24 datasets found
  1. Global accumulation of new wealth 2019-2021, by income percentile

    • statista.com
    Updated Jan 16, 2023
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    Statista (2023). Global accumulation of new wealth 2019-2021, by income percentile [Dataset]. https://www.statista.com/statistics/1359627/new-wealth-accumulation-worldwide-income/
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    Dataset updated
    Jan 16, 2023
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    Worldwide
    Description

    Between December 2019 and 2021, the top one percent of earners accumulated 63 percent of all new wealth worldwide. This is more than six times more wealth than accumulated by the bottom 90 percent over the same time period.

    Global wealth distribution Newly generated wealth landing in the hands of the few is not a new story and has been the focus of international development policy for many years. Looking at a regional level, Latin America was the region with the starkest distribution of wealth. In this region, 77 percent of the wealth was held by the richest 10 percent in 2021, and only 0.5 percent held by the poorest 50 percent. At an individual level, around 2.82 billion adults worldwide had a net worth of less than 10,000 U.S. dollars in 2021.

    Billionaires In 2021, the highest concentration of billionaires could be found in North America. However, China had the largest number of billionaires in its population in 2022, with most living in Beijing. Looking at wealth distribution amongst billionaires themselves, 20 people had fortunes of 50 billion U.S. dollars or more, but the majority of billionaires had a personal fortune between two and five billion U.S. dollars.

    In December 2022, Elon Musk slipped from the top spot of richest people on Earth. The number one spot was taken by French magnate, Bernard Arnault of Moët Hennessy Louis Vuitton.

  2. w

    The Global Findex Database 2025: Connectivity and Financial Inclusion in the...

    • microdata.worldbank.org
    Updated Oct 1, 2025
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    Development Research Group, Finance and Private Sector Development Unit (2025). The Global Findex Database 2025: Connectivity and Financial Inclusion in the Digital Economy - Cameroon [Dataset]. https://microdata.worldbank.org/index.php/catalog/7880
    Explore at:
    Dataset updated
    Oct 1, 2025
    Dataset authored and provided by
    Development Research Group, Finance and Private Sector Development Unit
    Time period covered
    2024
    Area covered
    Cameroon
    Description

    Abstract

    The Global Findex 2025 reveals how mobile technology is equipping more adults around the world to own and use financial accounts to save formally, access credit, make and receive digital payments, and pursue opportunities. Including the inaugural Global Findex Digital Connectivity Tracker, this fifth edition of Global Findex presents new insights on the interactions among mobile phone ownership, internet use, and financial inclusion.

    The Global Findex is the world’s most comprehensive database on digital and financial inclusion. It is also the only global source of comparable demand-side data, allowing cross-country analysis of how adults access and use mobile phones, the internet, and financial accounts to reach digital information and resources, save, borrow, make payments, and manage their financial health. Data for the Global Findex 2025 were collected from nationally representative surveys of about 145,000 adults in 141 economies. The latest edition follows the 2011, 2014, 2017, and 2021 editions and includes new series measuring mobile phone ownership and internet use, digital safety, and frequency of transactions using financial services.

    The Global Findex 2025 is an indispensable resource for policy makers in the fields of digital connectivity and financial inclusion, as well as for practitioners, researchers, and development professionals.

    Geographic coverage

    National Coverage

    Analysis unit

    Individual

    Kind of data

    Observation data/ratings [obs]

    Sampling procedure

    In most low- and middle-income economies, Global Findex data were collected through face-to-face interviews. In these economies, an area frame design was used for interviewing. In most high-income economies, telephone surveys were used. In 2024, face-to-face interviews were again conducted in 22 economies after phone-based surveys had been employed in 2021 as a result of mobility restrictions related to COVID-19. In addition, an abridged form of the questionnaire was administered by phone to survey participants in Algeria, China, the Islamic Republic of Iran, Libya, Mauritius, and Ukraine because of economy-specific restrictions. In just one economy, Singapore, did the interviewing mode change from face to face in 2021 to phone based in 2024.

    In economies in which face-to-face surveys were conducted, the first stage of sampling was the identification of primary sampling units. These units were then stratified by population size, geography, or both and clustered through one or more stages of sampling. Where population information was available, sample selection was based on probabilities proportional to population size; otherwise, simple random sampling was used. Random route procedures were used to select sampled households. Unless an outright refusal occurred, interviewers made up to three attempts to survey each sampled household. To increase the probability of contact and completion, attempts were made at different times of the day and, where possible, on different days. If an interview could not be completed at a household that was initially part of the sample, a simple substitution method was used to select a replacement household for inclusion.

    Respondents were randomly selected within sampled households. Each eligible household member (that is, all those ages 15 or older) was listed, and a handheld survey device randomly selected the household member to be interviewed. For paper surveys, the Kish grid method was used to select the respondent. In economies in which cultural restrictions dictated gender matching, respondents were randomly selected from among all eligible adults of the interviewer’s gender.

    In economies in which Global Findex surveys have traditionally been phone based, respondent selection followed the same procedure as in previous years, using random digit dialing or a nationally representative list of phone numbers. In most economies in which mobile phone and landline penetration is high, a dual sampling frame was used.

    The same procedure for respondent selection was applied to economies in which phone-based interviews were being conducted for the first time. Dual-frame (landline and mobile phone) random digit dialing was used where landline presence and use are 20 percent or higher based on historical Gallup estimates. Mobile phone random digit dialing was used in economies with limited or no landline presence (less than 20 percent). For landline respondents in economies in which mobile phone or landline penetration is 80 percent or higher, respondents were selected randomly by using either the next-birthday method or the household enumeration method, which involves listing all eligible household members and randomly selecting one to participate. For mobile phone respondents in these economies or in economies in which mobile phone or landline penetration is less than 80 percent, no further selection was performed. At least three attempts were made to reach the randomly selected person in each household, spread over different days and times of day.

    Research instrument

    The English version of the questionnaire is provided for download.

    Sampling error estimates

    Estimates of standard errors (which account for sampling error) vary by country and indicator. For country-specific margins of error, please refer to the Methodology section and corresponding table in: Klapper, Leora, Dorothe Singer, Laura Starita, and Alexandra Norris. 2025. The Global Findex Database 2025: Connectivity and Financial Inclusion in the Digital Economy. Washington, DC: World Bank. https://doi.org/10.1596/978-1-4648-2204-9.

  3. w

    The Global Findex Database 2025: Connectivity and Financial Inclusion in the...

    • microdata.worldbank.org
    Updated Oct 1, 2025
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    Development Research Group, Finance and Private Sector Development Unit (2025). The Global Findex Database 2025: Connectivity and Financial Inclusion in the Digital Economy - Paraguay [Dataset]. https://microdata.worldbank.org/index.php/catalog/7963
    Explore at:
    Dataset updated
    Oct 1, 2025
    Dataset authored and provided by
    Development Research Group, Finance and Private Sector Development Unit
    Time period covered
    2024
    Area covered
    Paraguay
    Description

    Abstract

    The Global Findex 2025 reveals how mobile technology is equipping more adults around the world to own and use financial accounts to save formally, access credit, make and receive digital payments, and pursue opportunities. Including the inaugural Global Findex Digital Connectivity Tracker, this fifth edition of Global Findex presents new insights on the interactions among mobile phone ownership, internet use, and financial inclusion.

    The Global Findex is the world’s most comprehensive database on digital and financial inclusion. It is also the only global source of comparable demand-side data, allowing cross-country analysis of how adults access and use mobile phones, the internet, and financial accounts to reach digital information and resources, save, borrow, make payments, and manage their financial health. Data for the Global Findex 2025 were collected from nationally representative surveys of about 145,000 adults in 141 economies. The latest edition follows the 2011, 2014, 2017, and 2021 editions and includes new series measuring mobile phone ownership and internet use, digital safety, and frequency of transactions using financial services.

    The Global Findex 2025 is an indispensable resource for policy makers in the fields of digital connectivity and financial inclusion, as well as for practitioners, researchers, and development professionals.

    Geographic coverage

    National Coverage

    Analysis unit

    Individual

    Kind of data

    Observation data/ratings [obs]

    Sampling procedure

    In most low- and middle-income economies, Global Findex data were collected through face-to-face interviews. In these economies, an area frame design was used for interviewing. In most high-income economies, telephone surveys were used. In 2024, face-to-face interviews were again conducted in 22 economies after phone-based surveys had been employed in 2021 as a result of mobility restrictions related to COVID-19. In addition, an abridged form of the questionnaire was administered by phone to survey participants in Algeria, China, the Islamic Republic of Iran, Libya, Mauritius, and Ukraine because of economy-specific restrictions. In just one economy, Singapore, did the interviewing mode change from face to face in 2021 to phone based in 2024.

    In economies in which face-to-face surveys were conducted, the first stage of sampling was the identification of primary sampling units. These units were then stratified by population size, geography, or both and clustered through one or more stages of sampling. Where population information was available, sample selection was based on probabilities proportional to population size; otherwise, simple random sampling was used. Random route procedures were used to select sampled households. Unless an outright refusal occurred, interviewers made up to three attempts to survey each sampled household. To increase the probability of contact and completion, attempts were made at different times of the day and, where possible, on different days. If an interview could not be completed at a household that was initially part of the sample, a simple substitution method was used to select a replacement household for inclusion.

    Respondents were randomly selected within sampled households. Each eligible household member (that is, all those ages 15 or older) was listed, and a handheld survey device randomly selected the household member to be interviewed. For paper surveys, the Kish grid method was used to select the respondent. In economies in which cultural restrictions dictated gender matching, respondents were randomly selected from among all eligible adults of the interviewer’s gender.

    In economies in which Global Findex surveys have traditionally been phone based, respondent selection followed the same procedure as in previous years, using random digit dialing or a nationally representative list of phone numbers. In most economies in which mobile phone and landline penetration is high, a dual sampling frame was used.

    The same procedure for respondent selection was applied to economies in which phone-based interviews were being conducted for the first time. Dual-frame (landline and mobile phone) random digit dialing was used where landline presence and use are 20 percent or higher based on historical Gallup estimates. Mobile phone random digit dialing was used in economies with limited or no landline presence (less than 20 percent). For landline respondents in economies in which mobile phone or landline penetration is 80 percent or higher, respondents were selected randomly by using either the next-birthday method or the household enumeration method, which involves listing all eligible household members and randomly selecting one to participate. For mobile phone respondents in these economies or in economies in which mobile phone or landline penetration is less than 80 percent, no further selection was performed. At least three attempts were made to reach the randomly selected person in each household, spread over different days and times of day.

    Research instrument

    The English version of the questionnaire is provided for download.

    Sampling error estimates

    Estimates of standard errors (which account for sampling error) vary by country and indicator. For country-specific margins of error, please refer to the Methodology section and corresponding table in: Klapper, Leora, Dorothe Singer, Laura Starita, and Alexandra Norris. 2025. The Global Findex Database 2025: Connectivity and Financial Inclusion in the Digital Economy. Washington, DC: World Bank. https://doi.org/10.1596/978-1-4648-2204-9.

  4. Countries by Gross National Income (GNI)

    • kaggle.com
    zip
    Updated Nov 10, 2022
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    The Devastator (2022). Countries by Gross National Income (GNI) [Dataset]. https://www.kaggle.com/datasets/thedevastator/countries-by-gross-national-income-gni
    Explore at:
    zip(4977 bytes)Available download formats
    Dataset updated
    Nov 10, 2022
    Authors
    The Devastator
    License

    https://creativecommons.org/publicdomain/zero/1.0/https://creativecommons.org/publicdomain/zero/1.0/

    Description

    Countries by Gross National Income (GNI)

    Economic health by nation

    About this dataset

    Gross National Income (GNI) is a marker of the economic health of a nation - it encompasses a nation's GDP while also taking into account money flowing in and out of the country from foreign trade. This dataset provides GNI rankings for countries around the world, allowing for comparisons of economic health and growth. Explore how different nations fare in terms of GNI, and what this says about their overall economic stability!

    How to use the dataset

    The Gross National Income (GNI) of countries around the world is a measure of the economic health of a nation. It is a summation of a nation's GDP (Gross Domestic Product) plus the money flowing into and out of the country from foreign countries.

    This dataset provides Rankings of countries by their GNI. The data is divided into two files: df_1.csv and df_2.csv. Both files contain the following columns:

    No.: The number of the country. (Numeric)

    Country: The name of the country. (String)

    Research Ideas

    • Measuring the economic health of a nation
    • Comparing the GDP of different countries
    • Determining the money flow into and out of a country

    Acknowledgements

    GNI data is sourced from wikipedia

    License

    License: CC0 1.0 Universal (CC0 1.0) - Public Domain Dedication No Copyright - You can copy, modify, distribute and perform the work, even for commercial purposes, all without asking permission. See Other Information.

    Columns

    File: df_1.csv

    File: df_4.csv | Column name | Description | |:----------------------------|:----------------------------------------------------------------------| | No. | The rank of the country based on GNI. (Numeric) | | Country | The name of the country. (String) | | GNI (Atlas method)[8] | The GNI of the country, in US dollars. (Numeric) | | GNI (Atlas method)[8].1 | The GNI of the country, as a percentage of the world total. (Numeric) | | GNI[9] | The GNI of the country, in US dollars. (Numeric) | | GNI[9].1 | The GNI of the country, as a percentage of the world total. (Numeric) | | GDP[10] | The GDP of the country, in US dollars. (Numeric) |

    File: df_9.csv | Column name | Description | |:--------------|:----------------------| | 0 | Country Name (String) | | 1 | GNI (Integer) |

    File: df_3.csv | Column name | Description | |:--------------|:----------------------| | 0 | Country Name (String) |

    File: df_2.csv

    File: df_6.csv | Column name | Description | |:--------------|:------------------------------------------------------------------| | Rank | The rank of the country based on GNI. (Numeric) | | 2021 | The GNI of the country in 2021. (Numeric) | | 2021.1 | The GNI of the country in 2021, adjusted for inflation. (Numeric) | | 2016 | The GNI of the country in 2016. (Numeric) | | 2016.1 | The GNI of the country in 2016, adjusted for inflation. (Numeric) | | 2014 | The GNI of the country in 2014. (Numeric) | | 2014.1 | The GNI of the country in 2014, adjusted for inflation. (Numeric) | | 2013 | The GNI of the country in 2013. (Numeric) | | 2013.1 | The GNI of the country in 2013, adjusted for inflation. (Numeric) | | 2012 | The GNI of the country in 2012. (Numeric) | | 2012.1 | The GNI of the country in 2012, adjusted for inflation. (Numeric) | | 2011 | The GNI of the country in 2011. (Numeric) | | 2011.1 | The GNI of the country in 2011, adjusted for inflation. (Numeric) | | 2010 | The GNI of the country in 2010. (Numeric) | | 2010.1 | The GNI of the country in 2010, adjusted for inflation. (Numeric) | | 2009 | The GNI of the country in 2009. (Numeric) | | 2009.1 | The GNI of the country in 2009, adjusted for inflation. (Numeric) | | 2008 | The GNI of the country in 2008. (Numeric) | | 2008.1 | The GNI of the country in 200...

  5. Households by annual income India FY 2021

    • statista.com
    Updated Nov 19, 2025
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    Statista (2025). Households by annual income India FY 2021 [Dataset]. https://www.statista.com/statistics/482584/india-households-by-annual-income/
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    Dataset updated
    Nov 19, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    India
    Description

    In the financial year 2021, a majority of Indian households fell under the aspirers category, earning between ******* and ******* Indian rupees a year. On the other hand, about ***** percent of households that same year, accounted for the rich, earning over * million rupees annually. The middle class more than doubled that year compared to ** percent in financial year 2005. Middle-class income group and the COVID-19 pandemic During the COVID-19 pandemic specifically during the lockdown in March 2020, loss of incomes hit the entire household income spectrum. However, research showed the severest affected groups were the upper middle- and middle-class income brackets. In addition, unemployment rates were rampant nationwide that further lead to a dismally low GDP. Despite job recoveries over the last few months, improvement in incomes were insignificant. Economic inequality While India maybe one of the fastest growing economies in the world, it is also one of the most vulnerable and severely afflicted economies in terms of economic inequality. The vast discrepancy between the rich and poor has been prominent since the last ***** decades. The rich continue to grow richer at a faster pace while the impoverished struggle more than ever before to earn a minimum wage. The widening gaps in the economic structure affect women and children the most. This is a call for reinforcement in in the country’s social structure that emphasizes access to quality education and universal healthcare services.

  6. Mexico: adult population distribution 2022, by wealth

    • statista.com
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    Statista, Mexico: adult population distribution 2022, by wealth [Dataset]. https://www.statista.com/statistics/1234470/mexico-adults-wealth-group/
    Explore at:
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    2022
    Area covered
    Latin America, Mexico
    Description

    In 2022, about 40 percent of adults in Mexico held a net worth under 10,000 U.S. dollars. In contrast, merely 393,000 Mexicans (that is, 0.4 percent of the total) had a net worth of over one million U.S. dollars. Mexico is one of the most unequal countries in Latin America regarding wealth distribution, with 78.7 percent of the national wealth held by the richest ten percent of the population.

    The minimum salaryThe minimum wage per day guaranteed by law in Mexico was decreed to increase by 22 percent between 2021 and 2022, reaching 172.87 Mexican pesos in 2022. In the Free Zone located near the northern border the minimum daily wage was raised to 260.34 Mexican pesos.This represented the fourth consecutive incrase since 2019, but could prove to be insufficient to maintain the wellbeing of Mexican workers after the soaring inflation rate registered in 2022 and the economic impact of the COVID-19 in Mexican households. The legal minimum salary has a long history in the North American country, it was first implemented with the approval of the Political Constitution of the United Mexican States in 1917. Income inequality in Latin AmericaLatin America, as other developing regions in the world, generally records high rates of inequality, with a Gini coefficient ranging between 38 and 54 among the region’s countries. Moreover, many of the countries with the biggest inequality in income distribution worldwide are found in Latin America. According to the Human Development Report 2019, wealth redistribution by means of tax transfers improves Latin America's Gini coefficient to a lesser degree than it does in advanced economies. Wider access to education and health services, on the other hand, have been proven to have a greater direct effect in improving Gini coefficient measurements in the region.

  7. w

    The Global Findex Database 2025: Connectivity and Financial Inclusion in the...

    • microdata.worldbank.org
    Updated Oct 1, 2025
    + more versions
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    Development Research Group, Finance and Private Sector Development Unit (2025). The Global Findex Database 2025: Connectivity and Financial Inclusion in the Digital Economy - Saudi Arabia [Dataset]. https://microdata.worldbank.org/index.php/catalog/7970
    Explore at:
    Dataset updated
    Oct 1, 2025
    Dataset authored and provided by
    Development Research Group, Finance and Private Sector Development Unit
    Time period covered
    2024
    Area covered
    Saudi Arabia
    Description

    Abstract

    The Global Findex 2025 reveals how mobile technology is equipping more adults around the world to own and use financial accounts to save formally, access credit, make and receive digital payments, and pursue opportunities. Including the inaugural Global Findex Digital Connectivity Tracker, this fifth edition of Global Findex presents new insights on the interactions among mobile phone ownership, internet use, and financial inclusion.

    The Global Findex is the world’s most comprehensive database on digital and financial inclusion. It is also the only global source of comparable demand-side data, allowing cross-country analysis of how adults access and use mobile phones, the internet, and financial accounts to reach digital information and resources, save, borrow, make payments, and manage their financial health. Data for the Global Findex 2025 were collected from nationally representative surveys of about 145,000 adults in 141 economies. The latest edition follows the 2011, 2014, 2017, and 2021 editions and includes new series measuring mobile phone ownership and internet use, digital safety, and frequency of transactions using financial services.

    The Global Findex 2025 is an indispensable resource for policy makers in the fields of digital connectivity and financial inclusion, as well as for practitioners, researchers, and development professionals.

    Geographic coverage

    National Coverage

    Analysis unit

    Individual

    Kind of data

    Observation data/ratings [obs]

    Sampling procedure

    In most low- and middle-income economies, Global Findex data were collected through face-to-face interviews. In these economies, an area frame design was used for interviewing. In most high-income economies, telephone surveys were used. In 2024, face-to-face interviews were again conducted in 22 economies after phone-based surveys had been employed in 2021 as a result of mobility restrictions related to COVID-19. In addition, an abridged form of the questionnaire was administered by phone to survey participants in Algeria, China, the Islamic Republic of Iran, Libya, Mauritius, and Ukraine because of economy-specific restrictions. In just one economy, Singapore, did the interviewing mode change from face to face in 2021 to phone based in 2024.

    In economies in which face-to-face surveys were conducted, the first stage of sampling was the identification of primary sampling units. These units were then stratified by population size, geography, or both and clustered through one or more stages of sampling. Where population information was available, sample selection was based on probabilities proportional to population size; otherwise, simple random sampling was used. Random route procedures were used to select sampled households. Unless an outright refusal occurred, interviewers made up to three attempts to survey each sampled household. To increase the probability of contact and completion, attempts were made at different times of the day and, where possible, on different days. If an interview could not be completed at a household that was initially part of the sample, a simple substitution method was used to select a replacement household for inclusion.

    Respondents were randomly selected within sampled households. Each eligible household member (that is, all those ages 15 or older) was listed, and a handheld survey device randomly selected the household member to be interviewed. For paper surveys, the Kish grid method was used to select the respondent. In economies in which cultural restrictions dictated gender matching, respondents were randomly selected from among all eligible adults of the interviewer’s gender.

    In economies in which Global Findex surveys have traditionally been phone based, respondent selection followed the same procedure as in previous years, using random digit dialing or a nationally representative list of phone numbers. In most economies in which mobile phone and landline penetration is high, a dual sampling frame was used.

    The same procedure for respondent selection was applied to economies in which phone-based interviews were being conducted for the first time. Dual-frame (landline and mobile phone) random digit dialing was used where landline presence and use are 20 percent or higher based on historical Gallup estimates. Mobile phone random digit dialing was used in economies with limited or no landline presence (less than 20 percent). For landline respondents in economies in which mobile phone or landline penetration is 80 percent or higher, respondents were selected randomly by using either the next-birthday method or the household enumeration method, which involves listing all eligible household members and randomly selecting one to participate. For mobile phone respondents in these economies or in economies in which mobile phone or landline penetration is less than 80 percent, no further selection was performed. At least three attempts were made to reach the randomly selected person in each household, spread over different days and times of day.

    Research instrument

    The English version of the questionnaire is provided for download.

    Sampling error estimates

    Estimates of standard errors (which account for sampling error) vary by country and indicator. For country-specific margins of error, please refer to the Methodology section and corresponding table in: Klapper, Leora, Dorothe Singer, Laura Starita, and Alexandra Norris. 2025. The Global Findex Database 2025: Connectivity and Financial Inclusion in the Digital Economy. Washington, DC: World Bank. https://doi.org/10.1596/978-1-4648-2204-9.

  8. Population distribution by wealth bracket in India 2021-2022

    • statista.com
    Updated Nov 28, 2025
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    Statista (2025). Population distribution by wealth bracket in India 2021-2022 [Dataset]. https://www.statista.com/statistics/482579/india-population-by-average-wealth/
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    Dataset updated
    Nov 28, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    India
    Description

    In 2022, the majority of Indian adults had a wealth of 10,000 U.S. dollars or less. On the other hand, about *** percent were worth more than *********** dollars that year. India The Republic of India is one of the world’s largest and most economically powerful states. India gained independence from Great Britain on August 15, 1947, after having been under their power for 200 years. With a population of about *** billion people, it was the second most populous country in the world. Of that *** billion, about **** million lived in New Delhi, the capital. Wealth inequality India suffers from extreme income inequality. It is estimated that the top 10 percent of the population holds ** percent of the national wealth. Billionaire fortune has increase sporadically in the last years whereas minimum wages have remain stunted.

  9. w

    The Global Findex Database 2025: Connectivity and Financial Inclusion in the...

    • microdata.worldbank.org
    Updated Oct 1, 2025
    + more versions
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    Development Research Group, Finance and Private Sector Development Unit (2025). The Global Findex Database 2025: Connectivity and Financial Inclusion in the Digital Economy - Guatemala [Dataset]. https://microdata.worldbank.org/index.php/catalog/7910
    Explore at:
    Dataset updated
    Oct 1, 2025
    Dataset authored and provided by
    Development Research Group, Finance and Private Sector Development Unit
    Time period covered
    2024
    Area covered
    Guatemala
    Description

    Abstract

    The Global Findex 2025 reveals how mobile technology is equipping more adults around the world to own and use financial accounts to save formally, access credit, make and receive digital payments, and pursue opportunities. Including the inaugural Global Findex Digital Connectivity Tracker, this fifth edition of Global Findex presents new insights on the interactions among mobile phone ownership, internet use, and financial inclusion.

    The Global Findex is the world’s most comprehensive database on digital and financial inclusion. It is also the only global source of comparable demand-side data, allowing cross-country analysis of how adults access and use mobile phones, the internet, and financial accounts to reach digital information and resources, save, borrow, make payments, and manage their financial health. Data for the Global Findex 2025 were collected from nationally representative surveys of about 145,000 adults in 141 economies. The latest edition follows the 2011, 2014, 2017, and 2021 editions and includes new series measuring mobile phone ownership and internet use, digital safety, and frequency of transactions using financial services.

    The Global Findex 2025 is an indispensable resource for policy makers in the fields of digital connectivity and financial inclusion, as well as for practitioners, researchers, and development professionals.

    Geographic coverage

    National Coverage

    Analysis unit

    Individual

    Kind of data

    Observation data/ratings [obs]

    Sampling procedure

    In most low- and middle-income economies, Global Findex data were collected through face-to-face interviews. In these economies, an area frame design was used for interviewing. In most high-income economies, telephone surveys were used. In 2024, face-to-face interviews were again conducted in 22 economies after phone-based surveys had been employed in 2021 as a result of mobility restrictions related to COVID-19. In addition, an abridged form of the questionnaire was administered by phone to survey participants in Algeria, China, the Islamic Republic of Iran, Libya, Mauritius, and Ukraine because of economy-specific restrictions. In just one economy, Singapore, did the interviewing mode change from face to face in 2021 to phone based in 2024.

    In economies in which face-to-face surveys were conducted, the first stage of sampling was the identification of primary sampling units. These units were then stratified by population size, geography, or both and clustered through one or more stages of sampling. Where population information was available, sample selection was based on probabilities proportional to population size; otherwise, simple random sampling was used. Random route procedures were used to select sampled households. Unless an outright refusal occurred, interviewers made up to three attempts to survey each sampled household. To increase the probability of contact and completion, attempts were made at different times of the day and, where possible, on different days. If an interview could not be completed at a household that was initially part of the sample, a simple substitution method was used to select a replacement household for inclusion.

    Respondents were randomly selected within sampled households. Each eligible household member (that is, all those ages 15 or older) was listed, and a handheld survey device randomly selected the household member to be interviewed. For paper surveys, the Kish grid method was used to select the respondent. In economies in which cultural restrictions dictated gender matching, respondents were randomly selected from among all eligible adults of the interviewer’s gender.

    In economies in which Global Findex surveys have traditionally been phone based, respondent selection followed the same procedure as in previous years, using random digit dialing or a nationally representative list of phone numbers. In most economies in which mobile phone and landline penetration is high, a dual sampling frame was used.

    The same procedure for respondent selection was applied to economies in which phone-based interviews were being conducted for the first time. Dual-frame (landline and mobile phone) random digit dialing was used where landline presence and use are 20 percent or higher based on historical Gallup estimates. Mobile phone random digit dialing was used in economies with limited or no landline presence (less than 20 percent). For landline respondents in economies in which mobile phone or landline penetration is 80 percent or higher, respondents were selected randomly by using either the next-birthday method or the household enumeration method, which involves listing all eligible household members and randomly selecting one to participate. For mobile phone respondents in these economies or in economies in which mobile phone or landline penetration is less than 80 percent, no further selection was performed. At least three attempts were made to reach the randomly selected person in each household, spread over different days and times of day.

    Research instrument

    The English version of the questionnaire is provided for download.

    Sampling error estimates

    Estimates of standard errors (which account for sampling error) vary by country and indicator. For country-specific margins of error, please refer to the Methodology section and corresponding table in: Klapper, Leora, Dorothe Singer, Laura Starita, and Alexandra Norris. 2025. The Global Findex Database 2025: Connectivity and Financial Inclusion in the Digital Economy. Washington, DC: World Bank. https://doi.org/10.1596/978-1-4648-2204-9.

  10. Number of millionaires Pakistan 2006-2026

    • statista.com
    Updated Nov 28, 2025
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    Statista (2025). Number of millionaires Pakistan 2006-2026 [Dataset]. https://www.statista.com/statistics/785036/pakistan-number-of-millionaires/
    Explore at:
    Dataset updated
    Nov 28, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    Pakistan
    Description

    In 2016, there were approximately **** thousand millionaires in Pakistan. The number of individuals owning one million U.S. dollars or more in Pakistan is expected to rise to **** thousand by 2026. HNWI forecast in Pakistan Individuals with investible assets of at least one million U.S. dollars in current exchange rate terms are considered high net worth. The number of high-net-worth individuals in Pakistan is expected to rise overall between 2022 and 2028, settling at just under ***** thousand individuals. Countries with the highest millionaire rate In 2021, Switzerland had the highest rate of millionaires in the world, with **** percent of the adult population owning assets worth more than one million U.S. dollars. Luxembourg came in second, with **** percent of the population being millionaires, and Iceland came in third. Furthermore, over ** million people in the United States were among the world's top one percent of ultra-high net-worth individuals in 2021. China came second, with over **** million top one percent wealth holders worldwide.

  11. Africa wealth distribution 2021, by region

    • statista.com
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    Statista, Africa wealth distribution 2021, by region [Dataset]. https://www.statista.com/statistics/1411174/africa-wealth-distribution-region/
    Explore at:
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    Africa
    Description

    In 2021, Southern Africa's richest ** percent held around ** percent of the total wealth. Furthermore, the richest one percent in the region held over ** percent. The other African regions had a slightly smaller share of wealth with the wealthiest people. For instance, in West Africa, the richest ** percent held close to ** percent of the wealth, while the richest one percent held ** percent. On the other hand. The poorest ** percent in all the regions held lower than ***** percent of the wealth.

  12. w

    The Global Findex Database 2025: Connectivity and Financial Inclusion in the...

    • microdata.worldbank.org
    Updated Oct 1, 2025
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    Development Research Group, Finance and Private Sector Development Unit (2025). The Global Findex Database 2025: Connectivity and Financial Inclusion in the Digital Economy - Sierra Leone [Dataset]. https://microdata.worldbank.org/index.php/catalog/7973
    Explore at:
    Dataset updated
    Oct 1, 2025
    Dataset authored and provided by
    Development Research Group, Finance and Private Sector Development Unit
    Time period covered
    2024
    Area covered
    Sierra Leone
    Description

    Abstract

    The Global Findex 2025 reveals how mobile technology is equipping more adults around the world to own and use financial accounts to save formally, access credit, make and receive digital payments, and pursue opportunities. Including the inaugural Global Findex Digital Connectivity Tracker, this fifth edition of Global Findex presents new insights on the interactions among mobile phone ownership, internet use, and financial inclusion.

    The Global Findex is the world’s most comprehensive database on digital and financial inclusion. It is also the only global source of comparable demand-side data, allowing cross-country analysis of how adults access and use mobile phones, the internet, and financial accounts to reach digital information and resources, save, borrow, make payments, and manage their financial health. Data for the Global Findex 2025 were collected from nationally representative surveys of about 145,000 adults in 141 economies. The latest edition follows the 2011, 2014, 2017, and 2021 editions and includes new series measuring mobile phone ownership and internet use, digital safety, and frequency of transactions using financial services.

    The Global Findex 2025 is an indispensable resource for policy makers in the fields of digital connectivity and financial inclusion, as well as for practitioners, researchers, and development professionals.

    Geographic coverage

    National Coverage

    Analysis unit

    Individual

    Kind of data

    Observation data/ratings [obs]

    Sampling procedure

    In most low- and middle-income economies, Global Findex data were collected through face-to-face interviews. In these economies, an area frame design was used for interviewing. In most high-income economies, telephone surveys were used. In 2024, face-to-face interviews were again conducted in 22 economies after phone-based surveys had been employed in 2021 as a result of mobility restrictions related to COVID-19. In addition, an abridged form of the questionnaire was administered by phone to survey participants in Algeria, China, the Islamic Republic of Iran, Libya, Mauritius, and Ukraine because of economy-specific restrictions. In just one economy, Singapore, did the interviewing mode change from face to face in 2021 to phone based in 2024.

    In economies in which face-to-face surveys were conducted, the first stage of sampling was the identification of primary sampling units. These units were then stratified by population size, geography, or both and clustered through one or more stages of sampling. Where population information was available, sample selection was based on probabilities proportional to population size; otherwise, simple random sampling was used. Random route procedures were used to select sampled households. Unless an outright refusal occurred, interviewers made up to three attempts to survey each sampled household. To increase the probability of contact and completion, attempts were made at different times of the day and, where possible, on different days. If an interview could not be completed at a household that was initially part of the sample, a simple substitution method was used to select a replacement household for inclusion.

    Respondents were randomly selected within sampled households. Each eligible household member (that is, all those ages 15 or older) was listed, and a handheld survey device randomly selected the household member to be interviewed. For paper surveys, the Kish grid method was used to select the respondent. In economies in which cultural restrictions dictated gender matching, respondents were randomly selected from among all eligible adults of the interviewer’s gender.

    In economies in which Global Findex surveys have traditionally been phone based, respondent selection followed the same procedure as in previous years, using random digit dialing or a nationally representative list of phone numbers. In most economies in which mobile phone and landline penetration is high, a dual sampling frame was used.

    The same procedure for respondent selection was applied to economies in which phone-based interviews were being conducted for the first time. Dual-frame (landline and mobile phone) random digit dialing was used where landline presence and use are 20 percent or higher based on historical Gallup estimates. Mobile phone random digit dialing was used in economies with limited or no landline presence (less than 20 percent). For landline respondents in economies in which mobile phone or landline penetration is 80 percent or higher, respondents were selected randomly by using either the next-birthday method or the household enumeration method, which involves listing all eligible household members and randomly selecting one to participate. For mobile phone respondents in these economies or in economies in which mobile phone or landline penetration is less than 80 percent, no further selection was performed. At least three attempts were made to reach the randomly selected person in each household, spread over different days and times of day.

    Research instrument

    The English version of the questionnaire is provided for download.

    Sampling error estimates

    Estimates of standard errors (which account for sampling error) vary by country and indicator. For country-specific margins of error, please refer to the Methodology section and corresponding table in: Klapper, Leora, Dorothe Singer, Laura Starita, and Alexandra Norris. 2025. The Global Findex Database 2025: Connectivity and Financial Inclusion in the Digital Economy. Washington, DC: World Bank. https://doi.org/10.1596/978-1-4648-2204-9.

  13. Russia: population by wealth bracket 2022

    • statista.com
    Updated Nov 28, 2025
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    Statista (2025). Russia: population by wealth bracket 2022 [Dataset]. https://www.statista.com/statistics/482573/russia-population-by-average-wealth/
    Explore at:
    Dataset updated
    Nov 28, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    2022
    Area covered
    Russia, Russia
    Description

    Over ** million Russians aged 20 years and above, or approximately ** percent of the total adult population of the country, had wealth under 10,000 U.S. dollars in 2022. To compare, on average around the globe, the share of residents belonging to this wealth range was measured at **** percent in the same year. Economic inequality in Russia The latest available data by the World Bank recorded Russia’s Gini index, used as a measurement of income or wealth inequality, at **. The organization classified Russia as an upper-middle-income economy. Over ** percent of Russians considered themselves belonging to the middle class in 2020. HNWIs in Russia Approximately *** percent of Russian adults, or ******* residents, owned over *********** U.S. dollars, or were referred to as high-net-worth individuals (HNWIs). In 2021, the total wealth of the adult population in the country reached nearly *** trillion U.S. dollars. A significant portion of it belonged to roughly ***** ultra-high-net-worth individuals (UHNWIs) whose net worth exceeded ** billion U.S. dollars.

  14. Nestlé's net income 2005-2024

    • statista.com
    Updated Jun 23, 2025
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    Statista (2025). Nestlé's net income 2005-2024 [Dataset]. https://www.statista.com/statistics/268889/net-profit-of-the-nestle-group-worldwide/
    Explore at:
    Dataset updated
    Jun 23, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    Worldwide, Switzerland
    Description

    The Nestlé Group’s net income rose from about *** billion in 2017 to roughly **** billion Swiss Francs in 2024. Nestlé is one of the world’s largest food and beverage companies, accounting for over 2000 brands in over 180 countries. Nestlé worldwide Nestlé is a multinational food and drink corporation based in Vaud, Switzerland. In 2024, the Swiss company generated about ** percent of its global sales in North America, Nestlé’s largest market. Roughly ** percent was earned in Europe that year. Asia, Oceania, and Africa (AOC) followed with about ** percent. Nestlé’s product categories In 2021, Nestlé Group’s top-selling products based on global sales were powdered and liquid beverages, which made almost ** billion Swiss Francs that year. PetCare stood in second place with just under ** billion Swiss Francs. In terms of, organic sales growth, PetCare is the fastest growing category.

  15. Apple net income 2005-2025

    • statista.com
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    Statista, Apple net income 2005-2025 [Dataset]. https://www.statista.com/statistics/267728/apples-net-income-since-2005/
    Explore at:
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    Worldwide
    Description

    Apple reported a net income of 112 billion U.S. dollars in its 2025 fiscal year, up from the highest net income to date in 2022. Apple’s global revenue amounted to 416 billion U.S. dollars in that same year. Founded in 1976 in California by Steve Jobs, Steve Wozniak, and Ronald Wayne, Apple has over the years developed into one of the most valuable brands worldwide. The fiscal year end of the company is September 30th. Apple’s products The product that contributed most to Apple’s success is the iPhone, which brought in 52 billion U.S. dollars sales revenue in the first quarter of 2019 alone. Revenues generated from iPhone sales consistently make up around 50 percent of Apple’s overall revenue in recent years. Other major Apple products include consumer electronic devices such as the Mac computers, iPad, Apple Watch and the smart speaker HomePod. Apple’s service products, such as the iTunes Store and iCloud, are becoming a greater part of the company’s business and provides new sources of revenue stream.

  16. Birth rate by family income in the U.S. 2021

    • statista.com
    • akomarchitects.com
    Updated Nov 28, 2025
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    Statista (2025). Birth rate by family income in the U.S. 2021 [Dataset]. https://www.statista.com/statistics/241530/birth-rate-by-family-income-in-the-us/
    Explore at:
    Dataset updated
    Nov 28, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    2021
    Area covered
    United States
    Description

    In 2021, the birth rate in the United States was highest in families that had under 10,000 U.S. dollars in income per year, at 62.75 births per 1,000 women. As the income scale increases, the birth rate decreases, with families making 200,000 U.S. dollars or more per year having the second-lowest birth rate, at 47.57 births per 1,000 women. Income and the birth rate Income and high birth rates are strongly linked, not just in the United States, but around the world. Women in lower income brackets tend to have higher birth rates across the board. There are many factors at play in birth rates, such as the education level of the mother, ethnicity of the mother, and even where someone lives. The fertility rate in the United States The fertility rate in the United States has declined in recent years, and it seems that more and more women are waiting longer to begin having children. Studies have shown that the average age of the mother at the birth of their first child in the United States was 27.4 years old, although this figure varies for different ethnic origins.

  17. Distribution of tax revenues worldwide 2019, by type

    • statista.com
    Updated Jan 16, 2023
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    Statista (2023). Distribution of tax revenues worldwide 2019, by type [Dataset]. https://www.statista.com/statistics/1359813/distriution-tax-revenues-worldwide-type/
    Explore at:
    Dataset updated
    Jan 16, 2023
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    2019
    Area covered
    Worldwide, OECD
    Description

    Between December 2019 and 2021, the top one percent of earners accumulated ** percent of all new wealth worldwide. Despite this, only **** percent of the average tax revenues of ** OECD- and ** non-OECD members in 2019 came from wealth taxes. The largest share of tax revenues came from VAT and other consumption taxes, while nearly ** percent were personal income taxes.

  18. w

    The Global Findex Database 2025: Connectivity and Financial Inclusion in the...

    • microdata.worldbank.org
    Updated Oct 1, 2025
    + more versions
    Share
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    Development Research Group, Finance and Private Sector Development Unit (2025). The Global Findex Database 2025: Connectivity and Financial Inclusion in the Digital Economy - Pakistan [Dataset]. https://microdata.worldbank.org/index.php/catalog/7961
    Explore at:
    Dataset updated
    Oct 1, 2025
    Dataset authored and provided by
    Development Research Group, Finance and Private Sector Development Unit
    Time period covered
    2024
    Area covered
    Pakistan
    Description

    Abstract

    The Global Findex 2025 reveals how mobile technology is equipping more adults around the world to own and use financial accounts to save formally, access credit, make and receive digital payments, and pursue opportunities. Including the inaugural Global Findex Digital Connectivity Tracker, this fifth edition of Global Findex presents new insights on the interactions among mobile phone ownership, internet use, and financial inclusion.

    The Global Findex is the world’s most comprehensive database on digital and financial inclusion. It is also the only global source of comparable demand-side data, allowing cross-country analysis of how adults access and use mobile phones, the internet, and financial accounts to reach digital information and resources, save, borrow, make payments, and manage their financial health. Data for the Global Findex 2025 were collected from nationally representative surveys of about 145,000 adults in 141 economies. The latest edition follows the 2011, 2014, 2017, and 2021 editions and includes new series measuring mobile phone ownership and internet use, digital safety, and frequency of transactions using financial services.

    The Global Findex 2025 is an indispensable resource for policy makers in the fields of digital connectivity and financial inclusion, as well as for practitioners, researchers, and development professionals.

    Geographic coverage

    National Coverage

    Analysis unit

    Individual

    Kind of data

    Observation data/ratings [obs]

    Sampling procedure

    In most low- and middle-income economies, Global Findex data were collected through face-to-face interviews. In these economies, an area frame design was used for interviewing. In most high-income economies, telephone surveys were used. In 2024, face-to-face interviews were again conducted in 22 economies after phone-based surveys had been employed in 2021 as a result of mobility restrictions related to COVID-19. In addition, an abridged form of the questionnaire was administered by phone to survey participants in Algeria, China, the Islamic Republic of Iran, Libya, Mauritius, and Ukraine because of economy-specific restrictions. In just one economy, Singapore, did the interviewing mode change from face to face in 2021 to phone based in 2024.

    In economies in which face-to-face surveys were conducted, the first stage of sampling was the identification of primary sampling units. These units were then stratified by population size, geography, or both and clustered through one or more stages of sampling. Where population information was available, sample selection was based on probabilities proportional to population size; otherwise, simple random sampling was used. Random route procedures were used to select sampled households. Unless an outright refusal occurred, interviewers made up to three attempts to survey each sampled household. To increase the probability of contact and completion, attempts were made at different times of the day and, where possible, on different days. If an interview could not be completed at a household that was initially part of the sample, a simple substitution method was used to select a replacement household for inclusion.

    Respondents were randomly selected within sampled households. Each eligible household member (that is, all those ages 15 or older) was listed, and a handheld survey device randomly selected the household member to be interviewed. For paper surveys, the Kish grid method was used to select the respondent. In economies in which cultural restrictions dictated gender matching, respondents were randomly selected from among all eligible adults of the interviewer’s gender.

    In economies in which Global Findex surveys have traditionally been phone based, respondent selection followed the same procedure as in previous years, using random digit dialing or a nationally representative list of phone numbers. In most economies in which mobile phone and landline penetration is high, a dual sampling frame was used.

    The same procedure for respondent selection was applied to economies in which phone-based interviews were being conducted for the first time. Dual-frame (landline and mobile phone) random digit dialing was used where landline presence and use are 20 percent or higher based on historical Gallup estimates. Mobile phone random digit dialing was used in economies with limited or no landline presence (less than 20 percent). For landline respondents in economies in which mobile phone or landline penetration is 80 percent or higher, respondents were selected randomly by using either the next-birthday method or the household enumeration method, which involves listing all eligible household members and randomly selecting one to participate. For mobile phone respondents in these economies or in economies in which mobile phone or landline penetration is less than 80 percent, no further selection was performed. At least three attempts were made to reach the randomly selected person in each household, spread over different days and times of day.

    Research instrument

    The English version of the questionnaire is provided for download.

    Sampling error estimates

    Estimates of standard errors (which account for sampling error) vary by country and indicator. For country-specific margins of error, please refer to the Methodology section and corresponding table in: Klapper, Leora, Dorothe Singer, Laura Starita, and Alexandra Norris. 2025. The Global Findex Database 2025: Connectivity and Financial Inclusion in the Digital Economy. Washington, DC: World Bank. https://doi.org/10.1596/978-1-4648-2204-9.

  19. w

    The Global Findex Database 2025: Connectivity and Financial Inclusion in the...

    • microdata.worldbank.org
    Updated Oct 1, 2025
    + more versions
    Share
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    Development Research Group, Finance and Private Sector Development Unit (2025). The Global Findex Database 2025: Connectivity and Financial Inclusion in the Digital Economy - Bolivia [Dataset]. https://microdata.worldbank.org/index.php/catalog/7873
    Explore at:
    Dataset updated
    Oct 1, 2025
    Dataset authored and provided by
    Development Research Group, Finance and Private Sector Development Unit
    Time period covered
    2024
    Area covered
    Bolivia
    Description

    Abstract

    The Global Findex 2025 reveals how mobile technology is equipping more adults around the world to own and use financial accounts to save formally, access credit, make and receive digital payments, and pursue opportunities. Including the inaugural Global Findex Digital Connectivity Tracker, this fifth edition of Global Findex presents new insights on the interactions among mobile phone ownership, internet use, and financial inclusion.

    The Global Findex is the world’s most comprehensive database on digital and financial inclusion. It is also the only global source of comparable demand-side data, allowing cross-country analysis of how adults access and use mobile phones, the internet, and financial accounts to reach digital information and resources, save, borrow, make payments, and manage their financial health. Data for the Global Findex 2025 were collected from nationally representative surveys of about 145,000 adults in 141 economies. The latest edition follows the 2011, 2014, 2017, and 2021 editions and includes new series measuring mobile phone ownership and internet use, digital safety, and frequency of transactions using financial services.

    The Global Findex 2025 is an indispensable resource for policy makers in the fields of digital connectivity and financial inclusion, as well as for practitioners, researchers, and development professionals.

    Geographic coverage

    National Coverage

    Analysis unit

    Individual

    Kind of data

    Observation data/ratings [obs]

    Sampling procedure

    In most low- and middle-income economies, Global Findex data were collected through face-to-face interviews. In these economies, an area frame design was used for interviewing. In most high-income economies, telephone surveys were used. In 2024, face-to-face interviews were again conducted in 22 economies after phone-based surveys had been employed in 2021 as a result of mobility restrictions related to COVID-19. In addition, an abridged form of the questionnaire was administered by phone to survey participants in Algeria, China, the Islamic Republic of Iran, Libya, Mauritius, and Ukraine because of economy-specific restrictions. In just one economy, Singapore, did the interviewing mode change from face to face in 2021 to phone based in 2024.

    In economies in which face-to-face surveys were conducted, the first stage of sampling was the identification of primary sampling units. These units were then stratified by population size, geography, or both and clustered through one or more stages of sampling. Where population information was available, sample selection was based on probabilities proportional to population size; otherwise, simple random sampling was used. Random route procedures were used to select sampled households. Unless an outright refusal occurred, interviewers made up to three attempts to survey each sampled household. To increase the probability of contact and completion, attempts were made at different times of the day and, where possible, on different days. If an interview could not be completed at a household that was initially part of the sample, a simple substitution method was used to select a replacement household for inclusion.

    Respondents were randomly selected within sampled households. Each eligible household member (that is, all those ages 15 or older) was listed, and a handheld survey device randomly selected the household member to be interviewed. For paper surveys, the Kish grid method was used to select the respondent. In economies in which cultural restrictions dictated gender matching, respondents were randomly selected from among all eligible adults of the interviewer’s gender.

    In economies in which Global Findex surveys have traditionally been phone based, respondent selection followed the same procedure as in previous years, using random digit dialing or a nationally representative list of phone numbers. In most economies in which mobile phone and landline penetration is high, a dual sampling frame was used.

    The same procedure for respondent selection was applied to economies in which phone-based interviews were being conducted for the first time. Dual-frame (landline and mobile phone) random digit dialing was used where landline presence and use are 20 percent or higher based on historical Gallup estimates. Mobile phone random digit dialing was used in economies with limited or no landline presence (less than 20 percent). For landline respondents in economies in which mobile phone or landline penetration is 80 percent or higher, respondents were selected randomly by using either the next-birthday method or the household enumeration method, which involves listing all eligible household members and randomly selecting one to participate. For mobile phone respondents in these economies or in economies in which mobile phone or landline penetration is less than 80 percent, no further selection was performed. At least three attempts were made to reach the randomly selected person in each household, spread over different days and times of day.

    Research instrument

    The English version of the questionnaire is provided for download.

    Sampling error estimates

    Estimates of standard errors (which account for sampling error) vary by country and indicator. For country-specific margins of error, please refer to the Methodology section and corresponding table in: Klapper, Leora, Dorothe Singer, Laura Starita, and Alexandra Norris. 2025. The Global Findex Database 2025: Connectivity and Financial Inclusion in the Digital Economy. Washington, DC: World Bank. https://doi.org/10.1596/978-1-4648-2204-9.

  20. w

    The Global Findex Database 2025: Connectivity and Financial Inclusion in the...

    • microdata.worldbank.org
    Updated Oct 1, 2025
    Share
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    Development Research Group, Finance and Private Sector Development Unit (2025). The Global Findex Database 2025: Connectivity and Financial Inclusion in the Digital Economy - Oman [Dataset]. https://microdata.worldbank.org/index.php/catalog/7960
    Explore at:
    Dataset updated
    Oct 1, 2025
    Dataset authored and provided by
    Development Research Group, Finance and Private Sector Development Unit
    Time period covered
    2024
    Area covered
    Oman
    Description

    Abstract

    The Global Findex 2025 reveals how mobile technology is equipping more adults around the world to own and use financial accounts to save formally, access credit, make and receive digital payments, and pursue opportunities. Including the inaugural Global Findex Digital Connectivity Tracker, this fifth edition of Global Findex presents new insights on the interactions among mobile phone ownership, internet use, and financial inclusion.

    The Global Findex is the world’s most comprehensive database on digital and financial inclusion. It is also the only global source of comparable demand-side data, allowing cross-country analysis of how adults access and use mobile phones, the internet, and financial accounts to reach digital information and resources, save, borrow, make payments, and manage their financial health. Data for the Global Findex 2025 were collected from nationally representative surveys of about 145,000 adults in 141 economies. The latest edition follows the 2011, 2014, 2017, and 2021 editions and includes new series measuring mobile phone ownership and internet use, digital safety, and frequency of transactions using financial services.

    The Global Findex 2025 is an indispensable resource for policy makers in the fields of digital connectivity and financial inclusion, as well as for practitioners, researchers, and development professionals.

    Geographic coverage

    National Coverage

    Analysis unit

    Individual

    Kind of data

    Observation data/ratings [obs]

    Sampling procedure

    In most low- and middle-income economies, Global Findex data were collected through face-to-face interviews. In these economies, an area frame design was used for interviewing. In most high-income economies, telephone surveys were used. In 2024, face-to-face interviews were again conducted in 22 economies after phone-based surveys had been employed in 2021 as a result of mobility restrictions related to COVID-19. In addition, an abridged form of the questionnaire was administered by phone to survey participants in Algeria, China, the Islamic Republic of Iran, Libya, Mauritius, and Ukraine because of economy-specific restrictions. In just one economy, Singapore, did the interviewing mode change from face to face in 2021 to phone based in 2024.

    In economies in which face-to-face surveys were conducted, the first stage of sampling was the identification of primary sampling units. These units were then stratified by population size, geography, or both and clustered through one or more stages of sampling. Where population information was available, sample selection was based on probabilities proportional to population size; otherwise, simple random sampling was used. Random route procedures were used to select sampled households. Unless an outright refusal occurred, interviewers made up to three attempts to survey each sampled household. To increase the probability of contact and completion, attempts were made at different times of the day and, where possible, on different days. If an interview could not be completed at a household that was initially part of the sample, a simple substitution method was used to select a replacement household for inclusion.

    Respondents were randomly selected within sampled households. Each eligible household member (that is, all those ages 15 or older) was listed, and a handheld survey device randomly selected the household member to be interviewed. For paper surveys, the Kish grid method was used to select the respondent. In economies in which cultural restrictions dictated gender matching, respondents were randomly selected from among all eligible adults of the interviewer’s gender.

    In economies in which Global Findex surveys have traditionally been phone based, respondent selection followed the same procedure as in previous years, using random digit dialing or a nationally representative list of phone numbers. In most economies in which mobile phone and landline penetration is high, a dual sampling frame was used.

    The same procedure for respondent selection was applied to economies in which phone-based interviews were being conducted for the first time. Dual-frame (landline and mobile phone) random digit dialing was used where landline presence and use are 20 percent or higher based on historical Gallup estimates. Mobile phone random digit dialing was used in economies with limited or no landline presence (less than 20 percent). For landline respondents in economies in which mobile phone or landline penetration is 80 percent or higher, respondents were selected randomly by using either the next-birthday method or the household enumeration method, which involves listing all eligible household members and randomly selecting one to participate. For mobile phone respondents in these economies or in economies in which mobile phone or landline penetration is less than 80 percent, no further selection was performed. At least three attempts were made to reach the randomly selected person in each household, spread over different days and times of day.

    Research instrument

    The English version of the questionnaire is provided for download.

    Sampling error estimates

    Estimates of standard errors (which account for sampling error) vary by country and indicator. For country-specific margins of error, please refer to the Methodology section and corresponding table in: Klapper, Leora, Dorothe Singer, Laura Starita, and Alexandra Norris. 2025. The Global Findex Database 2025: Connectivity and Financial Inclusion in the Digital Economy. Washington, DC: World Bank. https://doi.org/10.1596/978-1-4648-2204-9.

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Statista (2023). Global accumulation of new wealth 2019-2021, by income percentile [Dataset]. https://www.statista.com/statistics/1359627/new-wealth-accumulation-worldwide-income/
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Global accumulation of new wealth 2019-2021, by income percentile

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Dataset updated
Jan 16, 2023
Dataset authored and provided by
Statistahttp://statista.com/
Area covered
Worldwide
Description

Between December 2019 and 2021, the top one percent of earners accumulated 63 percent of all new wealth worldwide. This is more than six times more wealth than accumulated by the bottom 90 percent over the same time period.

Global wealth distribution Newly generated wealth landing in the hands of the few is not a new story and has been the focus of international development policy for many years. Looking at a regional level, Latin America was the region with the starkest distribution of wealth. In this region, 77 percent of the wealth was held by the richest 10 percent in 2021, and only 0.5 percent held by the poorest 50 percent. At an individual level, around 2.82 billion adults worldwide had a net worth of less than 10,000 U.S. dollars in 2021.

Billionaires In 2021, the highest concentration of billionaires could be found in North America. However, China had the largest number of billionaires in its population in 2022, with most living in Beijing. Looking at wealth distribution amongst billionaires themselves, 20 people had fortunes of 50 billion U.S. dollars or more, but the majority of billionaires had a personal fortune between two and five billion U.S. dollars.

In December 2022, Elon Musk slipped from the top spot of richest people on Earth. The number one spot was taken by French magnate, Bernard Arnault of Moët Hennessy Louis Vuitton.

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