Household data are collected as of March.

As stated in the Census's "Source and Accuracy of Estimates for Income, Poverty, and Health Insurance Coverage in the United States: 2011" (http://www.census.gov/hhes/www/p60_243sa.pdf):

Estimation of Median Incomes. The Census Bureau has changed the methodology for computing median income over time. The Census Bureau has computed medians using either Pareto interpolation or linear interpolation. Currently, we are using linear interpolation to estimate all medians. Pareto interpolation assumes a decreasing density of population within an income interval, whereas linear interpolation assumes a constant density of population within an income interval. The Census Bureau calculated estimates of median income and associated standard errors for 1979 through 1987 using Pareto interpolation if the estimate was larger than $20,000 for people or $40,000 for families and households. This is because the width of the income interval containing the estimate is greater than $2,500.

We calculated estimates of median income and associated standard errors for 1976, 1977, and 1978 using Pareto interpolation if the estimate was larger than $12,000 for people or $18,000 for families and households. This is because the width of the income interval containing the estimate is greater than $1,000. All other estimates of median income and associated standard errors for 1976 through 2011 (2012 ASEC) and almost all of the estimates of median income and associated standard errors for 1975 and earlier were calculated using linear interpolation.

Thus, use caution when comparing median incomes above $12,000 for people or $18,000 for families and households for different years. Median incomes below those levels are more comparable from year to year since they have always been calculated using linear interpolation. For an indication of the comparability of medians calculated using Pareto interpolation with medians calculated using linear interpolation, see Series P-60, Number 114, Money Income in 1976 of Families and Persons in the United States (www2.census.gov/prod2/popscan/p60-114.pdf).

Household data are collected as of March.

As stated in the Census's "Source and Accuracy of Estimates for Income, Poverty, and Health Insurance Coverage in the United States: 2011" (http://www.census.gov/hhes/www/p60_243sa.pdf):

Estimation of Median Incomes. The Census Bureau has changed the methodology for computing median income over time. The Census Bureau has computed medians using either Pareto interpolation or linear interpolation. Currently, we are using linear interpolation to estimate all medians. Pareto interpolation assumes a decreasing density of population within an income interval, whereas linear interpolation assumes a constant density of population within an income interval. The Census Bureau calculated estimates of median income and associated standard errors for 1979 through 1987 using Pareto interpolation if the estimate was larger than $20,000 for people or $40,000 for families and households. This is because the width of the income interval containing the estimate is greater than $2,500.

We calculated estimates of median income and associated standard errors for 1976, 1977, and 1978 using Pareto interpolation if the estimate was larger than $12,000 for people or $18,000 for families and households. This is because the width of the income interval containing the estimate is greater than $1,000. All other estimates of median income and associated standard errors for 1976 through 2011 (2012 ASEC) and almost all of the estimates of median income and associated standard errors for 1975 and earlier were calculated using linear interpolation.

Thus, use caution when comparing median incomes above $12,000 for people or $18,000 for families and households for different years. Median incomes below those levels are more comparable from year to year since they have always been calculated using linear interpolation. For an indication of the comparability of medians calculated using Pareto interpolation with medians calculated using linear interpolation, see Series P-60, Number 114, Money Income in 1976 of Families and Persons in the United States (www2.census.gov/prod2/popscan/p60-114.pdf).

This statistic shows the ratio of house prices to household income in the United Kingdom from 1976 to 2016. In 1976 the ratio of house prices to household income was ****. This has risen to **** in 2016. The lowest ratio at any point in this statistic was **** in 1996.

Abstract (en): The Recent College Graduates (RCG) survey estimates the potential supply of newly qualified teachers in the United States and explores the immediate post-degree employment and education experiences of individuals obtaining bachelor's or master's degrees from American colleges and universities. The RCG survey, which focuses heavily, but not exclusively, on those graduates qualified to teach at the elementary and secondary levels, is designed to meet the following objectives: (1) to determine how many graduates become eligible or qualified to teach for the first time and how many are employed as teachers in the year following graduation, by teaching field, (2) to examine the relationships among courses taken, student achievement, and occupational outcomes, and (3) to monitor unemployment rates and average salaries of graduates by field of study. The RCG survey collects information on education and employment of all graduates (date of graduation, field of study, whether newly qualified to teach, further enrollment, financial aid, employment status, and teacher employment characteristics) as well as standard demographic characteristics such as earnings, age, marital status, sex, and race/ethnicity. ICPSR data undergo a confidentiality review and are altered when necessary to limit the risk of disclosure. ICPSR also routinely creates ready-to-go data files along with setups in the major statistical software formats as well as standard codebooks to accompany the data. In addition to these procedures, ICPSR performed the following processing steps for this data collection: Checked for undocumented or out-of-range codes.. Students within one year of attaining a bachelor's or a master's degree from an American college or university. A two-stage stratified sampling approach was employed. The first stage consisted of drawing a sample of bachelor's and master's degree-granting institutions from Higher Education General Information Survey (HEGIS)/Integrated Postsecondary Education Data System (IPEDS) completions files. Institutions were stratified by control (public or private), by region, and by the proportion of degrees awarded in the field of education (over or under a specified number). Within each of these strata, institutions were selected according to size (size being measured by the sum of bachelor's and master's degrees awarded that year). The second stage consisted of the selection of a core sample of graduates (bachelor's and master's degree recipients) who received their degrees from the sampled institutions during the 1976-1977 academic year. Sampling rates of graduates differed by major field of study. The institution sample consisted of 300 institutions of which 30 were Historically Black Colleges (HBCs). The graduate sample was stratified by degree received and major field of study (vocational education, special education, other education, and noneducation). Data are representative at the national level. 2001-01-05 SAS and SPSS data definition statements have been created for this collection. Also, the codebook and data collection instrument were converted to a PDF file. The codebook and data collection instrument are provided by ICPSR as a Portable Document Format (PDF) file. The PDF file format was developed by Adobe Systems Incorporated and can be accessed using PDF reader software, such as the Adobe Acrobat Reader. Information on how to obtain a copy of the Acrobat Reader is provided on the ICPSR Web site.

Graph and download economic data for Real Median Household Income in North Carolina (MEHOINUSNCA672N) from 1984 to 2023 about NC, households, median, income, real, and USA.

In 2023, the median hourly earnings of wage and salary workers in the United States was 19.24 U.S. dollars. This is an increase from 1979, when median hourly earnings were at 4.44 U.S. dollars. Hourly Workers The United States national minimum wage is 7.25 U.S. dollars per hour, which has been the minimum wage since 2009. However, each state has the agency to set their state minimum wage. Furthermore, some cities are able to create their minimum wage. Many argue that the minimum wage is too low and should be raised, because it is not considered a living wage. There has been a movement to raise the minimum wage to 15 U.S. dollars per hour, called “Fight for 15” which began in the early 2010s. While there has been no movement at the federal level, some states have moved to increase their minimum wages, with at least three states and the District of Columbia setting minimum wage rates at or above 15 dollars per hour. More recently, some proponents of increasing the minimum wage say that 15 dollars is too low, and lawmakers should strive toward a higher goal, especially given that a 2021 analysis found that the minimum wage in the U.S. should be 22.88 U.S. dollars if it grew at the same rate as economic productivity. Salary Workers On the other hand, salary workers in the United States do not get paid on an hourly basis. The median weekly earnings of salary workers have significantly increased since 1979. Asian salary workers had the highest hourly earnings in the U.S. in 2021. Among female salary workers, those ages 45 to 54 years old had the highest median hourly earnings in 2021, likewise for male salary workers.

As of May 2025, the average annual price of Brent crude oil stood at 72 U.S. dollars per barrel. This is some eight U.S. dollars lower than the 2024 average. Brent is the world's leading price benchmark for Atlantic basin crude oils. Crude oil is one of the most closely observed commodity prices as it influences costs across all stages of the production process and consequently alters the price of consumer goods as well. What determines crude oil benchmarks? In the past decade, crude oil prices have been especially volatile. Their inherent inelasticity regarding short-term changes in demand and supply means that oil prices are erratic by nature. However, since the 2009 financial crisis, many commercial developments have greatly contributed to price volatility; such as economic growth by BRIC countries like China and India, and the advent of hydraulic fracturing and horizontal drilling in the U.S. The outbreak of the coronavirus pandemic and the Russia-Ukraine war are examples of geopolitical events dictating prices. Light crude oils - Brent and WTI Brent Crude is considered a classification of sweet light crude oil and acts as a benchmark price for oil around the world. It is considered a sweet light crude oil due to its low sulfur content and a low density and may be easily refined into gasoline. This oil originates in the North Sea and comprises several different oil blends, including Brent Blend and Ekofisk crude. Often, this crude oil is refined in Northwest Europe. Another sweet light oil often referenced alongside UK Brent is West Texas Intermediate (WTI). WTI oil prices amounted to 76.55 U.S. dollars per barrel in 2024.

Graph and download economic data for Real Median Household Income in New York (MEHOINUSNYA672N) from 1984 to 2023 about NY, households, median, income, real, and USA.

Analysis of ‘Canada National & Provincial Per Capita Income’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://www.kaggle.com/charlesluan/canada-national-provincial-capita-income-762019 on 28 January 2022.

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

Filtered data which only remains 10 provinces and national capita income, median income, with 16 years old & over, both sexes, in 2019 constant dollar

• The raw data had been already adjusted by 2019 constant dollar, from 1976-2019

• Please be aware territories of Canada were not listed in the original dataset

• For example, the 2018 Canada national average income is not equal to the average of 10 provinces income, since territories are not in the list.

• My practicing data exploration of this dataset: Facts of Individuals Income in Canada, 1976 - 2019

Acknowledgements

Data source:
Income of individuals by age group, sex and income source, Canada, provinces and selected census metropolitan areas **Raw data version: ** Table: 11-10-0239-01 (formerly CANSIM 206-0052) **Release date: ** 2021-03-23

Inspiration

I was really surprised when revealing these rows, it seems like there isn't much growth since 1976 Canada average income is 40,800 dollars while 2019 is 49,000 dollars. (Please be noticed these are adjusted by 2019 constant dollar)

Please correct me if I was wrong. Thank you

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

Household data are collected as of March.

As stated in the Census's "Source and Accuracy of Estimates for Income, Poverty, and Health Insurance Coverage in the United States: 2011" (http://www.census.gov/hhes/www/p60_243sa.pdf):

Estimation of Median Incomes. The Census Bureau has changed the methodology for computing median income over time. The Census Bureau has computed medians using either Pareto interpolation or linear interpolation. Currently, we are using linear interpolation to estimate all medians. Pareto interpolation assumes a decreasing density of population within an income interval, whereas linear interpolation assumes a constant density of population within an income interval. The Census Bureau calculated estimates of median income and associated standard errors for 1979 through 1987 using Pareto interpolation if the estimate was larger than $20,000 for people or $40,000 for families and households. This is because the width of the income interval containing the estimate is greater than $2,500.

We calculated estimates of median income and associated standard errors for 1976, 1977, and 1978 using Pareto interpolation if the estimate was larger than $12,000 for people or $18,000 for families and households. This is because the width of the income interval containing the estimate is greater than $1,000. All other estimates of median income and associated standard errors for 1976 through 2011 (2012 ASEC) and almost all of the estimates of median income and associated standard errors for 1975 and earlier were calculated using linear interpolation.

Thus, use caution when comparing median incomes above $12,000 for people or $18,000 for families and households for different years. Median incomes below those levels are more comparable from year to year since they have always been calculated using linear interpolation. For an indication of the comparability of medians calculated using Pareto interpolation with medians calculated using linear interpolation, see Series P-60, Number 114, Money Income in 1976 of Families and Persons in the United States (www2.census.gov/prod2/popscan/p60-114.pdf).

Wages in India increased to 21103 INR/Month in the second quarter of 2024 from 21036 INR/Month in the first quarter of 2024. This dataset provides the latest reported value for - India Average Daily Real Wage Rate - 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 Median Household Income in Washington (MEHOINUSWAA646N) from 1984 to 2023 about WA, households, median, income, and USA.

WMS service corresponding to the maps of average decennial precipitation in the period 1976-2005 for the month of February. Precipitation is given in millimeters. This information was prepared in the context of the DESERTNET project from data from meteorological stations of the State Meteorological Agency and the Ministry of the Environment. Spatialization of the data was performed using the distance inverse method. Each service includes three layers each of which corresponds to a dozen of the month. Node of the Andalusian Environmental Information Network. Regional Government of Andalusia. Integrated in the Spatial Data Infrastructure of Andalusia, following the guidelines of the Cartographic System of Andalusia.

The 2025 preliminary average annual price of West Texas Intermediate crude oil reached 68.24 U.S. dollars per barrel, as of May. This would be eight U.S. dollars below the 2024 average and the lowest annual average since 2021. WTI and other benchmarks WTI is a grade of crude oil also known as “Texas light sweet.” It is measured to have an API gravity of around 39.6 and specific gravity of about 0.83, which is considered “light” relative to other crude oils. This oil also contains roughly 0.24 percent sulfur, and is therefore named “sweet.” Crude oils are some of the most closely observed commodity prices in the world. WTI is the underlying commodity of the Chicago Mercantile Exchange’s oil futures contracts. The price of other crude oils, such as UK Brent crude oil, the OPEC crude oil basket, and Dubai Fateh oil, can be compared to that of WTI crude oil. Since 1976, the price of WTI crude oil has increased notably, rising from just 12.23 U.S. dollars per barrel in 1976 to a peak of 99.06 dollars per barrel in 2008. Geopolitical conflicts and their impact on oil prices The price of oil is controlled in part by limiting oil production. Prior to 1971, the Texas Railroad Commission controlled the price of oil by setting limits on production of U.S. oil. In 1971, the Texas Railroad Commission ceased limiting production, but OPEC, the Organization of Petroleum Exporting Countries with member states Iran, Iraq, Kuwait, Saudi Arabia, and Venezuela among others, continued to do so. In 1972, due to geopolitical conflict, OPEC set an oil embargo and cut oil production, causing prices to quadruple by 1974. Oil prices rose again in 1979 and 1980 due to the Iranian revolution, and doubled between 1978 and 1981 as the Iran-Iraq War prevented oil production. A number of geopolitical conflicts and periods of increased production and consumption have influenced the price of oil since then.

Graph and download economic data for Median Household Income in South Carolina (MEHOINUSSCA646N) from 1984 to 2023 about SC, households, median, income, and USA.

The average household income from agriculture and non-agricultural sources (since 1976).

The Gross Domestic Product per capita in Jordan was last recorded at 4016.83 US dollars in 2024. The GDP per Capita in Jordan is equivalent to 32 percent of the world's average. This dataset provides - Jordan GDP per capita - actual values, historical data, forecast, chart, statistics, economic calendar and news.

To what extent can state governments influence economic inequality? How do state fiscal policies of redistribution affect families in different economic situations? Using a large database of state fiscal policymaking tools (taxing and spending) between 1976 and 2006 we examine the effect of these tools on state level inequality as well as the average incomes of families in different economic groups. We find that state taxing and spending efforts can influence these indicators of economic inequality, though these fiscal policy tools can have differential effects. Spending on unemployment compensation and cash assistance as well as revenue from taxes on corporations are found to reduce state level inequality. We also find unemployment compensation to positively benefit the bottom 10th percentile of income earners, while the inheritance tax helps all income groups. Corporate tax revenue is associated with higher middle class incomes, while income tax revenue benefits both middle and upper incomes. Sales tax revenue positively benefits wealthy earners. Higher property tax revenue is associated with decreased income for all groups. These results suggest that state governments can affect redistribution through fiscal policies by affecting both state level inequality as well as the economic fortunes of different income groups.

Annual rainfall is the total accumulated rain over one year. Rain is vital for life, including plant growth, drinking water, river ecosystem health, and sanitation. Floods and droughts affect our environment, economy, and recreational opportunities.

This layer shows the annual rainfall as a percentage of normal across New Zealand for 1976 as part of the data series for years 1972 to 2013. Annual rainfall is the total accumulated rain over one year. It is estimated from the daily rainfall estimates of the Virtual Climate Station Network (NIWA). 'Normal' is defined as the average annual rainfall from 1972–2013.

This dataset relates to the "Annual average rainfall" measure on the Environmental Indicators, Te taiao Aotearoa website.

Geometry: raster catalogue Unit: percent

WMS service corresponding to the maps of average decennial precipitation in the period 1976-2005 for the month of May. Precipitation is given in millimeters. This information was prepared in the context of the DESERTNET project from data from meteorological stations of the State Meteorological Agency and the Ministry of the Environment. Spatialization of the data was performed using the distance inverse method. Each service includes three layers each of which corresponds to a dozen of the month. Node of the Andalusian Environmental Information Network. Regional Government of Andalusia. Integrated in the Spatial Data Infrastructure of Andalusia, following the guidelines of the Cartographic System of Andalusia.