After-tax income decomposed according to each component of the disposable income for the Market Basket Measure (MBM) (realized part of the adjusted MBM threshold, surplus or deficit and all adjustments such as non-discretionary expenses and income adjustments), by after-tax income decile, Canada and provinces, annual.

Udalmap is a municipal Information System, whose purpose is to show in detail the reality in the municipalities of the Basque Country. It allows, in turn, the design and evaluation of public policies, aimed at facilitating decision-making in multiple areas related to the growth and development of the territory, in the interest of a greater degree of territorial, economic, social cohesion and environmental respect.

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.

Analysis of ‘Municipal sustainability indicators: Average annual cumulative growth rate of total personal income in the last period (%)’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from http://data.europa.eu/88u/dataset/https-opendata-euskadi-eus-catalogo-indicadores-municipales-de-sostenibilidad-tasa-media-de-crecimiento-acumulativo-anual-de-la-renta-personal-total-en-el-ultimo-periodo- on 18 January 2022.

--- Dataset description provided by original source is as follows ---

Udalmap is a municipal information system, whose purpose is to show in detail the reality in the municipalities of the Basque Country. It allows, in turn, the design and evaluation of public policies aimed at facilitating decision-making in multiple areas related to the growth and development of the territory, with a view to a greater degree of territorial, economic, social and environmental cohesion.

--- Original source retains full ownership of the source dataset ---

Number of employees, average hourly and weekly earnings (including overtime), and average weekly hours for the industrial aggregate excluding unclassified businesses, last 5 months.

Table from the American Community Survey (ACS) 5-year series on income and earning related topics for City of Seattle Council Districts, Comprehensive Plan Growth Areas and Community Reporting Areas. Table includes B19025 Aggregate Household Income, B19013 Median Household Income, B19001 Household Income, B19113 Median Family Household Income, B19101 Family Household Income, B19202 Median Nonfamily Household Income, B19201 Nonfamily Household Income, B19301 Per Capita Income/B19313 Aggregate Income/B01001 Sex by Age, C24010 Sex by Occupation of the Civilian Employed Population 16 years and Over, B20017 Median Earnings by Sex by Work Experience for the Population 16 years and over with Earnings, B20001 Sex by Earnings for the Population 16 years and over with Earnings. Data is pulled from block group tables for the most recent ACS vintage and summarized to the neighborhoods based on block group assignment.

2016-2020 ACS 5-Year estimates of socioeconomic characteristics compiled by the 2010 US Decennial Census Tracts. These characteristics include Aggregate Travel Time To Work Of Workers By Sex, Travel Time To Work, Poverty Status In The Past 12 Months Of Families By Household Type By Tenure, Poverty Status Of Individuals In The Past 12 Months By Living Arrangement, Household Income In The Past 12 Months, Median Household Income In The Past 12 Months, Aggregate Household Income In The Past 12 Months, Median Family Income In The Past 12 Months, Median Non-family Household Income In The Past 12 Months, Sex By Age By Employment Status For The Population 16 Years And Over, Tenure By Occupants Per Room, Total Population in Occupied Housing Units by Tenure by year Householder Moved into Unit, Tenure By Housing Costs As A Percentage Of Household Income In The Past 12 Months, Sex By Occupation For The Civilian Employed Population 16 Years And Over, Median Earnings In the Past 12 Months (In 2015 Inflation-Adjusted Dollars) by Sex by Educational Attainment for the Population 25 Years and Over, Educational Attainment by Employment Status for the Population 25 to 64 Years, and Occupation By Median Earnings In The Past 12 Months (In 2015 Inflation-Adjusted Dollars) For The Full-Time, Year-Round Civilian Employed Population 16 Years And Over.

2016-2020 ACS 5-Year estimates of socioeconomic characteristics compiled at the state level. These characteristics include Aggregate Travel Time To Work Of Workers By Sex, Travel Time To Work, Poverty Status In The Past 12 Months Of Families By Household Type By Tenure, Poverty Status Of Individuals In The Past 12 Months By Living Arrangement, Household Income In The Past 12 Months, Median Household Income In The Past 12 Months, Aggregate Household Income In The Past 12 Months, Median Family Income In The Past 12 Months, Median Non-family Household Income In The Past 12 Months, Sex By Age By Employment Status For The Population 16 Years And Over, Tenure By Occupants Per Room, Total Population in Occupied Housing Units by Tenure by year Householder Moved into Unit, Tenure By Housing Costs As A Percentage Of Household Income In The Past 12 Months, Sex By Occupation For The Civilian Employed Population 16 Years And Over, Median Earnings In the Past 12 Months (In 2015 Inflation-Adjusted Dollars) by Sex by Educational Attainment for the Population 25 Years and Over, Educational Attainment by Employment Status for the Population 25 to 64 Years, and Occupation By Median Earnings In The Past 12 Months (In 2015 Inflation-Adjusted Dollars) For The Full-Time, Year-Round Civilian Employed Population 16 Years And Over.

2016-2020 ACS 5-Year estimates of socioeconomic characteristics compiled at the County level. These characteristics include Aggregate Travel Time To Work Of Workers By Sex, Travel Time To Work, Poverty Status In The Past 12 Months Of Families By Household Type By Tenure, Poverty Status Of Individuals In The Past 12 Months By Living Arrangement, Household Income In The Past 12 Months, Median Household Income In The Past 12 Months, Aggregate Household Income In The Past 12 Months, Median Family Income In The Past 12 Months, Median Non-family Household Income In The Past 12 Months, Sex By Age By Employment Status For The Population 16 Years And Over, Tenure By Occupants Per Room, Total Population in Occupied Housing Units by Tenure by year Householder Moved into Unit, Tenure By Housing Costs As A Percentage Of Household Income In The Past 12 Months, Sex By Occupation For The Civilian Employed Population 16 Years And Over, Median Earnings In the Past 12 Months (In 2015 Inflation-Adjusted Dollars) by Sex by Educational Attainment for the Population 25 Years and Over, Educational Attainment by Employment Status for the Population 25 to 64 Years, and Occupation By Median Earnings In The Past 12 Months (In 2015 Inflation-Adjusted Dollars) For The Full-Time, Year-Round Civilian Employed Population 16 Years And Over.

The table shows the average gross earnings of full-time employees by main feature of the post, cumulated on a quarterly basis

Replication dataset for "Effective corporate income taxation and its effect on capital accumulation: Cross-country evidence"

Abstract It is debated to what extent corporate taxation discourages capital formation, and the related empirical cross-country evidence is inconclusive. This paper provides new insights into this matter for a large sample of developed and developing countries. In a first step, national accounts data is used to calculate backward-looking effective corporate income tax rates (ECTR) for 77 countries during 1995–2018. In a second step, dynamic panel data regressions are used to estimate the effect of ECTR on aggregate corporate investment. The main findings of this exercise are that (i) statutory corporate income tax rates (SCTR), on average, are twice as high as ECTR, (ii) average ECTR have been relatively stable but show distinct dynamics across countries, and (iii) no significant negative relationship exists between ECTR and aggregate corporate investment. The latter finding is robust to different specifications and samples and when publicly available SCTR or forward-looking effective tax rate measures are used as alternative tax rate proxies.

The table shows the average net earnings of full-time employees, net of discounts, by main feature of the post, cumulated on a quarterly basis

Although the American Community Survey (ACS) produces population, demographic and housing unit estimates, the decennial census is the official source of population totals for April 1st of each decennial year. In between censuses, the Census Bureau's Population Estimates Program produces and disseminates the official estimates of the population for the nation, states, counties, cities, and towns and estimates of housing units and the group quarters population for states and counties..Information about the American Community Survey (ACS) can be found on the ACS website. Supporting documentation including code lists, subject definitions, data accuracy, and statistical testing, and a full list of ACS tables and table shells (without estimates) can be found on the Technical Documentation section of the ACS website.Sample size and data quality measures (including coverage rates, allocation rates, and response rates) can be found on the American Community Survey website in the Methodology section..Source: U.S. Census Bureau, 2023 American Community Survey 1-Year Estimates.ACS data generally reflect the geographic boundaries of legal and statistical areas as of January 1 of the estimate year. For more information, see Geography Boundaries by Year..Data are based on a sample and are subject to sampling variability. The degree of uncertainty for an estimate arising from sampling variability is represented through the use of a margin of error. The value shown here is the 90 percent margin of error. The margin of error can be interpreted roughly as providing a 90 percent probability that the interval defined by the estimate minus the margin of error and the estimate plus the margin of error (the lower and upper confidence bounds) contains the true value. In addition to sampling variability, the ACS estimates are subject to nonsampling error (for a discussion of nonsampling variability, see ACS Technical Documentation). The effect of nonsampling error is not represented in these tables..Users must consider potential differences in geographic boundaries, questionnaire content or coding, or other methodological issues when comparing ACS data from different years. Statistically significant differences shown in ACS Comparison Profiles, or in data users' own analysis, may be the result of these differences and thus might not necessarily reflect changes to the social, economic, housing, or demographic characteristics being compared. For more information, see Comparing ACS Data..Estimates of urban and rural populations, housing units, and characteristics reflect boundaries of urban areas defined based on 2020 Census data. As a result, data for urban and rural areas from the ACS do not necessarily reflect the results of ongoing urbanization..Explanation of Symbols:- The estimate could not be computed because there were an insufficient number of sample observations. For a ratio of medians estimate, one or both of the median estimates falls in the lowest interval or highest interval of an open-ended distribution. For a 5-year median estimate, the margin of error associated with a median was larger than the median itself.N The estimate or margin of error cannot be displayed because there were an insufficient number of sample cases in the selected geographic area. (X) The estimate or margin of error is not applicable or not available.median- The median falls in the lowest interval of an open-ended distribution (for example "2,500-")median+ The median falls in the highest interval of an open-ended distribution (for example "250,000+").** The margin of error could not be computed because there were an insufficient number of sample observations.*** The margin of error could not be computed because the median falls in the lowest interval or highest interval of an open-ended distribution.***** A margin of error is not appropriate because the corresponding estimate is controlled to an independent population or housing estimate. Effectively, the corresponding estimate has no sampling error and the margin of error may be treated as zero.

Wages in the United States increased 4.72 percent in May of 2025 over the same month in the previous year. This dataset provides the latest reported value for - United States Wages and Salaries Growth - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

Graph and download economic data for Households and Nonprofit Organizations; Net Worth as a Percentage of Disposable Personal Income, Level (HNONWPDPI) from Q4 1946 to Q1 2025 about net worth, disposable, nonprofit organizations, personal income, Net, percent, personal, households, income, and USA.

Although the American Community Survey (ACS) produces population, demographic and housing unit estimates, it is the Census Bureau's Population Estimates Program that produces and disseminates the official estimates of the population for the nation, states, counties, cities, and towns and estimates of housing units for states and counties..Supporting documentation on code lists, subject definitions, data accuracy, and statistical testing can be found on the American Community Survey website in the Technical Documentation section.Sample size and data quality measures (including coverage rates, allocation rates, and response rates) can be found on the American Community Survey website in the Methodology section..Source: U.S. Census Bureau, 2019 American Community Survey 1-Year Estimates.Data are based on a sample and are subject to sampling variability. The degree of uncertainty for an estimate arising from sampling variability is represented through the use of a margin of error. The value shown here is the 90 percent margin of error. The margin of error can be interpreted roughly as providing a 90 percent probability that the interval defined by the estimate minus the margin of error and the estimate plus the margin of error (the lower and upper confidence bounds) contains the true value. In addition to sampling variability, the ACS estimates are subject to nonsampling error (for a discussion of nonsampling variability, see ACS Technical Documentation). The effect of nonsampling error is not represented in these tables..Between 2018 and 2019 the American Community Survey retirement income question changed. These changes resulted in an increase in both the number of households reporting retirement income and higher aggregate retirement income at the national level. For more information see Changes to the Retirement Income Question ..The 2019 American Community Survey (ACS) data generally reflect the September 2018 Office of Management and Budget (OMB) delineations of metropolitan and micropolitan statistical areas. In certain instances the names, codes, and boundaries of the principal cities shown in ACS tables may differ from the OMB delineations due to differences in the effective dates of the geographic entities..Estimates of urban and rural populations, housing units, and characteristics reflect boundaries of urban areas defined based on Census 2010 data. As a result, data for urban and rural areas from the ACS do not necessarily reflect the results of ongoing urbanization..Explanation of Symbols:An "**" entry in the margin of error column indicates that either no sample observations or too few sample observations were available to compute a standard error and thus the margin of error. A statistical test is not appropriate.An "-" entry in the estimate column indicates that either no sample observations or too few sample observations were available to compute an estimate, or a ratio of medians cannot be calculated because one or both of the median estimates falls in the lowest interval or upper interval of an open-ended distribution, or the margin of error associated with a median was larger than the median itself.An "-" following a median estimate means the median falls in the lowest interval of an open-ended distribution.An "+" following a median estimate means the median falls in the upper interval of an open-ended distribution.An "***" entry in the margin of error column indicates that the median falls in the lowest interval or upper interval of an open-ended distribution. A statistical test is not appropriate.An "*****" entry in the margin of error column indicates that the estimate is controlled. A statistical test for sampling variability is not appropriate. An "N" entry in the estimate and margin of error columns indicates that data for this geographic area cannot be displayed because the number of sample cases is too small.An "(X)" means that the estimate is not applicable or not available.

United States US: Gini Coefficient (GINI Index): World Bank Estimate data was reported at 41.500 % in 2016. This records an increase from the previous number of 41.000 % for 2013. United States US: Gini Coefficient (GINI Index): World Bank Estimate data is updated yearly, averaging 40.400 % from Dec 1979 (Median) to 2016, with 11 observations. The data reached an all-time high of 41.500 % in 2016 and a record low of 34.600 % in 1979. United States US: Gini Coefficient (GINI Index): World Bank Estimate 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: Poverty. Gini index measures the extent to which the distribution of income (or, in some cases, consumption expenditure) among individuals or households within an economy deviates from a perfectly equal distribution. A Lorenz curve plots the cumulative percentages of total income received against the cumulative number of recipients, starting with the poorest individual or household. The Gini index measures the area between the Lorenz curve and a hypothetical line of absolute equality, expressed as a percentage of the maximum area under the line. Thus a Gini index of 0 represents perfect equality, while an index of 100 implies perfect inequality.; ; World Bank, Development Research Group. Data are based on primary household survey data obtained from government statistical agencies and World Bank country departments. For more information and methodology, please see PovcalNet (http://iresearch.worldbank.org/PovcalNet/index.htm).; ; The World Bank’s internationally comparable poverty monitoring database now draws on income or detailed consumption data from more than one thousand six hundred household surveys across 164 countries in six regions and 25 other high income countries (industrialized economies). While income distribution data are published for all countries with data available, poverty data are published for low- and middle-income countries and countries eligible to receive loans from the World Bank (such as Chile) and recently graduated countries (such as Estonia) only. See PovcalNet (http://iresearch.worldbank.org/PovcalNet/WhatIsNew.aspx) for definitions of geographical regions and industrialized countries.

Central African Republic CF: Gini Coefficient (GINI Index): World Bank Estimate data was reported at 43.000 % in 2021. This records a decrease from the previous number of 56.200 % for 2008. Central African Republic CF: Gini Coefficient (GINI Index): World Bank Estimate data is updated yearly, averaging 56.200 % from Dec 1992 (Median) to 2021, with 3 observations. The data reached an all-time high of 61.300 % in 1992 and a record low of 43.000 % in 2021. Central African Republic CF: Gini Coefficient (GINI Index): World Bank Estimate data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Central African Republic – Table CF.World Bank.WDI: Social: Poverty and Inequality. Gini index measures the extent to which the distribution of income (or, in some cases, consumption expenditure) among individuals or households within an economy deviates from a perfectly equal distribution. A Lorenz curve plots the cumulative percentages of total income received against the cumulative number of recipients, starting with the poorest individual or household. The Gini index measures the area between the Lorenz curve and a hypothetical line of absolute equality, expressed as a percentage of the maximum area under the line. Thus a Gini index of 0 represents perfect equality, while an index of 100 implies perfect inequality.;World Bank, Poverty and Inequality Platform. Data are based on primary household survey data obtained from government statistical agencies and World Bank country departments. Data for high-income economies are mostly from the Luxembourg Income Study database. For more information and methodology, please see http://pip.worldbank.org.;;The World Bank’s internationally comparable poverty monitoring database now draws on income or detailed consumption data from more than 2000 household surveys across 169 countries. See the Poverty and Inequality Platform (PIP) for details (www.pip.worldbank.org).