Graph and download economic data for Real Median Family Income in the United States (MEFAINUSA672N) from 1953 to 2023 about family, median, income, real, and USA.

Compared to the mid-20th century, wage increases in the United States' industrial sector did not change as drastically over the preceding 150 years. Industrial wages in the 1800s peaked in the final year of the American Civil War in 1865, and they were double the value of wages in 1830; yet wages did not exceed this value until the following century. Throughout the 1900s, however, the increase was much more pronounced; between 1943 and 1955 alone, industrial wages doubled, and quadrupled by 1972. In fact, wages in 1985 were over five times higher than they were in 1955, and ten times higher than in 1943. The only times during the 20th century when industrial wages fell was during the post-WWI recession in 1921, and again during the Great Depression in the 1930s.

Graph and download economic data for Personal income per capita (A792RC0A052NBEA) from 1929 to 2024 about personal income, per capita, personal, income, GDP, and USA.

During the early days of professional baseball, the dominant major leagues imposed a “reserve clause” designed to limit player wages by restricting competition for labor. Entry into the market by rival leagues challenged the incumbent monopsony cartel’s ability to restrict compensation. Using a sample of player salaries from the first 40 years of the reserve clause (1880-1919), this study examines the impact of inter-league competition on player wages. This study finds a positive salary effect associated with rival league entry that is consistent with monopsony wage suppression, but the effect is stronger during the 20th century than the 19th century. Changes in levels of market saturation and minor-league competition may explain differences in the effects between the two eras.

Wages in Macedonia increased 10.60 percent in April of 2025 over the same month in the previous year. This dataset provides - Macedonia Real Wage Growth- actual values, historical data, forecast, chart, statistics, economic calendar and news.

Russia Population: Percent of Total: Household Income per Capita: 14000.1 - 19000 RUB per Month data was reported at 13.800 % in Dec 2018. This records a decrease from the previous number of 14.400 % for Sep 2018. Russia Population: Percent of Total: Household Income per Capita: 14000.1 - 19000 RUB per Month data is updated quarterly, averaging 15.400 % from Dec 2011 (Median) to Dec 2018, with 29 observations. The data reached an all-time high of 16.300 % in Mar 2014 and a record low of 13.800 % in Dec 2018. Russia Population: Percent of Total: Household Income per Capita: 14000.1 - 19000 RUB per Month data remains active status in CEIC and is reported by Federal State Statistics Service. The data is categorized under Russia Premium Database’s Demographic and Labour Market – Table RU.GA013: Population by Average Household Income.

Compared to Western Europe, the development of average incomes differed between Scandinavia and and East-Central Europe between 1900 and 1950. Over these five decades, income in Scandinavia gradually caught up with the rest of Western Europe, eventually overtaking it by the middle of the century. By contrast, income across East-Central Europe fell further behind the west over this period, falling from 42 percent of the west's rate in 1900 to 37 percent in 1950.

This study contains selected demographic, social, economic, public policy, and political comparative data for Switzerland, Canada, France, and Mexico for the decades of 1900-1960. Each dataset presents comparable data at the province or district level for each decade in the period. Various derived measures, such as percentages, ratios, and indices, constitute the bulk of these datasets. Data for Switzerland contain information for all cantons for each decennial year from 1900 to 1960. Variables describe population characteristics, such as the age of men and women, county and commune of origin, ratio of foreigners to Swiss, percentage of the population from other countries such as Germany, Austria and Lichtenstein, Italy, and France, the percentage of the population that were Protestants, Catholics, and Jews, births, deaths, infant mortality rates, persons per household, population density, the percentage of urban and agricultural population, marital status, marriages, divorces, professions, factory workers, and primary, secondary, and university students. Economic variables provide information on the number of corporations, factory workers, economic status, cultivated land, taxation and tax revenues, canton revenues and expenditures, federal subsidies, bankruptcies, bank account deposits, and taxable assets. Additional variables provide political information, such as national referenda returns, party votes cast in National Council elections, and seats in the cantonal legislature held by political groups such as the Peasants, Socialists, Democrats, Catholics, Radicals, and others. Data for Canada provide information for all provinces for the decades 1900-1960 on population characteristics, such as national origin, the net internal migration per 1,000 of native population, population density per square mile, the percentage of owner-occupied dwellings, the percentage of urban population, the percentage of change in population from preceding censuses, the percentage of illiterate population aged 5 years and older, and the median years of schooling. Economic variables provide information on per capita personal income, total provincial revenue and expenditure per capita, the percentage of the labor force employed in manufacturing and in agriculture, the average number of employees per manufacturing establishment, assessed value of real property per capita, the average number of acres per farm, highway and rural road mileage, transportation and communication, the number of telephones per 100 population, and the number of motor vehicles registered per 1,000 population. Additional variables on elections and votes are supplied as well. Data for France provide information for all departements for all legislative elections since 1936, the two presidential elections of 1965 and 1969, and several referenda held in the period since 1958. Social and economic data are provided for the years 1946, 1954, and 1962, while various policy data are presented for the period 1959-1962. Variables provide information on population characteristics, such as the percentages of population by age group, foreign-born, bachelors aged 20 to 59, divorced men aged 25 and older, elementary school students in private schools, elementary school students per million population from 1966 to 1967, the number of persons in household in 1962, infant mortality rates per million births, and the number of priests per 10,000 population in 1946. Economic variables focus on the Gross National Product (GNP), the revenue per capita per household, personal income per capita, income tax, the percentage of active population in industry, construction and public works, transportation, hotels, public administration, and other jobs, the percentage of skilled and unskilled industrial workers, the number of doctors per 10,000 population, the number of agricultural cooperatives in 1946, the average hectares per farm, the percentage of farms cultivated by the owner, tenants, and sharecroppers, the number of workhorses, cows, and oxen per 100 hectares of farmland in 1946, and the percentages of automobiles per 1,000 population, radios per 100 homes, and cinema seats per 1,000 population. Data are also provided on the percentage of Communists (PCF), Socialists, Radical Socialists, Conservatives, Gaullists, Moderates, Poujadists, Independents, Turnouts, and other political groups and p

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 Calumet Park. The dataset can be utilized to gain insights into gender-based income distribution within the Calumet Park population, aiding in data analysis and decision-making..

Key observations

• Employment patterns: Within Calumet Park, among individuals aged 15 years and older with income, there were 1,900 men and 2,446 women in the workforce. Among them, 810 men were engaged in full-time, year-round employment, while 1,030 women were in full-time, year-round roles.
• Annual income under $24,999: Of the male population working full-time, 7.04% fell within the income range of under $24,999, while 0.58% of the female population working full-time was represented in the same income bracket.
• Annual income above $100,000: 15.43% of men in full-time roles earned incomes exceeding $100,000, while 5.83% 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 Calumet Park median household income by race. You can refer the same here

This collection of wage data was published in „Die Geschichte der Lage der Arbeiter in Deutschland von 1789 bis in die Gegenwart“ by Jürgen Kuczynski (volume I and volume II, here quoted after 6th edition, Berlin 1953, 1954). The data contains wage indices of a certain base year and the corresponding wage raw data (hourly wages, weekly wages, annual wages in marks and pfennigs). The wage data is regionally widely spread until the year 1914; it contains single cities as well as bigger regional units. Since 1924 Kuczynski’s surveys rely on the publications of the statistical office. The wage data is ordered by professional groups, industry and agriculture and by certain industrial sectors. Kuczynski’s wage index is mainly based on publications of trade unions and on reports of different chambers of commerce. The weaknesses of the indices are due to the methodological inconsequence and the limited representative status concerning the election of geographical units. Union wages and also actually paid wages are considered in the calculations, like for example daily, weekly and annual wages or layer wages for miners. On the other side important industrial sectors such as the food or the textile sector are not taken into account. Wage data for agriculture relies often on estimations or is calculated with insufficient material. Wages for work at home are not taken into account in the index calculation. There are also problems with the representative status of the index regarding regional units because cities are weighted too important compared with rural regions. Another topic of the survey is the construction of an index of costs of living. For a long time Kuczynski’s index for costs of living was without any concurrence. It was used by different authors without any changes or modifications. The substantial weakness of the index is that for the calculation of the development of the costs of living, it only takes costs of food and rent into account. Prices of food and rent were weighted in the ratio 3 to 1. Kuczynski does not give an explanation for this weighting. Further the certain price indices for food and rent were calculated by the aggregation of incomplete regional price developments.

Data tables in HistatA – Tables for the period from 1800 to1870:A.1 Wage Data (in Mark and Pfennig)A.2 Wage indices, base 1900 = 100A.3 Costs of living and real wages 1900 = 100 B - Tables for the period from 1870 to 1932:B.1 Wage Data (in Mark and Pfennig)B.2 Wage indices, base 1900 = 100B.3 Costs of living and real wages 1900 = 100 C - Tables for the period from 1932 to 1945:C.1 Wage Data (in Mark and Pfennig)C.2 Wage indices, base 1900 = 100C.3 Costs of living and real wages 1932 = 100

In 1900, the Pennsylvania Railroad, the largest non-government employer of at the time, introduced an new pension system of mandatory retirement for all employees over 70 from vice presidents to crossing guards. Workers in ill health could retire after age 65 with the approval of their supervisors. The rules were that the amount of a worker’s pension was one percent of their average earnings in the previous ten years times the length of their service. The Pennsylvania Railroad pension became a model for other railroads and large companies. These data describe the first twenty years of the pension. Information about almost ten thousand retirees was collected from the reports of the Pennsylvania Railroad Board for the Eastern Lines from 1900 to 1920. The data include names, occupations, average earnings, pension allowances, type of retirement (mandatory at age 70 or by request of the retiree or his supervisor), ages, years of service, and dates of retirement and death. The retirees are almost all male and white. The Pension Board intentionally excluded dining car workers, who were predominantly Black. During the first six years of the pension, average earnings were computed by assuming full time employment, but the Pension Board began using actual earnings in 1906. To study the effect of this change, the Pension Board’s reports included both actual and full-time earnings for employees who retired from 1906 to 1908.

In 2023, employees who graduated in computer science earned around 2,150 euros net per month five years after obtaining their master's degree. Industrial and information engineers were paid 2,000 euros monthly. By contrast, graduates in psychology and education earned on average 1,400 euros, 370 euros less than the national mean. There were significant salary differences between male and female graduates, too. Women graduated in 2018 received 1,640 euros monthly in 2023, whereas men were paid an average of 1900 euros.

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 River Grove. The dataset can be utilized to gain insights into gender-based income distribution within the River Grove population, aiding in data analysis and decision-making..

Key observations

• Employment patterns: Within River Grove, among individuals aged 15 years and older with income, there were 3,399 men and 3,742 women in the workforce. Among them, 1,977 men were engaged in full-time, year-round employment, while 1,900 women were in full-time, year-round roles.
• Annual income under $24,999: Of the male population working full-time, 1.92% fell within the income range of under $24,999, while 7.79% of the female population working full-time was represented in the same income bracket.
• Annual income above $100,000: 24.23% of men in full-time roles earned incomes exceeding $100,000, while 6.47% 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 River Grove median household income by race. You can refer the same here

This table contains 11 series, with data for years 1926 - 1960 (not all combinations necessarily have data for all years), and was last released on 2009-01-21. This table contains data described by the following dimensions (Not all combinations are available): Geography (1 items: Canada ...), Income-based estimates (11 items: Gross domestic product (GDP) at market prices; Net domestic income at factor cost; Wages; salaries and supplementary labour income; Corporation profits before taxes ...).

This table contains data on the income, expenditure and debt of municipalities since 1900. The data has been collected from previous publications on municipal finances. The most newsworthy and consistent municipal figures on income, expenditure and debt are included in this table. The data presented comes from the annual accounts and balance sheets of municipalities and correspond as much as possible to the classifications and registration methods that the municipalities use in their own administration. This table replaces the series on the finances of the municipalities in the Government History table. Data available from: 1900 Important policy events: 1986 - as a result of a different method of financing the old people's homes, a peak of 2 billion euros is visible on the income side of the Capital Account. 1995 - in this year, municipalities received approximately 15.5 billion euros from the government as a lump sum payment for the housing law loans. This leads to a one-time peak in the capital account income. The loans taken out have been repaid with this lump sum, so that in 1995 these will also decrease by the same amount. 2008 - As of January 1, 2008, payments received in advance from European and Dutch governments with a specific spending objective (eg the construction of new infrastructure) to cover expenditure in subsequent years are otherwise included in the balance sheet. These are included under Accruals and deferred income from this date. The amounts were previously booked under Provisions. This has led to a break in the figures of the relevant balance sheet items from 2007 to 2008. 2009 - as a result of the sale of Nuon/Essent shares, a peak of EUR 5.2 billion is visible. Since the received book profit and super dividends are included in the administrative current account, the increase is visible there. 2015 - Due to the transfer of tasks in the area of ​​the Social Domain from central government to municipalities, income and expenditure will increase by approximately 7 billion euros. 2020 - The sale of Eneco shares provides additional income (book profit) of 4.1 billion euros. Status of the figures: The results from 1900 up to and including 2020 are final, the results for 2021 are provisional. Changes as of March 22, 2023: The provisional figures for 2021 have been included. The figures for 2020 are now final. When will new figures be published: The new annual figures on the finances of the municipalities will be published approximately 15 months after the end of the reporting period. The figures can be adjusted based on the availability of new or updated source material. In general, the adjustments are minor. The adjustments are made when a new annual figure is added to the series.

One year after obtaining their university title, graduates in Italy earned an average net salary of 1,340 euros per month in 2023. People graduating in 2020 were paid 240 euros more, while those who obtained their tertiary education diploma in 2018 gained monthly 1,900 euros net. Hence, average salaries proportionally raised as work experience augmented. On the contrary, the salary gap between women and men grew as career progressed. One year after graduation, women earned 180 euros less than male colleagues. However, for those graduated in 2020, this difference increased to 200 euros, and five years after graduation it reached 250 euros.

This collection of wage data was published in „Die Geschichte der Lage der Arbeiter in Deutschland von 1789 bis in die Gegenwart“ by Jürgen Kuczynski (volume I and volume II, here quoted after 6th edition, Berlin 1953, 1954). The data contains wage indices of a certain base year and the corresponding wage raw data (hourly wages, weekly wages, annual wages in marks and pfennigs). The wage data is regionally widely spread until the year 1914; it contains single cities as well as bigger regional units. Since 1924 Kuczynski’s surveys rely on the publications of the statistical office. The wage data is ordered by professional groups, industry and agriculture and by certain industrial sectors. Kuczynski’s wage index is mainly based on publications of trade unions and on reports of different chambers of commerce. The weaknesses of the indices are due to the methodological inconsequence and the limited representative status concerning the election of geographical units. Union wages and also actually paid wages are considered in the calculations, like for example daily, weekly and annual wages or layer wages for miners. On the other side important industrial sectors such as the food or the textile sector are not taken into account. Wage data for agriculture relies often on estimations or is calculated with insufficient material. Wages for work at home are not taken into account in the index calculation. There are also problems with the representative status of the index regarding regional units because cities are weighted too important compared with rural regions. Another topic of the survey is the construction of an index of costs of living. For a long time Kuczynski’s index for costs of living was without any concurrence. It was used by different authors without any changes or modifications. The substantial weakness of the index is that for the calculation of the development of the costs of living, it only takes costs of food and rent into account. Prices of food and rent were weighted in the ratio 3 to 1. Kuczynski does not give an explanation for this weighting. Further the certain price indices for food and rent were calculated by the aggregation of incomplete regional price developments.

Data tables in Histat A – Tables for the period from 1800 to1870: A.1 Wage Data (in Mark and Pfennig) A.2 Wage indices, base 1900 = 100 A.3 Costs of living and real wages 1900 = 100

B - Tables for the period from 1870 to 1932: B.1 Wage Data (in Mark and Pfennig) B.2 Wage indices, base 1900 = 100 B.3 Costs of living and real wages 1900 = 100

C - Tables for the period from 1932 to 1945: C.1 Wage Data (in Mark and Pfennig) C.2 Wage indices, base 1900 = 100 C.3 Costs of living and real wages 1932 = 100

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 Plattsburgh town. The dataset can be utilized to gain insights into gender-based income distribution within the Plattsburgh town population, aiding in data analysis and decision-making..

Key observations

• Employment patterns: Within Plattsburgh town, among individuals aged 15 years and older with income, there were 4,521 men and 4,737 women in the workforce. Among them, 2,048 men were engaged in full-time, year-round employment, while 1,900 women were in full-time, year-round roles.
• Annual income under $24,999: Of the male population working full-time, 5.08% fell within the income range of under $24,999, while 13.32% of the female population working full-time was represented in the same income bracket.
• Annual income above $100,000: 19.87% of men in full-time roles earned incomes exceeding $100,000, while 13.79% 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 Plattsburgh town median household income by race. You can refer the same here

Information on farm household income and farm household composition. Source agency: Environment, Food and Rural Affairs Designation: National Statistics Language: English Alternative title: Farm Household Income and Household Composition, England

If you require the datasets in a more accessible format, please contact fbs.queries@defra.gsi.gov.uk

Background and guidance on the statistics

Information on farm household income and farm household composition was collected in the Farm Business Survey (FBS) for England for the first time in 2004/05. Collection of household income data is restricted to the household of the principal farmer from each farm business. For practical reasons, data is not collected for the households of any other farmers and partners. Two-thirds of farm businesses have an input only from the principal farmer’s household (see table 5). However, details of household composition are collected for the households of all farmers and partners in the business, but not employed farm workers.

Data on the income of farm households is used in conjunction with other economic information for the agricultural sector (e.g. farm business income) to help inform policy decisions and to help monitor and evaluate current policies relating to agriculture in the United Kingdom by Government. It also informs wider research into the economic performance of the agricultural industry.

This release gives the main results from the income and composition of farm households and the off-farm activities of the farmer and their spouse (Including common law partners) sections of the FBS. These sections include information on the household income of the principal farmer’s household, off-farm income sources for the farmer and spouse and incomes of other members of their household and the number of working age and pensionable adults and children in each of the households on the farm (the information on household composition can be found in Appendix B).

This release provides the main results from the 2013/14 FBS. The results are presented together with confidence intervals.

Survey content and methodology

The Farm Business Survey (FBS) is an annual survey providing information on the financial position and physical and economic performance of farm businesses in England. The sample of around 1,900 farm businesses covers all regions of England and all types of farming with the data being collected by face to face interview with the farmer. Results are weighted to represent the whole population of farm businesses that have at least 25 thousand Euros of standard output as recorded in the annual June Survey of Agriculture and Horticulture. In 2013 there were just over 58 thousand farm businesses meeting this criteria.

Since 2009/10 a sub-sample of around 1,000 farms in the FBS has taken part in both the additional surveys on the income and composition of farm households and the off-farm activities of the farmer and their spouse. In previous years, the sub-sample had included over 1,600 farms. As such, caution should be taken when comparing to earlier years.

The farms that responded to the additional survey on household incomes and off-farm activities of the farmer and spouse had similar characteristics to those farms in the main FBS in terms of farm type and geographical location. However, there is a smaller proportion of very large farms in the additional survey than in the main FBS. Full details of the characteristic of responding farms can be found at Appendix A of the notice.

For further information about the Farm Business Survey please see: https://www.gov.uk/government/organisations/department-for-environment-food-rural-affairs/series/farm-business-survey

Data analysis

The results from the FBS relate to farms which have a standard output of at least 25,000 Euros. Initial weights are applied to the FBS records based on the inverse sampling fraction for each design stratum (farm type by farm size). These weights are then adjusted (calibration weighting) so that they can produce unbiased estimators of a number of different target variables. Completion of the additional survey on household incomes and off-farm activities of the farmer and spouse was voluntary and a sample of around 1,000 farms was achieved. In order to take account of non-response, the results have been reweighted using a method that preserves marginal totals for populations according to farm type and farm size groups. As such, farm population totals for other classifications (e.g. regions) will not be in-line with results using the main FBS weights, nor will any results produced for variables derived from the rest of the FBS (e.g. farm business income).

Accuracy and reliability of the results

We show 95% confidence intervals against the results. These show the range of values that may apply to the figures. They mean that we are 95% confident that this range contains the true value. They are calculated as the standard errors (se) multiplied by 1.96 to give the 95% confidence interval. The standard errors only give an indication of the sampling error. They do not reflect any other sources of survey errors, such as non-response bias. For the Farm Business Survey, the confidence limits shown are appropriate for comparing groups within the same year only; they should not be used for comparing with previous years since they do not allow for the fact that many of the same farms will have contributed to the Farm Business Survey in both years.

Availability of results

This release contains headline results for each section. The full set of results can be found at: https://www.gov.uk/government/organisations/department-for-environment-food-rural-affairs/series/farm-business-survey#publications

Defra statistical notices can be viewed on the on the statistics pages of the Defra website at https://www.gov.uk/government/organisations/department-for-environment-food-rural-affairs/about/statistics. This site also shows details of future publications, with pre-announced dates.

Data Uses

Data from the Farm Business Survey (FBS) are provided to the EU as part of the Farm Accountancy Data Network (FADN). The data have been used to help inform policy decisions (e.g. Reform of Pillar 1 and Pillar 2 of Common Agricultural Policy) and to help monitor and evaluate current policies relating to agriculture in England (and the EU). It is also widely used by the industry for benchmarking and informs wider research into the economic performance of the agricultural industry.

User engagement

As part of our ongoing commitment to compliance with the Code of Practice for Official Statistics http://www.statisticsauthority.gov.uk/assessment/code-of-practice/index.html, we wish to strengthen our engagement with users of these statistics and better understand the use made of them and the types of decisions that they inform. Consequently, we invite users to make themselves known, to advise us of the use they do, or might, make of these statistics, and what their wishes are in terms of engagement. Feedback on this notice and enquiries about these statistics are also welcome.

Definitions

Household income of the principal farmer Principal farmer’s household income has the following components: (1) The share of farm business income (FBI) (including income from farm diversification) attributable to the principal farmer and their spouse. (2) Principal farmer’s and spouse’s off farm income from employment and self-employment, investment income, pensions and social payments. (3) Income of other household members. The share of farm business income and all employment and self-employment incomes, investment income and pension income are recorded as gross of income tax payments and National Insurance contributions, but after pension contributions. In addition, no deduction is made for council tax.

Household A household is defined as a single person or group of people living at the same address as their only or main residence, who either share one meal a day together or share the living accommodation. A household must contain at least one person who received drawings from the farm business or who took a share of the profit from the business.

Drawings Drawings represent the monies which the farmer takes from the business for their own personal use. The percentage of total drawings going to each household is collected and is used to calculate the total share of farm business income for the principal farmer’s household.

Mean Mean household income of individuals is the ”average”, found by adding up the weighted household incomes for each individual farm in the population for analysis and dividing the result by the corresponding weighted number of farms. In this report average is usually taken to refer to the mean.

Percentiles These are the values which divide the population for analysis, when ranked by an output variable (e.g. household income or net worth), into 100 equal-sized groups. E.g. twenty five per cent of the population would have incomes below the 25th percentile.

Median Median household income divides the population, when ranked by an output variable, into two equal sized groups. The median of the whole population is the same as the 50th percentile. The term is also used for the midpoint of the subsets of the income distribution

Quartiles Quartiles are values which divide the population, when ranked by an output variable, into four equal-sized groups. The lowest quartile is the same as the 25th percentile. The divisions of a population split by quartiles are referred to as quarters in this publication.

Quintiles Quintiles are values which divide the population, when ranked by an output variable, into five equal-sized groups. The divisions of a population split by quintiles are referred to as fifths in this publication.

Assets Assets include

About this dataset

Context

The dataset presents the median household incomes over the past decade across various racial categories identified by the U.S. Census Bureau in Troy. 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

• White: In Troy, the median household income for the households where the householder is White increased by $1,900(1.94%), between 2013 and 2023. The median household income, in 2023 inflation-adjusted dollars, was $97,710 in 2013 and $99,610 in 2023.
• Black or African American: In Troy, the median household income for Black or African American households was $12,293 in 2013(2023 inflation-adjusted dollars). However there is no reported data for 2023, indicating a lack of information for this specific year.
• Refer to the research insights for more key observations on American Indian and Alaska Native, Asian, Native Hawaiian and Other Pacific Islander, Some other race and Two or more races (multiracial) households

Content

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:

• White
• Black or African American
• American Indian and Alaska Native
• Asian
• Native Hawaiian and Other Pacific Islander
• Some other race
• Two or more races (multiracial)

Variables / Data Columns

• Race of the head of household: This column presents the self-identified race of the household head, encompassing all relevant racial categories (excluding ethnicity) applicable in Troy.
• 2010: 2010 median household income
• 2011: 2011 median household income
• 2012: 2012 median household income
• 2013: 2013 median household income
• 2014: 2014 median household income
• 2015: 2015 median household income
• 2016: 2016 median household income
• 2017: 2017 median household income
• 2018: 2018 median household income
• 2019: 2019 median household income
• 2020: 2020 median household income
• 2021: 2021 median household income
• 2022: 2022 median household income
• 2023: 2023 median household income
• Please note: All incomes have been adjusted for inflation and are presented in 2023-inflation-adjusted dollars.

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 Troy median household income by race. You can refer the same here