In the United States, approximately 7.75 million people were unemployed and looking for work in August 2025. The data has not been seasonally adjusted. For comparison, a look at the unemployment rate in EU states shows that the EU average is higher than the U.S. average.

Graph and download economic data for Unemployment Level (UNEMPLOY) from Jan 1948 to Sep 2025 about 16 years +, household survey, unemployment, and USA.

The employment and unemployment indicator shows several data points. The first figure is the number of people in the labor force, which includes the number of people who are either working or looking for work. The second two figures, the number of people who are employed and the number of people who are unemployed, are the two subcategories of the labor force. The unemployment rate is a calculation of the number of people who are in the labor force and unemployed as a percentage of the total number of people in the labor force.

The unemployment rate does not include people who are not employed and not in the labor force. This includes adults who are neither working nor looking for work. For example, full-time students may choose not to seek any employment during their college career, and are thus not considered in the unemployment rate. Stay-at-home parents and other caregivers are also considered outside of the labor force, and therefore outside the scope of the unemployment rate.

The unemployment rate is a key economic indicator, and is illustrative of economic conditions in the county at the individual scale.

There are additional considerations to the unemployment rate. Because it does not count those who are outside the labor force, it can exclude individuals who were looking for a job previously, but have since given up. The impact of this on the overall unemployment rate is difficult to quantify, but it is important to note because it shows that no statistic is perfect.

The unemployment rates for Champaign County, the City of Champaign, and the City of Urbana are extremely similar between 2000 and 2023.

All three areas saw a dramatic increase in the unemployment rate between 2006 and 2009. The unemployment rates for all three areas decreased overall between 2010 and 2019. However, the unemployment rate in all three areas rose sharply in 2020 due to the effects of the COVID-19 pandemic. The unemployment rate in all three areas dropped again in 2021 as pandemic restrictions were removed, and were almost back to 2019 rates in 2022. However, the unemployment rate in all three areas rose slightly from 2022 to 2023.

This data is sourced from the Illinois Department of Employment Security’s Local Area Unemployment Statistics (LAUS), and from the U.S. Bureau of Labor Statistics.

Sources: Illinois Department of Employment Security, Local Area Unemployment Statistics (LAUS); U.S. Bureau of Labor Statistics.

Unemployment Rate in the United States increased to 4.40 percent in September from 4.30 percent in August of 2025. This dataset provides the latest reported value for - United States Unemployment Rate - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

This dataset contains non-seasonally adjusted California Unemployment Rate by age groups, from the Current Population Survey (CPS). The age group ranges are as follows; 16-19 ; 20 - 24; 25 - 34; 35 - 44; 45 - 54; 55 -64; 65+. This data is based on a 12-month moving average.

This dataset is invaluable for data science applications due to its granularity and the historical depth it offers. With detailed monthly data on unemployment rates by age groups, data scientists can perform a myriad of analyses:

• Time Series Analysis: Analyzing trends over time to forecast future unemployment rates or identify cyclic patterns.
• Demographic Analysis: Understanding which age groups are most affected by unemployment and how this changes through economic conditions.
• Geographic Analysis: Although the dataset currently focuses on California, if similar data is available for other regions, comparisons can be made to understand regional economic differences.

The dataset can also be merged with other socioeconomic indicators like GDP, education levels, and industry growth metrics to examine broader economic narratives or policy impacts.

The number of unemployed youth worldwide decreased gradually from 2010 to 2019, but then increased in 2020 as a result of the COVID-19 pandemic. As of 2025, there were an estimated 66.94 million unemployed youths between 15 and 24 years worldwide. Highest youth unemployment globally The countries with the highest rates of youth not in education, employment, or training (NEET) include Niger, Kiribati, Guyana, Somalia, and Afghanistan. While there is geographic diversity in this group, each of these countries is either low-income or low-middle income. Moreover, each has their own set of challenges contributing to high NEET rates. For example, in Afghanistan, this can be attributed to conflict and the 2021 Taliban takeover. In Kiribati and other Pacific Island nations, they face high levels of brain drain to larger economies such as Australia, New Zealand, and the United States. Lowest youth unemployment globally On the contrary, countries with the lowest youth NEET rates include Japan, the Netherlands, Sweden, Iceland, and Malta. Factors such as well-structured vocational training programs and affordable university education contribute to low NEET rates. However, these countries still face their own challenges. For example, one contributing factor to such low NEET rates in Japan is the overall shrinkage of the Japanese population, which is simultaneously aging. While unemployment remains low in the country, it faces the potential crisis of not having enough people to support the labor market.

This map shows which month, out of the 14 current months, has the highest count of unemployed people. The predominance for April 2020 was overwhelmingly the current month with the highest unemployment. However, for May, 1 month prior has the most predominant month. This means that April had highest count of unemployed people and there was a decrease in unemployment for the month of May. The size is the sum of the categories. Explore the map to see how the trend progresses over time. As of March 2021, most areas have a predominance of 9 months prior. This shows a trend of increasing employment. The layer used in this map contains the most current 14 months of unemployment statistics from the U.S. Bureau of Labor Statistics (BLS). The data is offered at the nationwide, state, and county geography levels. Puerto Rico is included. These are not seasonally adjusted values. The layer is updated monthly with the newest unemployment statistics available from BLS. There are attributes in the layer that specify which month is associated to each statistic. The most current month offered by the Bureau of Labor Statistics is usually about 6 weeks behind, see the layer for details.The attributes included for each month are:Unemployment rate (%)Count of unemployed populationCount of employed population in the labor forceCount of people in the labor forceFor more information, visit the data page.

United States Unemployment data was reported at 6,580.000 Person th in Apr 2025. This records a decrease from the previous number of 7,242.000 Person th for Mar 2025. United States Unemployment data is updated monthly, averaging 6,579.500 Person th from Jan 1948 (Median) to Apr 2025, with 928 observations. The data reached an all-time high of 22,504.000 Person th in Apr 2020 and a record low of 1,480.000 Person th in Oct 1952. United States Unemployment data remains active status in CEIC and is reported by U.S. Bureau of Labor Statistics. The data is categorized under Global Database’s United States – Table US.G: Current Population Survey: Unemployment. [COVID-19-IMPACT]

Introduction

The U.S. job market, with its dynamic trends and fluctuating unemployment rates, serves as an important barometer for the nation's economic health. All rates provided in this dataset are seasonally adjusted. Delving into the intricacies of unemployment rates by age and gender helps researchers, policymakers, and analysts uncover underlying patterns and address potential disparities.

Usage Examples

• Economic Research: Study the historical unemployment trends to gauge economic cycles.
• Policy Making: Inform labor market policies and interventions based on age or gender disparities.
• Business Strategy: Companies can analyze job market conditions when considering expansions or contractions.
• Academic Projects: Students and educators can use the dataset for case studies, dissertations, or classroom projects.

Image Source Photo by Ron Lach : https://www.pexels.com/photo/woman-looking-for-jobs-in-newspaper-9832700/

Dataset Contents

This dataset, sourced from the FRED API, provides: - df_sex_unemployment_rates.csv: A breakdown of U.S. unemployment rates based on gender. - df_unemployment_rates.csv: Unemployment rates categorized by various age groups, ranging from young entrants (ages 16-17) to seasoned professionals (55 and above).

Together, these data files offer a comprehensive insight into the nuances of unemployment in the U.S., highlighting potential disparities in the job market across different age groups and between men and women.

Graph and download economic data for Unemployment Rate in Person County, NC (NCPERS5URN) from Jan 1990 to Aug 2025 about Person County, NC; Durham; NC; unemployment; rate; and USA.

This dataset provides a comprehensive overview of job market dynamics and unemployment trends across multiple regions from 2019 to 2023. It includes monthly data on unemployment rates, the number of active job postings, and the top in-demand skills within each region. Additionally, the dataset captures workforce demographics such as average age and education levels of unemployed workers, alongside indicators for retraining program needs.

The dataset is designed to support analysis and modeling tasks such as predicting unemployment hotspots, identifying skill gaps, and recommending targeted retraining or upskilling programs. It serves as a valuable resource for labor economists, policymakers, workforce development agencies, and data scientists aiming to understand and address regional employment challenges.

Overview with Chart & Report: Unemployment Rate is a percentage of unemployed workers in relation to the total civilian labor force. It reflects unemployed people actively seeking employment. The unemployment rate is a measure of

Unemployment Rates by State

Unemployment rates in US states from 1976 to 2018

By Throwback Thursday [source]

About this dataset

This dataset, titled Unemployment by State 1976 - 2018, provides comprehensive information on unemployment rates in each state within the United States from 1976 to 2018. The data was sourced from the Bureau of Labor Statistics, ensuring reliability and relevance.

The dataset includes a variety of columns that provide valuable insights into the unemployment situation in each state during this time period. These columns include:

1. Month and Year: This column represents the specific month and year for which the data was recorded. It enables researchers to analyze trends and changes in unemployment rates over time.

2. State: This categorical column indicates the name of the individual state for which the unemployment data is recorded. It allows users to compare and contrast unemployment rates between different states throughout this time frame.

3. Civilian Population: This numeric column represents the total number of individuals who were not part of the military or institutionalized, and were at least 16 years old during a particular month and year. It serves as a reference point for understanding workforce size when analyzing employment trends.

4. Total Labor Force: This numeric column represents the total number of individuals who were either employed or actively seeking employment during a specific period in a particular state. It provides an accurate measure of workforce participation that can be used alongside other variables for further analysis.

5. Percent of Population: This numeric column reflects what percentage of a state's civilian population made up its total labor force during a given month and year, providing insights into labor market dynamics on a proportional scale.

6. Employed - Total: This numeric column gives an aggregate count representing how many individuals were employed within each state during a certain period, enabling analysis of employment opportunities across states over time.

7. Employed - Percent of Population: Expressed as a percentage, this variable indicates what proportion of each state's civilian population was employed during specific months/years under consideration. It helps measure the efficiency of state economies in utilizing available workforce resources.

8. Unemployed - Total: This numeric column represents the total number of individuals who were unemployed during specific months and years within each state. It serves as a quantifiable indicator of labor market fluctuations and economic challenges faced by different states at various times.

9. Unemployed - Percent of Labor Force: This numeric column reveals the percentage of total labor force members who were unemployed during specific periods, providing an insight into the severity of unemployment rates relative to overall workforce size.

With this comprehensive dataset, researchers can conduct in-depth analyses on unemployment rates across different states

How to use the dataset

This dataset provides comprehensive information on unemployment rates in each state from 1976 to 2018. The data is obtained from the Bureau of Labor Statistics and covers various aspects related to unemployment.

Here is a step-by-step guide on how to effectively utilize this dataset:

• Understand the columns: Familiarize yourself with the different columns present in the dataset. Each column represents a specific attribute related to unemployment rates, such as the month and year of the data recorded, state name, civilian population, total labor force, percentage of population employed or unemployed, and more.

• Filter by state: If you are interested in analyzing specific states, use the State column to filter and extract data for those particular states. This will help you focus your analysis on regions that are most relevant to your research or area of interest.

• Analyze trends over time: Utilize the Month and Year column (excluding dates) for understanding long-term trends in unemployment rates across different states. This can be done by creating line plots or bar charts comparing unemployment rates for multiple states over time.

• Compare employment percentages: The columns Employed - Percent of Population and Unemployed - Percent of Labor Force provide valuable insights into employment trends at both individual state as well as national levels. Use these percentages to compare different states' employment performances against each other or within a specific timeframe.

• Calculate raw numbers: The columns E...

Dataset

This dataset was created by Saai Sudarsanan D

Released under World Bank Dataset Terms of Use

Contents

Context

This dataset is created via OECD datasource which is consisted of 2000 between 2019. https://data.oecd.org/unemp/unemployment-rate.htm

Content

The unemployed are people of working age who are without work, are available for work, and have taken specific steps to find work. The uniform application of this definition results in estimates of unemployment rates that are more internationally comparable than estimates based on national definitions of unemployment. This indicator is measured in numbers of unemployed people as a percentage of the labour force and it is seasonally adjusted. The labour force is defined as the total number of unemployed people plus those in employment. Data are based on labour force surveys (LFS). For European Union countries where monthly LFS information is not available, the monthly unemployed figures are estimated by Eurostat.

In 2024, unemployment affected approximately **** million people in Japan, marking a decrease from the previous year. The number of unemployed people decreased by over *** million compared to 2002 when unemployment was the highest in the last two decades.

Graph and download economic data for Unemployment Rate - With a Disability, 16 Years and over (LNU04074597) from Jun 2008 to Sep 2025 about disability, 16 years +, household survey, unemployment, rate, and USA.

This dataset contains historical and recent unemployment data from various sources, including the Current Population Survey (Household Survey). It features unemployment rates and levels for the United States and specific states like California and Texas, covering different demographic groups and seasonal adjustments. Data is provided in monthly and quarterly frequencies. Key metrics include the overall unemployment rate, insured unemployment, and the noncyclical rate of unemployment. This dataset is useful for economic analysis and forecasting unemployment trends.

Column Descriptions:

id: Unique identifier for each data series. realtime_start: The start date when the data was recorded in real-time. realtime_end: The end date when the data was recorded in real-time. title: Title of the data series. observation_start: The starting date of the observation period for the data series. observation_end: The ending date of the observation period for the data series. frequency: The frequency at which data is recorded (e.g., Monthly, Quarterly). frequency_short: Shortened notation for the frequency (e.g., M for Monthly, Q for Quarterly). units: Units of measurement for the data (e.g., Percent, Thousands of Persons). units_short: Shortened notation for units (e.g., %, Thous. of Persons). seasonal_adjustment: Indicates whether the data is seasonally adjusted. seasonal_adjustment_short: Shortened notation for seasonal adjustment (e.g., SA for Seasonally Adjusted, NSA for Not Seasonally Adjusted). last_updated: The date and time when the data series was last updated. popularity: Popularity score of the data series, indicating its usage or reference frequency. notes: Additional notes providing context or details about the data series.

Unemployment rate of people from non-white ethnic groups Source: Annual Population Survey (APS) Publisher: Nomis Geographies: Local Authority District (LAD), County/Unitary Authority, Government Office Region (GOR), National Geographic coverage: England Time coverage: 2004 to 2009 Type of data: Survey

Graph and download economic data for Unemployment Rate - Black or African American (LNS14000006) from Jan 1972 to Sep 2025 about African-American, 16 years +, household survey, unemployment, rate, and USA.