funded by UKRI Global Challenge Research Fund (GCRF) from 2017 to 2023. Its main aim was to grow research capability to meet the challenges faced by developing countries (Grow). SHLC, led by University of Glasgow, was set up as an international collaborative research centre to address urban challenges across communities in Africa and Asia. Its work contributed to three UN 2030 Sustainable Development Goals: 11 - Make cities and human settlements sustainable; 3 - Ensure healthy lives for all; 4 - Ensure inclusive and equitable quality education for all. SHLC brought together the expertise of urban studies, education, health, geography, planning and data science from nine institutions in eight countries. Its international partners included: Ifakara Health Institute (Tanzania), Khulna University (Bangladesh), Nankai University (China), National Institute of Urban Affairs (India), The Human Sciences Research Council and University of Witwatersrand (South Africa), The University of the Philippines and The University of Rwanda. SHLC working programme had two streams of work and eight specific task packages. Stream one included four Capacity Strengthening Packages which involved the training of over 100 researchers and enhancing the associated academic networks. Steam two work consisted of four Research Task Packages. The co-designed research programme adopted a common research framework in all seven countries (14 case study cities), aiming to bring a thorough and comprehensive understanding of social, economic and environmental sustainability challenges faced by these cities and local communities. Apart from policy reviews, secondary data analysis, the project employed two major primary data collection methods – household questionnaire survey and neighbourhood focus groups. The team have overcome many challenges brought by the Covid-19 pandemics and completed the household survey in 13 cities with a total sample size of 14245, which covered five different types of neighbourhoods ranging from the rich to the poor. The team also completed 74 neighbourhood focus group interviews. Data collection was carried out from late 2021 to early 2022. Huge resources and researchers’ time were dedicated to coordinate, collect, translate, clean and merge these quantitative and qualitative data.

  17. Per capita disposable income in urban and rural China 1990-2024

    • statista.com
    Updated Jun 23, 2025
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    Statista (2025). Per capita disposable income in urban and rural China 1990-2024 [Dataset]. https://www.statista.com/statistics/259451/annual-per-capita-disposable-income-of-rural-and-urban-households-in-china/
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    Dataset updated
    Jun 23, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    China
    Description

    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.

  18. Top 20 billionaire countries 2025

    • statista.com
    Updated Jun 23, 2025
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    Statista (2025). Top 20 billionaire countries 2025 [Dataset]. https://www.statista.com/statistics/299513/billionaires-top-countries/
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    Dataset updated
    Jun 23, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    Jan 2025
    Area covered
    World
    Description

    According to the Hurun Global Rich List 2025, the United States housed the highest number of billionaires worldwide in 2025. In detail, there were *** billionaires living in the United States as of January that year. By comparison, *** billionaires resided in China. India, the United Kingdom, and Germany were also the homes of a significant number of billionaires that year. United States has regained its first place As the founder and exporter of consumer capitalism, it is no surprise that the United States is home to a large number of billionaires. Although China had briefly overtaken the U.S. in recent years, the United States has reclaimed its position as the country with the most billionaires in the world. Moreover, North America leads the way in terms of the highest number of ultra high net worth individuals – those with a net worth of more than ***** million U.S. dollars. The prominence of Europe and North America is a reflection of the higher degree of economic development in those states. However, this may also change as China and other emerging economies continue developing. Female billionaires Moreover, the small proportion of female billionaires does little to counter critics claiming the global economy is dominated by an elite comprised mainly of men. On the list of the 20 richest people in the world, only one was a woman. Moreover, recent political discourse has put a great amount of attention on the wealth held by the super-rich with the wealth distribution of the global population being heavily unequal.

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

    • statista.com
    Updated Jan 21, 2025
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    Statista (2025). 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 updated
    Jan 21, 2025
    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.

  20. Most popular domestic travel destinations of Chinese millionaires 2025

    • statista.com
    Updated Jun 20, 2025
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    Statista (2025). Most popular domestic travel destinations of Chinese millionaires 2025 [Dataset]. https://www.statista.com/statistics/260741/major-domestic-travel-destinations-of-chinese-millionaires/
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    Dataset updated
    Jun 20, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    2025
    Area covered
    China
    Description

    A survey conducted among Chinese millionaires in early 2025 revealed that around ** percent of respondents chose Sanya as their preferred domestic travel destination. This destination was the most popular among the respondents in a similar survey a year earlier.

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Statista (2024). Chinese cities with the highest GDP in 2023 [Dataset]. https://www.statista.com/statistics/278939/chinese-cities-with-the-highest-gdp/
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Chinese cities with the highest GDP in 2023

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Dataset updated
Nov 27, 2024
Dataset authored and provided by
Statistahttp://statista.com/
Time period covered
2023
Area covered
China
Description

In 2023, Shanghai was the city with the largest GDP in China, reaching a value added of approximately 4.7 trillion yuan. The four Chinese first-tier cites Beijing, Shanghai, Shenzhen, and Guangzhou had by far the strongest economic performance. Development of Chinese cities Rapid urbanization and economic growth have reshaped all Chinese cities since the economic opening up of China. While the first-tier cities have overall benefitted most from this development, the last two decades have seen many second-tier cities catching up. For many years already, growth rates in Qingdao, Hangzhou, Changsha, and Zhengzhou have been higher than in Shanghai or Beijing.This development was driven by lower costs in smaller cities, a specialization of their economies, and political measures to support inland cities and ease the pressure on the largest municipalities. Today, per capita GDP in cities such as Suzhou, Nanjing, and Shenzhen is already higher than in Beijing or Shanghai. Future perspectives Competition between cities will further change China’s urban landscape in the future. Medium-sized cities that can provide an attractive economic environment have the potential to grow their economy at a faster pace, attract immigration, and further increase their relative importance. Cities that are losing their competitive edge, however, like Shenyang, Dalian, and other cities in the northeastern rustbelt, are increasingly confronted by economic stagnation and demographic decline.

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