The United States topped the list in 2018 for the country with the highest gap between CEO and worker pay. In that year, for every U.S. dollar an average worker received, the average CEO earned 265 U.S. dollars. India, the United Kingdom, South Africa, and the Netherlands rounded out the top five for countries with the highest CEO to worker pay.
The 99 percent
It is a well-known issue that wages for average workers in the United States have been stagnating. Average hourly earnings for American employees, which have been hovering just below 11 U.S. dollars, have not gone up by much over the past year. The federal minimum wage in the United States has been 2.13 U.S. dollars for tipped workers and 7.25 U.S. dollars for non-tipped workers since 2009 and would be much higher today if minimum wage was adjusted for inflation.
The one percent
The gap between normal workers and CEOs is particularly high in the U.S. The richest CEO in 2018 was Elon Musk, with an annual compensation of about 2.84 billion U.S. dollars. America is also home to the world’s richest man, Jeff Bezos, who is the head of Amazon.com.
North America and the Middle East had the highest wages for customer support workers worldwide in 2018, with a median wage of ****** U.S. dollars according to a 2018 survey of employees in customer support roles. The region with the lowest wages was Asia, with ****** U.S. dollars.
This statistic shows the average salary of IT professionals worldwide in 2018, by industry. IT jobs in the aerospace/defense industry have the highest average salary, making about ***** thousand U.S. dollars per year in 2018.
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Latvia Average Wages and Salaries: Gross: AR: Gambling and Betting Activities data was reported at 1,184.340 EUR in Jun 2018. This records an increase from the previous number of 1,032.700 EUR for May 2018. Latvia Average Wages and Salaries: Gross: AR: Gambling and Betting Activities data is updated monthly, averaging 759.345 EUR from Jan 2008 (Median) to Jun 2018, with 126 observations. The data reached an all-time high of 1,184.340 EUR in Jun 2018 and a record low of 558.460 EUR in Feb 2010. Latvia Average Wages and Salaries: Gross: AR: Gambling and Betting Activities data remains active status in CEIC and is reported by Central Statistical Bureau of Latvia. The data is categorized under Global Database’s Latvia – Table LV.G018: Average Wages and Salaries: Statistical Classification of Economic Activities Revision 2.
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Indonesia Monthly Average Wage: Female data was reported at 2,178,134.000 IDR in 2018. This records an increase from the previous number of 2,070,274.000 IDR for 2017. Indonesia Monthly Average Wage: Female data is updated yearly, averaging 720,632.000 IDR from Aug 1994 (Median) to 2018, with 24 observations. The data reached an all-time high of 2,178,134.000 IDR in 2018 and a record low of 113,497.000 IDR in 1994. Indonesia Monthly Average Wage: Female data remains active status in CEIC and is reported by Central Bureau of Statistics. The data is categorized under Global Database’s Indonesia – Table ID.GBB002: Monthly Average Wage: by Industry.
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Wages in China increased to 120698 CNY/Year in 2023 from 114029 CNY/Year in 2022. This dataset provides - China Average Yearly Wages - actual values, historical data, forecast, chart, statistics, economic calendar and news.
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Indonesia Monthly Average Wage: Information and Communication data was reported at 4,049,057.000 IDR in 2018. This records a decrease from the previous number of 4,197,907.000 IDR for 2017. Indonesia Monthly Average Wage: Information and Communication data is updated yearly, averaging 3,953,221.000 IDR from Aug 2015 (Median) to 2018, with 4 observations. The data reached an all-time high of 4,197,907.000 IDR in 2017 and a record low of 3,272,083.000 IDR in 2015. Indonesia Monthly Average Wage: Information and Communication data remains active status in CEIC and is reported by Central Bureau of Statistics. The data is categorized under Global Database’s Indonesia – Table ID.GBB002: Monthly Average Wage: by Industry.
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Graph and download economic data for Average Hourly Earnings of All Employees, Total Private (CES0500000003) from Mar 2006 to Jun 2025 about earnings, average, establishment survey, hours, wages, private, employment, and USA.
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Context
The dataset presents the distribution of median household income among distinct age brackets of householders in Country Life Acres. Based on the latest 2018-2022 5-Year Estimates from the American Community Survey, it displays how income varies among householders of different ages in Country Life Acres. It showcases how household incomes typically rise as the head of the household gets older. The dataset can be utilized to gain insights into age-based household income trends and explore the variations in incomes across households.
Key observations: Insights from 2022
In terms of income distribution across age cohorts, in Country Life Acres, where there exist only two delineated age groups, the median household income is $260,314 for householders within the 45 to 64 years age group, compared to $210,853 for the 65 years and over age group.
When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2018-2022 5-Year Estimates. All incomes have been adjusting for inflation and are presented in 2023-inflation-adjusted dollars.
Age groups classifications include:
Variables / Data Columns
Good to know
Margin of Error
Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.
Custom data
If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.
Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.
This dataset is a part of the main dataset for Country Life Acres median household income by age. You can refer the same here
This statistic presents the average annual salary of BNP Paribas employees between 2013 and 2018, by country. In 2018, the average annual salary of an employee working for BNP Paribas in France amounted ****** euros.
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Context
The dataset presents the distribution of median household income among distinct age brackets of householders in Country Club Hills. Based on the latest 2018-2022 5-Year Estimates from the American Community Survey, it displays how income varies among householders of different ages in Country Club Hills. It showcases how household incomes typically rise as the head of the household gets older. The dataset can be utilized to gain insights into age-based household income trends and explore the variations in incomes across households.
Key observations: Insights from 2022
In terms of income distribution across age cohorts, in Country Club Hills, the median household income stands at $94,474 for householders within the 45 to 64 years age group, followed by $74,106 for the 65 years and over age group. Notably, householders within the 25 to 44 years age group, had the lowest median household income at $64,679.
When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2018-2022 5-Year Estimates. All incomes have been adjusting for inflation and are presented in 2023-inflation-adjusted dollars.
Age groups classifications include:
Variables / Data Columns
Good to know
Margin of Error
Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.
Custom data
If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.
Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.
This dataset is a part of the main dataset for Country Club Hills median household income by age. You can refer the same here
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Context
The dataset presents the distribution of median household income among distinct age brackets of householders in Country Club. Based on the latest 2018-2022 5-Year Estimates from the American Community Survey, it displays how income varies among householders of different ages in Country Club. It showcases how household incomes typically rise as the head of the household gets older. The dataset can be utilized to gain insights into age-based household income trends and explore the variations in incomes across households.
Key observations: Insights from 2022
In terms of income distribution across age cohorts, in Country Club, householders within the 25 to 44 years age group have the highest median household income at $98,485, followed by those in the 45 to 64 years age group with an income of $89,007. Meanwhile householders within the under 25 years age group report the second lowest median household income of $64,558. Notably, householders within the 65 years and over age group, had the lowest median household income at $56,379.
When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2018-2022 5-Year Estimates. All incomes have been adjusting for inflation and are presented in 2023-inflation-adjusted dollars.
Age groups classifications include:
Variables / Data Columns
Good to know
Margin of Error
Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.
Custom data
If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.
Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.
This dataset is a part of the main dataset for Country Club median household income by age. You can refer the same here
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Malta Gross Annual Average Salary: Women data was reported at 16,481.343 EUR in Jun 2018. This records a decrease from the previous number of 16,743.206 EUR for Mar 2018. Malta Gross Annual Average Salary: Women data is updated quarterly, averaging 12,507.183 EUR from Dec 2000 (Median) to Jun 2018, with 71 observations. The data reached an all-time high of 16,743.206 EUR in Mar 2018 and a record low of 8,919.610 EUR in Dec 2000. Malta Gross Annual Average Salary: Women data remains active status in CEIC and is reported by National Statistics Office - Malta. The data is categorized under Global Database’s Malta – Table MT.G007: Gross Annual Average Salary.
Goal 8Promote sustained, inclusive and sustainable economic growth, full and productive employment and decent work for allTarget 8.1: Sustain per capita economic growth in accordance with national circumstances and, in particular, at least 7 per cent gross domestic product growth per annum in the least developed countriesIndicator 8.1.1: Annual growth rate of real GDP per capitaNY_GDP_PCAP: Annual growth rate of real GDP per capita (%)Target 8.2: Achieve higher levels of economic productivity through diversification, technological upgrading and innovation, including through a focus on high-value added and labour-intensive sectorsIndicator 8.2.1: Annual growth rate of real GDP per employed personSL_EMP_PCAP: Annual growth rate of real GDP per employed person (%)Target 8.3: Promote development-oriented policies that support productive activities, decent job creation, entrepreneurship, creativity and innovation, and encourage the formalization and growth of micro-, small- and medium-sized enterprises, including through access to financial servicesIndicator 8.3.1: Proportion of informal employment in total employment, by sector and sexSL_ISV_IFEM: Proportion of informal employment, by sector and sex (ILO harmonized estimates) (%)Target 8.4: Improve progressively, through 2030, global resource efficiency in consumption and production and endeavour to decouple economic growth from environmental degradation, in accordance with the 10-Year Framework of Programmes on Sustainable Consumption and Production, with developed countries taking the leadIndicator 8.4.1: Material footprint, material footprint per capita, and material footprint per GDPEN_MAT_FTPRPG: Material footprint per unit of GDP, by type of raw material (kilograms per constant 2010 United States dollar)EN_MAT_FTPRPC: Material footprint per capita, by type of raw material (tonnes)EN_MAT_FTPRTN: Material footprint, by type of raw material (tonnes)Indicator 8.4.2: Domestic material consumption, domestic material consumption per capita, and domestic material consumption per GDPEN_MAT_DOMCMPT: Domestic material consumption, by type of raw material (tonnes)EN_MAT_DOMCMPG: Domestic material consumption per unit of GDP, by type of raw material (kilograms per constant 2010 United States dollars)EN_MAT_DOMCMPC: Domestic material consumption per capita, by type of raw material (tonnes)Target 8.5: By 2030, achieve full and productive employment and decent work for all women and men, including for young people and persons with disabilities, and equal pay for work of equal valueIndicator 8.5.1: Average hourly earnings of employees, by sex, age, occupation and persons with disabilitiesSL_EMP_EARN: Average hourly earnings of employees by sex and occupation (local currency)Indicator 8.5.2: Unemployment rate, by sex, age and persons with disabilitiesSL_TLF_UEM: Unemployment rate, by sex and age (%)SL_TLF_UEMDIS: Unemployment rate, by sex and disability (%)Target 8.6: By 2020, substantially reduce the proportion of youth not in employment, education or trainingIndicator 8.6.1: Proportion of youth (aged 15–24 years) not in education, employment or trainingSL_TLF_NEET: Proportion of youth not in education, employment or training, by sex and age (%)Target 8.7: Take immediate and effective measures to eradicate forced labour, end modern slavery and human trafficking and secure the prohibition and elimination of the worst forms of child labour, including recruitment and use of child soldiers, and by 2025 end child labour in all its formsIndicator 8.7.1: Proportion and number of children aged 5–17 years engaged in child labour, by sex and ageSL_TLF_CHLDEC: Proportion of children engaged in economic activity and household chores, by sex and age (%)SL_TLF_CHLDEA: Proportion of children engaged in economic activity, by sex and age (%)Target 8.8: Protect labour rights and promote safe and secure working environments for all workers, including migrant workers, in particular women migrants, and those in precarious employmentIndicator 8.8.1: Fatal and non-fatal occupational injuries per 100,000 workers, by sex and migrant statusSL_EMP_FTLINJUR: Fatal occupational injuries among employees, by sex and migrant status (per 100,000 employees)SL_EMP_INJUR: Non-fatal occupational injuries among employees, by sex and migrant status (per 100,000 employees)Indicator 8.8.2: Level of national compliance with labour rights (freedom of association and collective bargaining) based on International Labour Organization (ILO) textual sources and national legislation, by sex and migrant statusSL_LBR_NTLCPL: Level of national compliance with labour rights (freedom of association and collective bargaining) based on International Labour Organization (ILO) textual sources and national legislationTarget 8.9: By 2030, devise and implement policies to promote sustainable tourism that creates jobs and promotes local culture and productsIndicator 8.9.1: Tourism direct GDP as a proportion of total GDP and in growth rateST_GDP_ZS: Tourism direct GDP as a proportion of total GDP (%)Target 8.10: Strengthen the capacity of domestic financial institutions to encourage and expand access to banking, insurance and financial services for allIndicator 8.10.1: (a) Number of commercial bank branches per 100,000 adults and (b) number of automated teller machines (ATMs) per 100,000 adultsFB_ATM_TOTL: Number of automated teller machines (ATMs) per 100,000 adultsFB_CBK_BRCH: Number of commercial bank branches per 100,000 adultsIndicator 8.10.2: Proportion of adults (15 years and older) with an account at a bank or other financial institution or with a mobile-money-service providerFB_BNK_ACCSS: Proportion of adults (15 years and older) with an account at a financial institution or mobile-money-service provider, by sex (% of adults aged 15 years and older)Target 8.a: Increase Aid for Trade support for developing countries, in particular least developed countries, including through the Enhanced Integrated Framework for Trade-related Technical Assistance to Least Developed CountriesIndicator 8.a.1: Aid for Trade commitments and disbursementsDC_TOF_TRDCMDL: Total official flows (commitments) for Aid for Trade, by donor countries (millions of constant 2018 United States dollars)DC_TOF_TRDDBMDL: Total official flows (disbursement) for Aid for Trade, by donor countries (millions of constant 2018 United States dollars)DC_TOF_TRDDBML: Total official flows (disbursement) for Aid for Trade, by recipient countries (millions of constant 2018 United States dollars)DC_TOF_TRDCML: Total official flows (commitments) for Aid for Trade, by recipient countries (millions of constant 2018 United States dollars)Target 8.b: By 2020, develop and operationalize a global strategy for youth employment and implement the Global Jobs Pact of the International Labour OrganizationIndicator 8.b.1: Existence of a developed and operationalized national strategy for youth employment, as a distinct strategy or as part of a national employment strategySL_CPA_YEMP: Existence of a developed and operationalized national strategy for youth employment, as a distinct strategy or as part of a national employment strategy
The median wage for customer support workers worldwide rose slightly in 2018 to ****** U.S. dollars, according to a 2018 survey of employees in customer support roles. However, being a worldwide survey, this is not limited just to North America and Europe, where salaries tend to be higher.
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Sierra Leone SL: Survey Mean Consumption or Income per Capita: Total Population: Annualized Average Growth Rate data was reported at 2.860 % in 2018. Sierra Leone SL: Survey Mean Consumption or Income per Capita: Total Population: Annualized Average Growth Rate data is updated yearly, averaging 2.860 % from Dec 2018 (Median) to 2018, with 1 observations. Sierra Leone SL: Survey Mean Consumption or Income per Capita: Total Population: Annualized Average Growth Rate data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Sierra Leone – Table SL.World Bank.WDI: Poverty. The growth rate in the welfare aggregate of the total population is computed as the annualized average growth rate in per capita real consumption or income of the total population in the income distribution in a country from household surveys over a roughly 5-year period. Mean per capita real consumption or income is measured at 2011 Purchasing Power Parity (PPP) using the PovcalNet (http://iresearch.worldbank.org/PovcalNet). For some countries means are not reported due to grouped and/or confidential data. The annualized growth rate is computed as (Mean in final year/Mean in initial year)^(1/(Final year - Initial year)) - 1. The reference year is the year in which the underlying household survey data was collected. In cases for which the data collection period bridged two calendar years, the first year in which data were collected is reported. The initial year refers to the nearest survey collected 5 years before the most recent survey available, only surveys collected between 3 and 7 years before the most recent survey are considered. The final year refers to the most recent survey available between 2011 and 2015. Growth rates for Iraq are based on survey means of 2005 PPP$. The coverage and quality of the 2011 PPP price data for Iraq and most other North African and Middle Eastern countries were hindered by the exceptional period of instability they faced at the time of the 2011 exercise of the International Comparison Program. See PovcalNet for detailed explanations.; ; World Bank, Global Database of Shared Prosperity (GDSP) circa 2011-2016 (http://www.worldbank.org/en/topic/poverty/brief/global-database-of-shared-prosperity).; ; The comparability of welfare aggregates (consumption or income) for the chosen years T0 and T1 is assessed for every country. If comparability across the two surveys is a major concern for a country, the selection criteria are re-applied to select the next best survey year(s). Annualized growth rates are calculated between the survey years, using a compound growth formula. The survey years defining the period for which growth rates are calculated and the type of welfare aggregate used to calculate the growth rates are noted in the footnotes.
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Context
The dataset presents the distribution of median household income among distinct age brackets of householders in Hill Country Village. Based on the latest 2018-2022 5-Year Estimates from the American Community Survey, it displays how income varies among householders of different ages in Hill Country Village. It showcases how household incomes typically rise as the head of the household gets older. The dataset can be utilized to gain insights into age-based household income trends and explore the variations in incomes across households.
Key observations: Insights from 2022
In terms of income distribution across age cohorts, in Hill Country Village, the median household income stands at $260,314 for householders within the 25 to 44 years age group, followed by $260,314 for the 45 to 64 years age group. Notably, householders within the 65 years and over age group, had the lowest median household income at $168,553.
When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2018-2022 5-Year Estimates. All incomes have been adjusting for inflation and are presented in 2023-inflation-adjusted dollars.
Age groups classifications include:
Variables / Data Columns
Good to know
Margin of Error
Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.
Custom data
If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.
Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.
This dataset is a part of the main dataset for Hill Country Village median household income by age. You can refer the same here
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
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Context
The dataset presents the median household incomes over the past decade across various racial categories identified by the U.S. Census Bureau in Town And Country. It portrays the median household income of the head of household across racial categories (excluding ethnicity) as identified by the Census Bureau. It also showcases the annual income trends, between 2013 and 2023, providing insights into the economic shifts within diverse racial communities.The dataset can be utilized to gain insights into income disparities and variations across racial categories, aiding in data analysis and decision-making..
Key observations
When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.
Racial categories include:
Variables / Data Columns
Good to know
Margin of Error
Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.
Custom data
If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.
Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.
This dataset is a part of the main dataset for Town And Country median household income by race. You can refer the same here
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License information was derived automatically
Malta Gross Annual Average Salary: Men data was reported at 20,850.245 EUR in Jun 2018. This records an increase from the previous number of 20,076.519 EUR for Mar 2018. Malta Gross Annual Average Salary: Men data is updated quarterly, averaging 14,658.118 EUR from Dec 2000 (Median) to Jun 2018, with 71 observations. The data reached an all-time high of 20,850.245 EUR in Jun 2018 and a record low of 11,452.550 EUR in Dec 2000. Malta Gross Annual Average Salary: Men data remains active status in CEIC and is reported by National Statistics Office - Malta. The data is categorized under Global Database’s Malta – Table MT.G007: Gross Annual Average Salary.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Context
The dataset presents the distribution of median household income among distinct age brackets of householders in Brazos Country. Based on the latest 2018-2022 5-Year Estimates from the American Community Survey, it displays how income varies among householders of different ages in Brazos Country. It showcases how household incomes typically rise as the head of the household gets older. The dataset can be utilized to gain insights into age-based household income trends and explore the variations in incomes across households.
Key observations: Insights from 2022
In terms of income distribution across age cohorts, in Brazos Country, the median household income stands at $213,056 for householders within the 45 to 64 years age group, followed by $172,241 for the 25 to 44 years age group. Notably, householders within the 65 years and over age group, had the lowest median household income at $97,401.
When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2018-2022 5-Year Estimates. All incomes have been adjusting for inflation and are presented in 2023-inflation-adjusted dollars.
Age groups classifications include:
Variables / Data Columns
Good to know
Margin of Error
Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.
Custom data
If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.
Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.
This dataset is a part of the main dataset for Brazos Country median household income by age. You can refer the same here
The United States topped the list in 2018 for the country with the highest gap between CEO and worker pay. In that year, for every U.S. dollar an average worker received, the average CEO earned 265 U.S. dollars. India, the United Kingdom, South Africa, and the Netherlands rounded out the top five for countries with the highest CEO to worker pay.
The 99 percent
It is a well-known issue that wages for average workers in the United States have been stagnating. Average hourly earnings for American employees, which have been hovering just below 11 U.S. dollars, have not gone up by much over the past year. The federal minimum wage in the United States has been 2.13 U.S. dollars for tipped workers and 7.25 U.S. dollars for non-tipped workers since 2009 and would be much higher today if minimum wage was adjusted for inflation.
The one percent
The gap between normal workers and CEOs is particularly high in the U.S. The richest CEO in 2018 was Elon Musk, with an annual compensation of about 2.84 billion U.S. dollars. America is also home to the world’s richest man, Jeff Bezos, who is the head of Amazon.com.