Between 1914 and 1969, weekly wages in manufacturing industries in the United States grew by a factor of 12. In the first half of the century, the most significant periods of increase came during the World Wars, as manufacturing industries were at the core of the war effort. However, wages then fell sharply after both World Wars, due to post-war recessions and oversaturation of the job market as soldiers returned home. Interwar period Wage growth during the interwar period was often stagnant, despite the significant economic growth during the Roarin' 20s, and manufacturing wages remained steady at around 24 dollars from 1923 to 1929. This was, again, due to oversaturation of the job market, as employment in the agricultural sector declined due to mechanization and many rural workers flocked to industrial cities in search of employment. The Great Depression then saw the largest and most prolonged period of decline in manufacturing wages. From September 1929 to March 1933, weekly wages fell from 24 dollars to below 15 dollars, and it would take another four years for them to return to pre-Depression levels. Postwar prosperity After the 1945 Recession, the decades that followed the Second World War then saw consistent growth in manufacturing wages in almost every year, as the U.S. cemented itself as the foremost economic power in the world. This period is sometimes referred to as the Golden Age of Capitalism, and the U.S. strengthened its economic presence in Western Europe and other OECD countries, while expanding its political and military presence across Asia. Manufacturing and exports played a major role in the U.S.' economic growth in this period, and wages grew from roughly 40 dollars per week in 1945 to more than 120 dollars by the late 1960s.

Wages in Australia increased to 1510.90 AUD/Week in the fourth quarter of 2024 from 1480.90 AUD/Week in the second quarter of 2024. This dataset provides - Australia Average Weekly Wages - actual values, historical data, forecast, chart, statistics, economic calendar and news.

Graph and download economic data for Mean Family Income in the United States (MAFAINUSA646N) from 1953 to 2023 about family, average, income, and USA.

This table contains data on the remuneration of employees, the labour costs and the volume of labour of workers employed by companies and institutions established in the Netherlands. The remuneration of employees is subdivided according to wages and social contributions borne by employers. Wage costs are the total of wages, employers’ social contributions and final taxes reduced by wage cost subsidies. The labour volume of workers is given in average number of jobs (divided by full-time/part-time jobs and sex), average number of years of employment, hours worked, hours paid and agreed hours years. In addition to the original figures, the table shows the remuneration of employees, wages and labour costs in relation to the average number of years of employment and hours worked.

Data available from 1969 to 2016.

Status of the figures: The data from 1969 to 2015 are final. The 2016 data are provisional. As this table has been discontinued, the data will no longer be finalised.

Changes as of 22 June 2018 None, this table has been discontinued. The Central Bureau of Statistics has recently carried out a revision of the national accounts. New statistical sources and estimation methods are used. This table with data for revision has been replaced by table Remuneration and labour volume of workers; industry, national accounts. For additional information see paragraph 3.

When will there be new figures? No longer applicable.

This table contains 22 series, with data for years 1951 - 1969 (not all combinations necessarily have data for all years). This table contains data described by the following dimensions (Not all combinations are available): Geography (11 items: Canada; Newfoundland and Labrador; Prince Edward Island; Nova Scotia ...), Seasonal adjustment (2 items: Unadjusted; Seasonally adjusted ...), Wages and salaries (1 items: Total wages and salaries ...).

Table SA27 presents estimates of wage and salary employment in Standard Industrial Classification (SIC) two-digit detail. Employment is measured as the average annual number of jobs, full-time plus part-time, by place of work; each wage and salary job that a person holds is counted at full weight. (For estimates of employment that include self-employment, see Table SA25.) The State estimates of wage and salary employment correspond very closely to the estimates of wages and salaries presented in Table SA07 The source data for BEA's wage and salary employment estimates are mainly from the ES-202 series of the Bureau of Labor Statistics. The ES-202 series provides monthly employment and quarterly wages for each State (and county) in SIC four-digit detail. BEA restricts its estimates of wage and salary employment to the SIC Division ("one-digit") and two-digit levels and suppresses these estimates in many individual cases in order to preclude the disclosure of information about individual employers.

Wage Rate Index: Annual: Fisheries data was reported at 8,972.000 1969-1970=100 in 2018. This records an increase from the previous number of 8,421.000 1969-1970=100 for 2017. Wage Rate Index: Annual: Fisheries data is updated yearly, averaging 1,928.000 1969-1970=100 from Jun 1975 (Median) to 2018, with 44 observations. The data reached an all-time high of 8,972.000 1969-1970=100 in 2018 and a record low of 197.000 1969-1970=100 in 1975. Wage Rate Index: Annual: Fisheries data remains active status in CEIC and is reported by Bangladesh Bureau of Statistics. The data is categorized under Global Database’s Bangladesh – Table BD.G023: Wage Rate Index: 1969-1970=100.

Bangladesh Wage Rate Index: Annual data was reported at 11,281.000 1969-1970=100 in 2018. This records an increase from the previous number of 10,597.000 1969-1970=100 for 2017. Bangladesh Wage Rate Index: Annual data is updated yearly, averaging 1,945.000 1969-1970=100 from Jun 1975 (Median) to 2018, with 44 observations. The data reached an all-time high of 11,281.000 1969-1970=100 in 2018 and a record low of 221.000 1969-1970=100 in 1975. Bangladesh Wage Rate Index: Annual data remains active status in CEIC and is reported by Bangladesh Bureau of Statistics. The data is categorized under Global Database’s Bangladesh – Table BD.G023: Wage Rate Index: 1969-1970=100. Rebased from 1969-70=100 to 2010-11=100 Replacement series ID: 373831497

Graph and download economic data for Per Capita Personal Income in Franklin County, NC (PCPI37069) from 1969 to 2023 about Franklin County, NC; Raleigh; personal income; NC; per capita; personal; income; and USA.

Bangladesh Wage Rate Index: Annual: Agriculture data was reported at 11,963.000 1969-1970=100 in 2018. This records an increase from the previous number of 11,243.000 1969-1970=100 for 2017. Bangladesh Wage Rate Index: Annual: Agriculture data is updated yearly, averaging 1,771.000 1969-1970=100 from Jun 1975 (Median) to 2018, with 44 observations. The data reached an all-time high of 11,963.000 1969-1970=100 in 2018 and a record low of 261.000 1969-1970=100 in 1975. Bangladesh Wage Rate Index: Annual: Agriculture data remains active status in CEIC and is reported by Bangladesh Bureau of Statistics. The data is categorized under Global Database’s Bangladesh – Table BD.G023: Wage Rate Index: 1969-1970=100.

Graph and download economic data for Per Capita Personal Income in Austin-Round Rock, TX (MSA) (AUST448PCPI) from 1969 to 2023 about Austin, personal income, per capita, personal, TX, income, and USA.

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

Key observations

• Employment patterns: Within Martinsville city, among individuals aged 15 years and older with income, there were 4,303 men and 4,926 women in the workforce. Among them, 1,939 men were engaged in full-time, year-round employment, while 1,969 women were in full-time, year-round roles.
• Annual income under $24,999: Of the male population working full-time, 13.98% fell within the income range of under $24,999, while 17.67% of the female population working full-time was represented in the same income bracket.
• Annual income above $100,000: 14.39% of men in full-time roles earned incomes exceeding $100,000, while 6.50% 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 Martinsville city median household income by race. You can refer the same here

Graph and download economic data for Per Capita Personal Income in Los Angeles County, CA (PCPI06037) from 1969 to 2023 about Los Angeles County, CA; Los Angeles; personal income; per capita; CA; personal; income; and USA.

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

Key observations

• Employment patterns: Within Falcon Heights, among individuals aged 15 years and older with income, there were 1,969 men and 2,115 women in the workforce. Among them, 933 men were engaged in full-time, year-round employment, while 706 women were in full-time, year-round roles.
• Annual income under $24,999: Of the male population working full-time, 7.07% fell within the income range of under $24,999, while 3.26% of the female population working full-time was represented in the same income bracket.
• Annual income above $100,000: 30.33% of men in full-time roles earned incomes exceeding $100,000, while 34.56% 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 Falcon Heights median household income by race. You can refer the same here

Bangladesh Wage Rate Index: Rajshahi data was reported at 12,437.340 1969-1970=100 in Dec 2018. This records a decrease from the previous number of 12,475.880 1969-1970=100 for Nov 2018. Bangladesh Wage Rate Index: Rajshahi data is updated monthly, averaging 5,195.580 1969-1970=100 from Dec 1998 (Median) to Dec 2018, with 240 observations. The data reached an all-time high of 12,475.880 1969-1970=100 in Nov 2018 and a record low of 2,304.000 1969-1970=100 in Dec 1998. Bangladesh Wage Rate Index: Rajshahi data remains active status in CEIC and is reported by Bangladesh Bureau of Statistics . The data is categorized under Global Database’s Bangladesh – Table BD.G021: Wage Rate Index: 1969-1970=100.

Graph and download economic data for Average Weekly Earnings, Manufacturing, Total for United States (M08261USM052NNBR) from Jun 1914 to Mar 1969 about earnings, manufacturing, and USA.

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

Key observations

• Employment patterns: Within Frankenmuth, among individuals aged 15 years and older with income, there were 1,969 men and 2,130 women in the workforce. Among them, 933 men were engaged in full-time, year-round employment, while 685 women were in full-time, year-round roles.
• Annual income under $24,999: Of the male population working full-time, 6.54% fell within the income range of under $24,999, while 2.04% of the female population working full-time was represented in the same income bracket.
• Annual income above $100,000: 30.01% of men in full-time roles earned incomes exceeding $100,000, while 21.46% 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 Frankenmuth median household income by race. You can refer the same here

Graph and download economic data for Per Capita Personal Income in Madison, WI (MSA) (MADI555PCPI) from 1969 to 2023 about Madison, WI, personal income, per capita, personal, income, and USA.

Graph and download economic data for Per Capita Personal Income in San Diego County, CA (PCPI06073) from 1969 to 2023 about San Diego County, CA; San Diego; personal income; per capita; CA; personal; income; and USA.

Table SA25 contains estimates of employment in Standard Industrial Classification (SIC) two-digit detail. Employment is measured as the average annual number of jobs, full-time plus part-time; each job that a person holds is counted at full weight. The estimates are largely by place of work. The estimates are organized both by type--wage and salary employment and self-employment--and by industry. The series by industry is for the combination of the two types of employment. These employment estimates correspond closely to the earnings estimates presented in Table SA05; however, the earnings estimates include the income of limited partnerships and of tax-exempt cooperatives, for which there are no corresponding employment estimates. (For wage and salary employment by industry, see Table SA27; for self-employment by industry, subtract the Table SA27 data from the Table SA25 data.) The source data for BEA's wage and salary employment estimates are mainly from the ES-202 series of the Bureau of Labor Statistics. The ES-202 series provides monthly employment and quarterly wages for each State (and county) in SIC four-digit detail. BEA restricts its estimates of wage and salary employment to the SIC Division ("one-digit") and two-digit levels because self-employment is estimated-- based mainly on data tabulated from individual and partnership Federal individual income tax returns-- at that level. The estimates are suppressed in many individual cases in order to preclude the disclosure of information about individual employers.