Labor Force Participation Rate in the United States decreased to 62.40 percent in May from 62.60 percent in April of 2025. This dataset provides the latest reported value for - United States Labor Force Participation Rate - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

Labor force participation rate is a measure of the active workforce. It is the total number of those employed or actively seeking employment divided by the all working age population, however, from the U.S. Census Bureau’s American Community Survey (ACS), the universe for the working age population considered varies. For participation rates by sex, the population used is 20 to 64 years old. For race and ethnic groupings, the age range is 16 and older. As a result of the narrower age range the rates by sex are higher than those by race.

Labor Force Participation Rate in India remained unchanged at 50.40 percent in the fourth quarter of 2024 from 50.40 percent in the third quarter of 2024. This dataset provides - India Labor Force Participation Rate - actual values, historical data, forecast, chart, statistics, economic calendar and news.

This dataset contains information about the unemployment rate in Austin (SD23 measure EOA.A.1). Texas Workforce Comission provides Texas Labor Market Information for Austin, the Austin Round-Rock MSA, Texas, and the United States. This dataset includes the average number of people in the civilian labor force, the employment count, the unemployment count, and the unemployment rate for Austin, the Austin Round-Rock MSA, Texas, and the United States. The unemployment rate can be useful in understanding economic and workforce trends in Austin over time. View more details and insights related to this dataset on the story page: https://data.austintexas.gov/stories/s/Percentage-Unemployment-Rate/ehhu-nafn/

2020 data excluded because the U.S. Census Bureau did not release 2020 ACS 1-year estimates due to COVID-19. Some racial and ethnic categories are suppressed to avoid misleading estimates when the relative standard error exceeds 30%.

Data Source: American Community Survey (ACS) 1-Year Estimates

Why This Matters

According to the U.S. Bureau of Labor Statistics, the labor force participation rate is an important measure of the health of the labor market, which represents the relative amount of labor resources available for the production of goods and services.

Changes in overall labor force participation reflect demographic, policy, and employer changes, whereas gaps in labor force participation between different segments of the working-age population reveal barriers to participation.

Black, Indigenous, and people of color participate in the labor market at lower rates than white people. These inequities reflect policies and practices, such as employment discrimination, racial segregation, and mass incarceration, among other factors.

The District's Response

Investing in targeted programs that provide pathways to higher wages and jobs, such as the Advanced Technical Centers (ATC), the DC Infrastructure Academy, and Career MAP, which aim to tackle the systemic barriers that keep people out of the labor force.

Administering federal and local safety net programs such as TANF For District Families, SNAP, unemployment insurance, and Medicaid that provide temporary cash and health benefits to address economic hardship.

Partners with the Department of Employment Services in building youth from the ground up through its various programs and services, including mentorship, counseling justice system services, job training development, and employment.

1990 to present (approximate 2 month lag) Virginia Labor Force and Unemployment estimates by Month by County.

Special data considerations: Period values of "M01-M12" represent Months of Year; "M13" is the Annual Average.

U.S. Bureau of Labor Statistics; Local Area Unemployment Statistics, table la.data.54.Virginia Data accessed from the Bureau of Labor Statistics public database LABSTAT (https://download.bls.gov/pub/time.series/la/)

Supporting documentation can be found on the U.S. Bureau of Labor Statistics website under Local Area Unemployment Statistics, Handbook of Methods (https://www.bls.gov/opub/hom/lau/home.htm)

Survey Description: Labor force and unemployment estimates for States and local areas are developed by State workforce agencies to measure local labor market conditions under a Federal-State cooperative program. The Department of Labor develops the concepts, definitions, and technical procedures which are used by State agencies for preparation of labor force and unemployment estimates.

These estimates are derived from a variety of sources, including the Current Population Survey, the Current Employment Statistics survey, the Quarterly Census of Employment and Wages, various programs at the Census Bureau, and unemployment insurance claims data from the State workforce agencies.

To establish uniform labor force concepts and definitions in all States and areas consistent with those used for the U.S. as a whole, monthly national estimates of employment and unemployment from the Current Population Survey are used as controls (benchmarks) for the State labor force statistics.

Summary Data Available: Monthly labor force and unemployment series are available for approximately 7,500 geographic areas, including cities over 25,000 population, counties, metropolitan areas, States, and other areas.

For each area, the following measures are presented by place of residence:

• Total civilian labor force,
• Total number of people employed,
• Total number of people unemployed, and
• Unemployment rate

Data Characteristics: Rates are expressed as percents with one decimal place. Levels are measured as individual persons (not thousands) and are stored with no decimal places.

ACS 1-year estimates are based on data collected over one calendar year, offering more current information but with a higher margin of error. ACS 5-year estimates combine five years of data, providing more reliable information but less current. Both are based on probability samples. Some racial and ethnic categories are suppressed to avoid misleading estimates when the relative standard error exceeds 30%.

Data Source: American Community Survey (ACS) 1- & 5-Year Estimates

Why This Matters

According to the U.S. Bureau of Labor Statistics, the labor force participation rate is an important measure of the health of the labor market, which represents the relative amount of labor resources available for the production of goods and services.

Changes in overall labor force participation reflect demographic, policy, and employer changes, whereas gaps in labor force participation between different segments of the working-age population reveal barriers to participation.

Black, Indigenous, and people of color participate in the labor market at lower rates than white people. These inequities reflect policies and practices, such as employment discrimination, racial segregation, and mass incarceration, among other factors.

The District's Response

Investing in targeted programs that provide pathways to higher wages and jobs, such as the Advanced Technical Centers (ATC), the DC Infrastructure Academy, and Career MAP, which aim to tackle the systemic barriers that keep people out of the labor force.

Administering federal and local safety net programs such as TANF For District Families, SNAP, unemployment insurance, and Medicaid that provide temporary cash and health benefits to address economic hardship.

Partners with the Department of Employment Services in building youth from the ground up through its various programs and services, including mentorship, counseling justice system services, job training development, and employment.

This Alberta Official Statistic compares the labour force participation rates for both males and females in Alberta. The labour force participation rate is a measure of the percentage of the working age population (15 years or older) who are employed, or unemployed and looking for work.

This dataset contains unemployment rates for the U.S. (1948 - Present) and California (1976 - Present). The unemployment rate represents the number of unemployed as a percentage of the labor force. Labor force data are restricted to people 16 years of age and older, who currently reside in 1 of the 50 states or the District of Columbia, who do not reside in institutions (e.g., penal and mental facilities, homes for the aged), and who are not on active duty in the Armed Forces. This rate is also defined as the U-3 measure of labor underutilization.

Analysis of ‘Strategic Measure_Percentage Unemployment Rate’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://catalog.data.gov/dataset/fb383985-5de9-4f55-ba17-581333f28ba9 on 26 January 2022.

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

This dataset contains information about the unemployment rate in Austin (SD23 measure EOA.A.1). Texas Workforce Comission provides Texas Labor Market Information for Austin, the Austin Round-Rock MSA, Texas, and the United States.

This dataset includes the average number of people in the civilian labor force, the employment count, the unemployment count, and the unemployment rate for Austin, the Austin Round-Rock MSA, Texas, and the United States. The unemployment rate can be useful in understanding economic and workforce trends in Austin over time.

View more details and insights related to this dataset on the story page: https://data.austintexas.gov/stories/s/Percentage-Unemployment-Rate/ehhu-nafn/

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

OECD Data Filters: REF_AREA: USA MEASURE: LF_WAP UNIT_MEASURE: PT_WAP_SUB TRANSFORMATION: _Z ADJUSTMENT: Y SEX: M AGE: Y25T54 ACTIVITY: _Z FREQ: M

All OECD data should be cited as follows: OECD (year), (dataset name), (data source) DOI or https://data-explorer.oecd.org/ (https://data-explorer.oecd.org/). (accessed on (date)).

Labor Force Participation Rate in Canada remained unchanged at 65.30 percent in May. This dataset provides the latest reported value for - Canada Labor Force Participation Rate - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

OECD Data Filters: REF_AREA: USA MEASURE: LF_WAP UNIT_MEASURE: PT_WAP_SUB TRANSFORMATION: _Z ADJUSTMENT: Y SEX: F AGE: Y25T54 ACTIVITY: _Z FREQ: M

All OECD data should be cited as follows: OECD (year), (dataset name), (data source) DOI or https://data-explorer.oecd.org/ (https://data-explorer.oecd.org/). (accessed on (date)).

Analysis of ‘Unemployment in India’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://www.kaggle.com/gokulrajkmv/unemployment-in-india on 28 January 2022.

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

Context

The story behind this datasets is how lock-down affects employment opportunities and how the unemployment rate increases during the Covid-19.

Content

This dataset contains the unemployment rate of all the states in India

Region = states in India Date = date which the unemployment rate observed Frequency = measuring frequency (Monthly)
Estimated Unemployment Rate (%) = percentage of people unemployed in each States of India Estimated Employed = percentage of people employed Estimated Labour Participation Rate (%) = labour force participation rate by dividing the number of people actively participating in the labour force by the total number of people eligible to participate in the labor force force

Acknowledgements

I wouldn't be here without the help of my friends. I owe you thanks !!

Inspiration

questions? 1. How Covid-19 affects the employment 2. how far the unemployment rate will go

source of datasets https://unemploymentinindia.cmie.com/

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

****Dataset Overview**** This dataset contains historical macroeconomic data, featuring key economic indicators in the United States. It includes important metrics such as the Consumer Price Index (CPI), Retail Sales, Unemployment Rate, Industrial Production, Money Supply (M2), and more. The dataset spans from 1993 to the present and includes monthly data on various economic indicators, processed to show their rate of change (either percentage or absolute difference, depending on the indicator).

provenance

The data in this dataset is sourced from the Federal Reserve Economic Data (FRED) database, hosted by the Federal Reserve Bank of St. Louis. FRED provides access to a wide range of economic data, including key macroeconomic indicators for the United States. My work involved calculating the rate of change (ROC) for each indicator and reorganizing the data into a more usable format for analysis. For more information and access to the full database, visit FRED's website.

Purpose and Use for the Kaggle Community:

This dataset is a valuable resource for data scientists, economists, and analysts interested in understanding macroeconomic trends, performing time series analysis, or building predictive models. With the rate of change included, users can quickly assess the growth or contraction in these indicators month-over-month. This dataset can be used for:

• Exploratory Data Analysis (EDA): Understanding historical economic trends. -Time Series Forecasting: Building models to predict future economic conditions. -Macroeconomic Analysis: Analyzing the relationship between various economic indicators. -Machine Learning Projects: Using the data as features to predict financial or economic outcomes. -By utilizing this dataset, users can perform in-depth analysis on the impact of macroeconomic changes, compare the historical performance of various indicators, and experiment with different time series forecasting techniques.

****Column Descriptions****

Year: The year of the observation.

Month: The month of the observation (1-12).

Industrial Production: Monthly data on the total output of US factories, mines, and utilities.

Manufacturers' New Orders: Durable Goods: Measures the value of new orders placed with manufacturers for durable goods, indicating future production activity.

Consumer Price Index (CPIAUCSL): A measure of the average change over time in the prices paid by urban consumers for a market basket of consumer goods and services.

Unemployment Rate: The percentage of the total labor force that is unemployed but actively seeking employment.

Retail Sales: The total receipts of retail stores, indicating consumer spending and economic activity.

Producer Price Index: Measures the average change over time in the selling prices received by domestic producers for their output.

Personal Consumption Expenditures (PCE): A measure of the prices paid by consumers for goods and services, used in calculating inflation.

National Home Price Index: A measure of changes in residential real estate prices across the country.

All Employees, Total Nonfarm: The number of nonfarm payroll employees, an important indicator of the labor market.

Labor Force Participation Rate: The percentage of the working-age population that is either employed or actively looking for work.

Federal Funds Effective Rate: The interest rate at which depository institutions lend reserve balances to other depository institutions overnight.

Building Permits: The number of building permits issued for residential and non-residential buildings, a leading indicator of construction activity.

Money Supply (M2): The total money supply, including cash, checking deposits, and easily convertible near money.

Personal Income: The total income received by individuals from all sources, including wages, investments, and government transfers.

Trade Balance: The difference between a country's imports and exports, indicating the net trade flow.

Consumer Sentiment: The index reflecting consumer sentiment and expectations for the future economic outlook.

Consumer Confidence: A measure of how optimistic or pessimistic consumers are regarding their expected financial situation and the economy.

Notes on Interest Rates Please note that for the Federal Funds Effective Rate (FEDFUNDS), the dataset includes the absolute change in basis points (bps), not the rate of change. This means that the dataset reflects the direct change in the interest rate rather than the percentage change month-over-month. The change is represented in basis points, where 1 basis point equals 0.01%.

Abstract

THE CLEANED AND HARMONIZED VERSION OF THE SURVEY DATA PRODUCED AND PUBLISHED BY THE ECONOMIC RESEARCH FORUM REPRESENTS 100% OF THE ORIGINAL SURVEY DATA COLLECTED BY THE DEPARTMENT OF STATISTICS OF THE HASHEMITE KINGDOM OF JORDAN

The Department of Statistics (DOS) carried out four rounds of the 2016 Employment and Unemployment Survey (EUS). The survey rounds covered a sample of about fourty nine thousand households Nation-wide. The sampled households were selected using a stratified multi-stage cluster sampling design.

It is worthy to mention that the DOS employed new technology in data collection and data processing. Data was collected using electronic questionnaire instead of a hard copy, namely a hand held device (PDA).

The survey main objectives are: - To identify the demographic, social and economic characteristics of the population and manpower. - To identify the occupational structure and economic activity of the employed persons, as well as their employment status. - To identify the reasons behind the desire of the employed persons to search for a new or additional job. - To measure the economic activity participation rates (the number of economically active population divided by the population of 15+ years old). - To identify the different characteristics of the unemployed persons. - To measure unemployment rates (the number of unemployed persons divided by the number of economically active population of 15+ years old) according to the various characteristics of the unemployed, and the changes that might take place in this regard. - To identify the most important ways and means used by the unemployed persons to get a job, in addition to measuring durations of unemployment for such persons. - To identify the changes overtime that might take place regarding the above-mentioned variables.

The raw survey data provided by the Statistical Agency were cleaned and harmonized by the Economic Research Forum, in the context of a major project that started in 2009. During which extensive efforts have been exerted to acquire, clean, harmonize, preserve and disseminate micro data of existing labor force surveys in several Arab countries.

Geographic coverage

Covering a sample representative on the national level (Kingdom), governorates, and the three Regions (Central, North and South).

Analysis unit

1- Household/family. 2- Individual/person.

Universe

The survey covered a national sample of households and all individuals permanently residing in surveyed households.

Kind of data

Sample survey data [ssd]

Sampling procedure

THE CLEANED AND HARMONIZED VERSION OF THE SURVEY DATA PRODUCED AND PUBLISHED BY THE ECONOMIC RESEARCH FORUM REPRESENTS 100% OF THE ORIGINAL SURVEY DATA COLLECTED BY THE DEPARTMENT OF STATISTICS OF THE HASHEMITE KINGDOM OF JORDAN

Mode of data collection

Computer Assisted Personal Interview [capi]

Cleaning operations

----> Raw Data

A tabulation results plan has been set based on the previous Employment and Unemployment Surveys while the required programs were prepared and tested. When all prior data processing steps were completed, the actual survey results were tabulated using an ORACLE package. The tabulations were then thoroughly checked for consistency of data. The final report was then prepared, containing detailed tabulations as well as the methodology of the survey.

----> Harmonized Data

• The SPSS package is used to clean and harmonize the datasets.
• The harmonization process starts with a cleaning process for all raw data files received from the Statistical Agency.
• All cleaned data files are then merged to produce one data file on the individual level containing all variables subject to harmonization.
• A country-specific program is generated for each dataset to generate/ compute/ recode/ rename/ format/ label harmonized variables.
• A post-harmonization cleaning process is then conducted on the data.
• Harmonized data is saved on the household as well as the individual level, in SPSS and then converted to STATA, to be disseminated.

Labor Force Participation Rate in Sri Lanka increased to 47.70 percent in the fourth quarter of 2024 from 46.90 percent in the third quarter of 2024. This dataset provides - Sri Lanka Labor Force Participation Rate - actual values, historical data, forecast, chart, statistics, economic calendar and news.

VITAL SIGNS INDICATOR Unemployment (EC3)

FULL MEASURE NAME Unemployment rate by residential location

LAST UPDATED July 2019

DESCRIPTION Unemployment refers to the share of the labor force – by place of residence – that is not currently employed full-time or part-time. The unemployment rate reflects the strength of the overall employment market.

DATA SOURCE California Employment Development Department: Historical Unemployment Rates 1990-2018 https://data.edd.ca.gov/Labor-Force-and-Unemployment-Rates/Local-Area-Unemployment-Statistics-LAUS-Annual-Ave/7jbb-3rb8

CONTACT INFORMATION vitalsigns.info@bayareametro.gov

METHODOLOGY NOTES (across all datasets for this indicator) Unemployment rates produced by EDD for the region and county levels are not adjusted for seasonality (as they reflect annual data) and are final data (i.e., not preliminary). Unemployment rates produced by BLS for the metro regions are adjusted for seasonality; they reflect the primary MSA for the named region, except for the San Francisco Bay Area which uses the nine-county region. The unemployment rate is calculated based on the number of unemployed persons divided by the total labor force. Note that the unemployment rate can decline or increase as a result of changes in either variable.

Data of the US Employment and Unemployment rates since 1940. The data is obtained from the USA Bureau of Labor Statistics and includes the employment status of the civilian noninstitutional population from 1940 to the present day. The numbers in the dataset are measured in thousands and provide important information on the labor market in the US over several decades. This dataset can be used by researchers, policymakers, and analysts to understand the trends and fluctuations in the US labor market, as well as to develop strategies for improving employment and reducing unemployment rates.

The infra-annual labour statistics dataset contains predominantly monthly and quarterly labour statistics, and associated statistical methodological information, for the OECD member countries and selected other economies. It covers countries that compile labour statistics from sample household surveys on a monthly or quarterly basis. It is widely accepted that household surveys are the best source for labour market key statistics. In such surveys, information is collected from people living in households through a representative sample and the surveys are based on standard methodology and procedures used internationally.

The subjects available cover: working age population by age; active and inactive labour force by age; employment by economic activity, by working time and by status; and, unemployment (including monthly unemployment) by age and by duration. Data is expressed in levels (thousands of persons) or rates (e.g. employment rate) where applicable. The relationship between these several measures are as follow:

• Working age population = Labour force population + Inactive population

• Labour force population = Employed population + Unemployed population

• Employment rate = Employed population / Working age population

• Unemployment rate = Unemployed population / Labour force population

• Labour force participation rate = Labour force population / Working age population

The infra-annual labour statistics compiled for all OECD member countries, are drawn from Labour Force Surveys based on definition provided by the 19th Conference of Labour Statisticians in 2013. The uniform application of these definitions across all OECD member countries results in estimates that are internationally comparable.