Dataset Overview

This dataset provides a comprehensive overview of the U.S. workforce and their median weekly earnings over time, spanning from 2009 to 2021. The data is broken down by gender and includes both current and constant dollar values, providing insight into the economic trends affecting different segments of the workforce.

Columns Description

• Year: The year of the data point.
• Quarter: The quarter of the year (1-4) when the data was collected.
• Number of workers (in thousands) - Total: The total number of workers in the U.S. workforce, reported in thousands.
• Number of workers (in thousands) - Men: The number of male workers in the U.S. workforce, reported in thousands.
• Number of workers (in thousands) - Women: The number of female workers in the U.S. workforce, reported in thousands.
• Median weekly earnings (in current dollars) - Total: The median weekly earnings of all workers in the U.S. workforce, reported in current dollars.
• Median weekly earnings (in current dollars) - Men: The median weekly earnings of male workers in the U.S. workforce, reported in current dollars.
• Median weekly earnings (in current dollars) - Women: The median weekly earnings of female workers in the U.S. workforce, reported in current dollars.
• Median weekly earnings (in constant dollars) - Total: The median weekly earnings of all workers in the U.S. workforce, adjusted for inflation and reported in constant dollars.
• Median weekly earnings (in constant dollars) - Men: The median weekly earnings of male workers in the U.S. workforce, adjusted for inflation and reported in constant dollars.
• Median weekly earnings (in constant dollars) - Women: The median weekly earnings of female workers in the U.S. workforce, adjusted for inflation and reported in constant dollars.

Dataset Summary

This dataset contains 37 entries, each representing a quarter from Q4 2009 to Q4 2021. It offers a valuable perspective on workforce trends and wage disparities between men and women over time, adjusted for inflation. The data can be used for economic research, gender studies, and trend analysis.

Potential Use Cases

1. Economic Analysis: Study the trends in workforce participation and earnings over time.
2. Gender Wage Gap Research: Analyze the wage disparities between men and women.
3. Inflation Impact Study: Assess the impact of inflation on workers' earnings over time.
4. Quarterly Workforce Insights: Gain insights into how the workforce composition and earnings change quarter by quarter.

Acknowledgements

This dataset is compiled from public sources, aiming to provide a clear picture of the U.S. workforce and wage trends over the years.

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Key Table Information.Table Title.Median Earnings in the Past 12 Months by Group Quarters Type (5 Types) by Sex.Table ID.ACSDT1Y2024.B26219.Survey/Program.American Community Survey.Year.2024.Dataset.ACS 1-Year Estimates Detailed Tables.Source.U.S. Census Bureau, 2024 American Community Survey, 1-Year Estimates.Dataset Universe.The dataset universe of the American Community Survey (ACS) is the U.S. resident population and housing. For more information about ACS residence rules, see the ACS Design and Methodology Report. Note that each table describes the specific universe of interest for that set of estimates..Methodology.Unit(s) of Observation.American Community Survey (ACS) data are collected from individuals living in housing units and group quarters, and about housing units whether occupied or vacant. For more information about ACS sampling and data collection, see the ACS Design and Methodology Report..Geography Coverage.ACS data generally reflect the geographic boundaries of legal and statistical areas as of January 1 of the estimate year. For more information, see Geography Boundaries by Year.Estimates of urban and rural populations, housing units, and characteristics reflect boundaries of urban areas defined based on 2020 Census data. As a result, data for urban and rural areas from the ACS do not necessarily reflect the results of ongoing urbanization..Sampling.The ACS consists of two separate samples: housing unit addresses and group quarters facilities. Independent housing unit address samples are selected for each county or county-equivalent in the U.S. and Puerto Rico, with sampling rates depending on a measure of size for the area. For more information on sampling in the ACS, see the Accuracy of the Data document..Confidentiality.The Census Bureau has modified or suppressed some estimates in ACS data products to protect respondents' confidentiality. Title 13 United States Code, Section 9, prohibits the Census Bureau from publishing results in which an individual's data can be identified. For more information on confidentiality protection in the ACS, see the Accuracy of the Data document..Technical Documentation/Methodology.Information about the American Community Survey (ACS) can be found on the ACS website. Supporting documentation including code lists, subject definitions, data accuracy, and statistical testing, and a full list of ACS tables and table shells (without estimates) can be found on the Technical Documentation section of the ACS website.Sample size and data quality measures (including coverage rates, allocation rates, and response rates) can be found on the American Community Survey website in the Methodology section.Data are based on a sample and are subject to sampling variability. The degree of uncertainty for an estimate arising from sampling variability is represented through the use of a margin of error. The value shown here is the 90 percent margin of error. The margin of error can be interpreted roughly as providing a 90 percent probability that the interval defined by the estimate minus the margin of error and the estimate plus the margin of error (the lower and upper confidence bounds) contains the true value. In addition to sampling variability, the ACS estimates are subject to nonsampling error (for a discussion of nonsampling variability, see ACS Technical Documentation). The effect of nonsampling error is not represented in these tables.Users must consider potential differences in geographic boundaries, questionnaire content or coding, or other methodological issues when comparing ACS data from different years. Statistically significant differences shown in ACS Comparison Profiles, or in data users' own analysis, may be the result of these differences and thus might not necessarily reflect changes to the social, economic, housing, or demographic characteristics being compared. For more information, see Comparing ACS Data..Weights.ACS estimates are obtained from a raking ratio estimation procedure that results in the assignment of two sets of weights: a weight to each sample person record and a weight to each sample housing unit record. Estimates of person characteristics are based on the person weight. Estimates of family, household, and housing unit characteristics are based on the housing unit weight. For any given geographic area, a characteristic total is estimated by summing the weights assigned to the persons, households, families or housing units possessing the characteristic in the geographic area. For more information on weighting and estimation in the ACS, see the Accuracy of the Data document.Although the American Community Survey (ACS) produces population, demographic and housing unit estimates, the decennial census is the official source of population totals for April 1st of each decennial year. In between censuses, the Census Bureau's Population Estimates Program produces and disseminates the official estimates of the population for the nation, stat...

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