This comprehensive dataset encapsulates a detailed snapshot of the wealthiest individuals globally, as listed by Forbes in 2024. Compiled through meticulous web scraping and data aggregation, the dataset includes a wide range of attributes for each billionaire. Fields encompass basic personal information such as name, age, and gender, alongside financial details including net worth and sources of wealth. The dataset further delves into aspects like industry involvement, organizational affiliations, philanthropic endeavors, and educational backgrounds.

Key attributes in this dataset include:

Name: Full legal name of the billionaire. Age: Age of the individual. 2024 Net Worth: Estimated net worth in USD for the year 2024. Industry: Primary industry or sector of operation. Source of Wealth: Origin of the billionaire’s wealth. Title: Professional title or position. Organization: Name of the associated organization. Self-Made: Indicator if the wealth is self-made. Self-Made Score: A quantitative score assessing how self-made their wealth is. Philanthropy Score: A score reflecting the extent of their philanthropic activities. Residence: Main residence of the individual. Citizenship: Legal citizenship. Gender: Gender identity. Marital Status: Current marital status. Children: Number of children. Education: Highest level of education attained.

This dataset is ideal for analysis, offering insights into the distribution of wealth, the influence of education on wealth accumulation, and trends across different industries. It also provides a foundation for exploring the impact of socioeconomic factors on personal wealth. The data were collected and formatted with careful consideration to ensure accuracy, making it a valuable resource for researchers, economists, and anyone interested in the dynamics of wealth and success.

Please note that some data is missing in this dataset, primarily due to the unavailability of information from Forbes. This issue becomes more prevalent beyond the top 400 entries. Many individuals lack a self-made score, a philanthropy score, or specific details regarding their title or organization as per Forbes' listings. I am currently working to update the dataset with this missing information. However, this update process is quite tedious and time-consuming since it is mostly manual. I appreciate your patience and understanding as I work through these details.

Costa Rica CR: Account: Income: Richest 60%: % Aged 15+ data was reported at 66.721 % in 2014. This records an increase from the previous number of 60.007 % for 2011. Costa Rica CR: Account: Income: Richest 60%: % Aged 15+ data is updated yearly, averaging 63.364 % from Dec 2011 (Median) to 2014, with 2 observations. The data reached an all-time high of 66.721 % in 2014 and a record low of 60.007 % in 2011. Costa Rica CR: Account: Income: Richest 60%: % Aged 15+ data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Costa Rica – Table CR.World Bank.WDI: Banking Indicators. Denotes the percentage of respondents who report having an account (by themselves or together with someone else). For 2011, this can be an account at a bank or another type of financial institution, and for 2014 this can be a mobile account as well (see year-specific definitions for details) (income, richest 60%, % age 15+). [ts: data are available for multiple waves].; ; Demirguc-Kunt et al., 2015, Global Financial Inclusion Database, World Bank.; Weighted average;

Coverage of Social Insurance Programs in Richest Quintile

Percent of Population Eligible

By data.world's Admin [source]

About this dataset

This dataset offers a unique insight into the coverage of social insurance programs for the wealthiest quintile of populations around the world. It reveals how many individuals in each country are receiving support from old age contributory pensions, disability benefits, and social security and health insurance benefits such as occupational injury benefits, paid sick leave, maternity leave, and more. This data provides an invaluable resource to understand the health and well-being of those most financially privileged in society – often having greater impact on decision making than other groups. With up-to-date figures from 2019-05-11 this dataset is invaluable in uncovering where there is work to be done for improved healthcare provision in each country across the world

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How to use the dataset

• Understand the context: Before you begin analyzing this dataset, it is important to understand the information that it provides. Take some time to read the description of what is included in the dataset, including a clear understanding of the definitions and scope of coverage provided with each data point.

• Examine the data: Once you have a general understanding of this dataset's contents, take some time to explore its contents in more depth. What specific questions does this dataset help answer? What kind of insights does it provide? Are there any missing pieces?

• Clean & Prepare Data: After you've preliminarily examined its content, start preparing your data for further analysis and visualization. Clean up any formatting issues or irregularities present in your data set by correcting typos and eliminating unnecessary rows or columns before working with your chosen programming language (I prefer R for data manipulation tasks). Additionally, consider performing necessary transformations such as sorting or averaging values if appropriate for the findings you wish to draw from your analysis.

• Visualize Results: Once you've cleaned and prepared your data, use visualizations such as charts, graphs or tables to reveal patterns within it that support specific conclusions about how insurance coverage under social programs vary among different groups within society's quintiles - based on age groups etc.. This type of visualization allows those who aren't familiar with programming to process complex information quickly and accurately than when displayed numerically in tabular form only!

5 Final Analysis & Export Results: Finally export your visuals into presentation-ready formats (e.g., PDFs) which can be shared with colleagues! Additionally use these results as part of a narrative conclusion report providing an accurate assessment and meaningful interpretation about how social insurance programs vary between different members within society's quintiles (i..e., accordingest vs poorest), along with potential policy implications relevant for implementing effective strategies that improve access accordingly!

Research Ideas

• Analyzing the effectiveness of social insurance programs by comparing the coverage levels across different geographic areas or socio-economic groups;
• Estimating the economic impact of social insurance programs on local and national economies by tracking spending levels and revenues generated;
• Identifying potential problems with access to social insurance benefits, such as racial or gender disparities in benefit coverage

Acknowledgements

If you use this dataset in your research, please credit the original authors. Data Source

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: coverage-of-social-insurance-programs-in-richest-quintile-of-population-1.csv

Acknowledgements

If you use this dataset in your research, please credit the original authors. If you use this dataset in your research, please credit data.world's Admin.

United States US: Account: Income: Richest 60%: % Aged 15+ data was reported at 97.904 % in 2014. This records an increase from the previous number of 92.810 % for 2011. United States US: Account: Income: Richest 60%: % Aged 15+ data is updated yearly, averaging 95.357 % from Dec 2011 (Median) to 2014, with 2 observations. The data reached an all-time high of 97.904 % in 2014 and a record low of 92.810 % in 2011. United States US: Account: Income: Richest 60%: % Aged 15+ data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s United States – Table US.World Bank.WDI: Banking Indicators. Denotes the percentage of respondents who report having an account (by themselves or together with someone else). For 2011, this can be an account at a bank or another type of financial institution, and for 2014 this can be a mobile account as well (see year-specific definitions for details) (income, richest 60%, % age 15+). [ts: data are available for multiple waves].; ; Demirguc-Kunt et al., 2015, Global Financial Inclusion Database, World Bank.; Weighted average;

Australia Account: Income: Richest 60%: % Aged 15+ data was reported at 99.159 % in 2014. This records a decrease from the previous number of 99.729 % for 2011. Australia Account: Income: Richest 60%: % Aged 15+ data is updated yearly, averaging 99.444 % from Dec 2011 (Median) to 2014, with 2 observations. The data reached an all-time high of 99.729 % in 2011 and a record low of 99.159 % in 2014. Australia Account: Income: Richest 60%: % Aged 15+ data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Australia – Table AU.World Bank.WDI: Banking Indicators. Denotes the percentage of respondents who report having an account (by themselves or together with someone else). For 2011, this can be an account at a bank or another type of financial institution, and for 2014 this can be a mobile account as well (see year-specific definitions for details) (income, richest 60%, % age 15+). [ts: data are available for multiple waves].; ; Demirguc-Kunt et al., 2015, Global Financial Inclusion Database, World Bank.; Weighted average;

Data for the last five years. Interesting dynamics of capitalization of companies. How do people make money in technology companies.

Inspiration

What trends are waiting for us this year?

Norway NO: Bank Account Ownership at a Financial Institution or with a Mobile-Money-Service Provider, Richest 60%: % of Population Aged 15+ data was reported at 100.000 % in 2017. This stayed constant from the previous number of 100.000 % for 2014. Norway NO: Bank Account Ownership at a Financial Institution or with a Mobile-Money-Service Provider, Richest 60%: % of Population Aged 15+ data is updated yearly, averaging 100.000 % from Dec 2014 (Median) to 2017, with 2 observations. The data reached an all-time high of 100.000 % in 2017 and a record low of 100.000 % in 2017. Norway NO: Bank Account Ownership at a Financial Institution or with a Mobile-Money-Service Provider, Richest 60%: % of Population Aged 15+ data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Norway – Table NO.World Bank: Bank Account Ownership. Account denotes the percentage of respondents who report having an account (by themselves or together with someone else) at a bank or another type of financial institution or report personally using a mobile money service in the past 12 months (richest 60%, share of population ages 15+).; ; Demirguc-Kunt et al., 2018, Global Financial Inclusion Database, World Bank.; Weighted Average; Each economy is classified based on the classification of World Bank Group's fiscal year 2018 (July 1, 2017-June 30, 2018).

Libya LY: Bank Account Ownership at a Financial Institution or with a Mobile-Money-Service Provider, Richest 60%: % of Population Aged 15+ data was reported at 70.582 % in 2017. Libya LY: Bank Account Ownership at a Financial Institution or with a Mobile-Money-Service Provider, Richest 60%: % of Population Aged 15+ data is updated yearly, averaging 70.582 % from Dec 2017 (Median) to 2017, with 1 observations. Libya LY: Bank Account Ownership at a Financial Institution or with a Mobile-Money-Service Provider, Richest 60%: % of Population Aged 15+ data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Libya – Table LY.World Bank.WDI: Bank Account Ownership. Account denotes the percentage of respondents who report having an account (by themselves or together with someone else) at a bank or another type of financial institution or report personally using a mobile money service in the past 12 months (richest 60%, share of population ages 15+).; ; Demirguc-Kunt et al., 2018, Global Financial Inclusion Database, World Bank.; Weighted average; Each economy is classified based on the classification of World Bank Group's fiscal year 2018 (July 1, 2017-June 30, 2018).

Panama PA: Bank Account Ownership at a Financial Institution or with a Mobile-Money-Service Provider, Richest 60%: % of Population Aged 15+ data was reported at 55.556 % in 2017. This records an increase from the previous number of 51.512 % for 2014. Panama PA: Bank Account Ownership at a Financial Institution or with a Mobile-Money-Service Provider, Richest 60%: % of Population Aged 15+ data is updated yearly, averaging 51.512 % from Dec 2011 (Median) to 2017, with 3 observations. The data reached an all-time high of 55.556 % in 2017 and a record low of 29.517 % in 2011. Panama PA: Bank Account Ownership at a Financial Institution or with a Mobile-Money-Service Provider, Richest 60%: % of Population Aged 15+ data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Panama – Table PA.World Bank.WDI: Bank Account Ownership. Account denotes the percentage of respondents who report having an account (by themselves or together with someone else) at a bank or another type of financial institution or report personally using a mobile money service in the past 12 months (richest 60%, share of population ages 15+).; ; Demirguc-Kunt et al., 2018, Global Financial Inclusion Database, World Bank.; Weighted average; Each economy is classified based on the classification of World Bank Group's fiscal year 2018 (July 1, 2017-June 30, 2018).

Laos LA: Bank Account Ownership at a Financial Institution or with a Mobile-Money-Service Provider, Richest 60%: % of Population Aged 15+ data was reported at 36.793 % in 2017. This records an increase from the previous number of 30.833 % for 2011. Laos LA: Bank Account Ownership at a Financial Institution or with a Mobile-Money-Service Provider, Richest 60%: % of Population Aged 15+ data is updated yearly, averaging 33.813 % from Dec 2011 (Median) to 2017, with 2 observations. The data reached an all-time high of 36.793 % in 2017 and a record low of 30.833 % in 2011. Laos LA: Bank Account Ownership at a Financial Institution or with a Mobile-Money-Service Provider, Richest 60%: % of Population Aged 15+ data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Laos – Table LA.World Bank.WDI: Bank Account Ownership. Account denotes the percentage of respondents who report having an account (by themselves or together with someone else) at a bank or another type of financial institution or report personally using a mobile money service in the past 12 months (richest 60%, share of population ages 15+).; ; Demirguc-Kunt et al., 2018, Global Financial Inclusion Database, World Bank.; Weighted average; Each economy is classified based on the classification of World Bank Group's fiscal year 2018 (July 1, 2017-June 30, 2018).

Germany DE: Account at a Financial Institution: Income: Richest 60%: % Aged 15+ data was reported at 99.878 % in 2014. This records an increase from the previous number of 95.367 % for 2011. Germany DE: Account at a Financial Institution: Income: Richest 60%: % Aged 15+ data is updated yearly, averaging 97.622 % from Dec 2011 (Median) to 2014, with 2 observations. The data reached an all-time high of 99.878 % in 2014 and a record low of 95.367 % in 2011. Germany DE: Account at a Financial Institution: Income: Richest 60%: % Aged 15+ data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Germany – Table DE.World Bank.WDI: Banking Indicators. Account at a financial institution denotes the percentage of respondents who report having an account (by themselves or together with someone else) at a bank or another type of financial institution.; ; Demirguc-Kunt et al., 2015, Global Financial Inclusion Database, World Bank.; Weighted average;

Chad TD: Account: Income: Richest 60%: % Aged 15+ data was reported at 15.185 % in 2014. This records an increase from the previous number of 10.492 % for 2011. Chad TD: Account: Income: Richest 60%: % Aged 15+ data is updated yearly, averaging 12.839 % from Dec 2011 (Median) to 2014, with 2 observations. The data reached an all-time high of 15.185 % in 2014 and a record low of 10.492 % in 2011. Chad TD: Account: Income: Richest 60%: % Aged 15+ data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Chad – Table TD.World Bank.WDI: Banking Indicators. Denotes the percentage of respondents who report having an account (by themselves or together with someone else). For 2011, this can be an account at a bank or another type of financial institution, and for 2014 this can be a mobile account as well (see year-specific definitions for details) (income, richest 60%, % age 15+). [ts: data are available for multiple waves].; ; Demirguc-Kunt et al., 2015, Global Financial Inclusion Database, World Bank.; Weighted average;

Chad TD: Mobile Account: Income: Richest 60%: % Aged 15+ data was reported at 6.922 % in 2014. Chad TD: Mobile Account: Income: Richest 60%: % Aged 15+ data is updated yearly, averaging 6.922 % from Dec 2014 (Median) to 2014, with 1 observations. The data reached an all-time high of 6.922 % in 2014 and a record low of 6.922 % in 2014. Chad TD: Mobile Account: Income: Richest 60%: % Aged 15+ data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Chad – Table TD.World Bank.WDI: Banking Indicators. Mobile account denotes the percentage of respondents who report personally using a mobile phone to pay bills or to send or receive money through a GSM Association (GSMA) Mobile Money for the Unbanked (MMU) service in the past 12 months; or receiving wages, government transfers, or payments for agricultural products through a mobile phone in the past 12 months.; ; Demirguc-Kunt et al., 2015, Global Financial Inclusion Database, World Bank.; Weighted average;

Brazil BR: Mobile Account: Income: Richest 60%: % Aged 15+ data was reported at 0.894 % in 2014. Brazil BR: Mobile Account: Income: Richest 60%: % Aged 15+ data is updated yearly, averaging 0.894 % from Dec 2014 (Median) to 2014, with 1 observations. The data reached an all-time high of 0.894 % in 2014 and a record low of 0.894 % in 2014. Brazil BR: Mobile Account: Income: Richest 60%: % Aged 15+ data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Brazil – Table BR.World Bank.WDI: Banking Indicators. Mobile account denotes the percentage of respondents who report personally using a mobile phone to pay bills or to send or receive money through a GSM Association (GSMA) Mobile Money for the Unbanked (MMU) service in the past 12 months; or receiving wages, government transfers, or payments for agricultural products through a mobile phone in the past 12 months.; ; Demirguc-Kunt et al., 2015, Global Financial Inclusion Database, World Bank.; Weighted average;

Spain ES: Bank Account Ownership at a Financial Institution or with a Mobile-Money-Service Provider, Richest 60%: % of Population Aged 15+ data was reported at 94.144 % in 2017. This records a decrease from the previous number of 98.196 % for 2014. Spain ES: Bank Account Ownership at a Financial Institution or with a Mobile-Money-Service Provider, Richest 60%: % of Population Aged 15+ data is updated yearly, averaging 94.205 % from Dec 2011 (Median) to 2017, with 3 observations. The data reached an all-time high of 98.196 % in 2014 and a record low of 94.144 % in 2017. Spain ES: Bank Account Ownership at a Financial Institution or with a Mobile-Money-Service Provider, Richest 60%: % of Population Aged 15+ data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Spain – Table ES.World Bank.WDI: Bank Account Ownership. Account denotes the percentage of respondents who report having an account (by themselves or together with someone else) at a bank or another type of financial institution or report personally using a mobile money service in the past 12 months (richest 60%, share of population ages 15+).; ; Demirguc-Kunt et al., 2018, Global Financial Inclusion Database, World Bank.; Weighted average; Each economy is classified based on the classification of World Bank Group's fiscal year 2018 (July 1, 2017-June 30, 2018).

Ukraine UA: Bank Account Ownership at a Financial Institution or with a Mobile-Money-Service Provider, Richest 60%: % of Population Aged 15+ data was reported at 69.313 % in 2017. This records an increase from the previous number of 58.681 % for 2014. Ukraine UA: Bank Account Ownership at a Financial Institution or with a Mobile-Money-Service Provider, Richest 60%: % of Population Aged 15+ data is updated yearly, averaging 58.681 % from Dec 2011 (Median) to 2017, with 3 observations. The data reached an all-time high of 69.313 % in 2017 and a record low of 48.576 % in 2011. Ukraine UA: Bank Account Ownership at a Financial Institution or with a Mobile-Money-Service Provider, Richest 60%: % of Population Aged 15+ data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Ukraine – Table UA.World Bank.WDI: Bank Account Ownership. Account denotes the percentage of respondents who report having an account (by themselves or together with someone else) at a bank or another type of financial institution or report personally using a mobile money service in the past 12 months (richest 60%, share of population ages 15+).; ; Demirguc-Kunt et al., 2018, Global Financial Inclusion Database, World Bank.; Weighted average; Each economy is classified based on the classification of World Bank Group's fiscal year 2018 (July 1, 2017-June 30, 2018).

Luxembourg LU: Bank Account Ownership at a Financial Institution or with a Mobile-Money-Service Provider, Richest 60%: % of Population Aged 15+ data was reported at 99.065 % in 2017. This records an increase from the previous number of 96.870 % for 2014. Luxembourg LU: Bank Account Ownership at a Financial Institution or with a Mobile-Money-Service Provider, Richest 60%: % of Population Aged 15+ data is updated yearly, averaging 96.870 % from Dec 2011 (Median) to 2017, with 3 observations. The data reached an all-time high of 99.065 % in 2017 and a record low of 96.275 % in 2011. Luxembourg LU: Bank Account Ownership at a Financial Institution or with a Mobile-Money-Service Provider, Richest 60%: % of Population Aged 15+ data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Luxembourg – Table LU.World Bank.WDI: Bank Account Ownership. Account denotes the percentage of respondents who report having an account (by themselves or together with someone else) at a bank or another type of financial institution or report personally using a mobile money service in the past 12 months (richest 60%, share of population ages 15+).; ; Demirguc-Kunt et al., 2018, Global Financial Inclusion Database, World Bank.; Weighted average; Each economy is classified based on the classification of World Bank Group's fiscal year 2018 (July 1, 2017-June 30, 2018).

Malta MT: Bank Account Ownership at a Financial Institution or with a Mobile-Money-Service Provider, Richest 60%: % of Population Aged 15+ data was reported at 99.153 % in 2017. This records an increase from the previous number of 97.544 % for 2014. Malta MT: Bank Account Ownership at a Financial Institution or with a Mobile-Money-Service Provider, Richest 60%: % of Population Aged 15+ data is updated yearly, averaging 97.544 % from Dec 2011 (Median) to 2017, with 3 observations. The data reached an all-time high of 99.153 % in 2017 and a record low of 95.543 % in 2011. Malta MT: Bank Account Ownership at a Financial Institution or with a Mobile-Money-Service Provider, Richest 60%: % of Population Aged 15+ data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Malta – Table MT.World Bank: Bank Account Ownership. Account denotes the percentage of respondents who report having an account (by themselves or together with someone else) at a bank or another type of financial institution or report personally using a mobile money service in the past 12 months (richest 60%, share of population ages 15+).; ; Demirguc-Kunt et al., 2018, Global Financial Inclusion Database, World Bank.; Weighted Average; Each economy is classified based on the classification of World Bank Group's fiscal year 2018 (July 1, 2017-June 30, 2018).

Brazil BR: Account at a Financial Institution: Income: Richest 60%: % Aged 15+ data was reported at 74.624 % in 2014. This records an increase from the previous number of 67.101 % for 2011. Brazil BR: Account at a Financial Institution: Income: Richest 60%: % Aged 15+ data is updated yearly, averaging 70.863 % from Dec 2011 (Median) to 2014, with 2 observations. The data reached an all-time high of 74.624 % in 2014 and a record low of 67.101 % in 2011. Brazil BR: Account at a Financial Institution: Income: Richest 60%: % Aged 15+ data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Brazil – Table BR.World Bank.WDI: Banking Indicators. Account at a financial institution denotes the percentage of respondents who report having an account (by themselves or together with someone else) at a bank or another type of financial institution.; ; Demirguc-Kunt et al., 2015, Global Financial Inclusion Database, World Bank.; Weighted average;

El Salvador SV: Mobile Account: Income: Richest 60%: % Aged 15+ data was reported at 4.879 % in 2014. El Salvador SV: Mobile Account: Income: Richest 60%: % Aged 15+ data is updated yearly, averaging 4.879 % from Dec 2014 (Median) to 2014, with 1 observations. El Salvador SV: Mobile Account: Income: Richest 60%: % Aged 15+ data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s El Salvador – Table SV.World Bank.WDI: Banking Indicators. Mobile account denotes the percentage of respondents who report personally using a mobile phone to pay bills or to send or receive money through a GSM Association (GSMA) Mobile Money for the Unbanked (MMU) service in the past 12 months; or receiving wages, government transfers, or payments for agricultural products through a mobile phone in the past 12 months.; ; Demirguc-Kunt et al., 2015, Global Financial Inclusion Database, World Bank.; Weighted average;