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.

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).

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 data collection supplies standard monthly labor force data on work experience, income, and migration. Comprehensive information is given on the employment status, occupation, and industry of persons 14 years old and older. Additional data are available concerning weeks worked and hours per week worked, reason not working full-time, total income and income components, and residence. In 1976, household records were introduced for the first time into the Annual Demographic File, in addition to family and person records. Information on demographic characteristics, such as age, sex, race, marital status, veteran status, household relationship, educational attainment, and Hispanic origin, is available for each person in the household enumerated.

South Korea's Occupational Wage Survey (OWS) is an annual business establishment survey conducted since 1970 by South Korea's Ministry of Labor. The dataset contains detailed information on individual workers' earnings, hours worked, educational attainment, actual labor market experience, occupation, industry, and region. The surveyed establishments must employ at least ten workers and were selected by a stratified random sampling method. Because they exclude workers in small enterprises, the self-employed, family workers, temporary workers, and public sector workers, the surveys represent approximately one-half of South Korea's total nonagricultural labor force. The samples for each year are randomly drawn from the original surveys. The surveys cover all industries up through 1986. After 1986, agriculture, forestry, hunting, and fishing are excluded. This change in sampling procedure does not appear to cause a significant change in the types of nonfarm enterprises covered by the survey.

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.

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 ---

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

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).

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

The aim of the Graduate Careers Council of Australia's annual Graduate Destination Survey is to collect information about the activities of Australia's higher education graduates after the completion of their degree. The survey was begun in 1974 and has been conducted annually since then. This particular file reflects the 1976 data. The target population for the survey is graduates who had completed requirements for higher education qualifications in the previous calendar year, including graduates residing overseas and international students. The survey variables can be broadly categorised into three areas of investigation: Course, Employment and Further study. Course variables include level of qualification attained; field of study; attendance; length of time taken to complete the course; and employer support, if applicable, during the course. Employment variables include employment status at census date; whether employed full-time or part-time; whether a short-term or permanent employee; occupation at census date; annual salary; and length of service. Further study variables include level of current qualification; field of study; attendance; date of course commencement; and institution attended. Background variables include age, sex, residency status, home state, disability, non-english speaking background, first educational qualification after leaving school, and highest educational qualification prior to undertaking the course.

Canada Median Income: 2018p: Economic Families: Elderly data was reported at 88,000.000 CAD in 2023. This records an increase from the previous number of 84,700.000 CAD for 2022. Canada Median Income: 2018p: Economic Families: Elderly data is updated yearly, averaging 60,000.000 CAD from Dec 1976 (Median) to 2023, with 48 observations. The data reached an all-time high of 88,000.000 CAD in 2023 and a record low of 41,400.000 CAD in 1976. Canada Median Income: 2018p: Economic Families: Elderly data remains active status in CEIC and is reported by Statistics Canada. The data is categorized under Global Database’s Canada – Table CA.H028: Average Family Income by Economic Family Type.

Income of individuals by age group, sex and income source, Canada, provinces and selected census metropolitan areas, annual.

About this dataset

Context

The dataset presents the detailed breakdown of the count of individuals within distinct income brackets, categorizing them by gender (men and women) and employment type - full-time (FT) and part-time (PT), offering valuable insights into the diverse income landscapes within Clayton town. The dataset can be utilized to gain insights into gender-based income distribution within the Clayton town population, aiding in data analysis and decision-making..

Key observations

• Employment patterns: Within Clayton town, among individuals aged 15 years and older with income, there were 1,976 men and 1,507 women in the workforce. Among them, 1,174 men were engaged in full-time, year-round employment, while 802 women were in full-time, year-round roles.
• Annual income under $24,999: Of the male population working full-time, 1.79% fell within the income range of under $24,999, while 6.86% of the female population working full-time was represented in the same income bracket.
• Annual income above $100,000: 45.74% of men in full-time roles earned incomes exceeding $100,000, while 32.54% of women in full-time positions earned within this income bracket.
• Refer to the research insights for more key observations on more income brackets ( Annual income under $24,999, Annual income between $25,000 and $49,999, Annual income between $50,000 and $74,999, Annual income between $75,000 and $99,999 and Annual income above $100,000) and employment types (full-time year-round and part-time)

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

Income brackets:

• $1 to $2,499 or loss
• $2,500 to $4,999
• $5,000 to $7,499
• $7,500 to $9,999
• $10,000 to $12,499
• $12,500 to $14,999
• $15,000 to $17,499
• $17,500 to $19,999
• $20,000 to $22,499
• $22,500 to $24,999
• $25,000 to $29,999
• $30,000 to $34,999
• $35,000 to $39,999
• $40,000 to $44,999
• $45,000 to $49,999
• $50,000 to $54,999
• $55,000 to $64,999
• $65,000 to $74,999
• $75,000 to $99,999
• $100,000 or more

Variables / Data Columns

• Income Bracket: This column showcases 20 income brackets ranging from $1 to $100,000+..
• Full-Time Males: The count of males employed full-time year-round and earning within a specified income bracket
• Part-Time Males: The count of males employed part-time and earning within a specified income bracket
• Full-Time Females: The count of females employed full-time year-round and earning within a specified income bracket
• Part-Time Females: The count of females employed part-time and earning within a specified income bracket

Employment type classifications include:

• Full-time, year-round: A full-time, year-round worker is a person who worked full time (35 or more hours per week) and 50 or more weeks during the previous calendar year.
• Part-time: A part-time worker is a person who worked less than 35 hours per week during the previous calendar year.

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.

Inspiration

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/.

Recommended for further research

This dataset is a part of the main dataset for Clayton town median household income by race. You can refer the same here

Malaysia HIBAS: Monthly Gross Income: Mean: Sarawak data was reported at 5,387.000 MYR in 2016. This records an increase from the previous number of 4,934.000 MYR for 2014. Malaysia HIBAS: Monthly Gross Income: Mean: Sarawak data is updated yearly, averaging 2,259.000 MYR from Dec 1976 (Median) to 2016, with 16 observations. The data reached an all-time high of 5,387.000 MYR in 2016 and a record low of 426.000 MYR in 1976. Malaysia HIBAS: Monthly Gross Income: Mean: Sarawak data remains active status in CEIC and is reported by Department of Statistics. The data is categorized under Global Database’s Malaysia – Table MY.H031: Household Income and Basic Amenities Survey: Monthly Gross Income: Median and Mean: by State.

This table contains 67200 series, with data for years 1976 - 2011 (not all combinations necessarily have data for all years). This table contains data described by the following dimensions (Not all combinations are available): Geography (35 items: Canada; Atlantic provinces; Newfoundland and Labrador; Prince Edward Island; ...); Sex (3 items: Both sexes; Males; Females); Age group (8 items: All age groups; Under 20 years; 20 to 24 years; 25 to 34 years; ...); Income recipient (4 items: Number of recipients; Aggregate income of recipients; Average income of recipients; Median income of recipients); Income source (20 items: Total income; Market income; Earnings; Wages, salaries and commissions; ...).

Graph and download economic data for State Minimum Wage Rate for Virginia (STTMINWGVA) from 1976 to 2025 about minimum wage, VA, wages, rate, and USA.