In 1990, the unemployment rate of the United States stood at 5.6 percent. Since then there have been many significant fluctuations to this number - the 2008 financial crisis left millions of people without work, as did the COVID-19 pandemic. By the end of 2022 and throughout 2023, the unemployment rate came to 3.6 percent, the lowest rate seen for decades. However, 2024 saw an increase up to four percent. For monthly updates on unemployment in the United States visit either the monthly national unemployment rate here, or the monthly state unemployment rate here. Both are seasonally adjusted. UnemploymentUnemployment is defined as a situation when an employed person is laid off, fired or quits his work and is still actively looking for a job. Unemployment can be found even in the healthiest economies, and many economists consider an unemployment rate at or below five percent to mean there is 'full employment' within an economy. If former employed persons go back to school or leave the job to take care of children they are no longer part of the active labor force and therefore not counted among the unemployed. Unemployment can also be the effect of events that are not part of the normal dynamics of an economy. Layoffs can be the result of technological progress, for example when robots replace workers in automobile production. Sometimes unemployment is caused by job outsourcing, due to the fact that employers often search for cheap labor around the globe and not only domestically. In 2022, the tech sector in the U.S. experienced significant lay-offs amid growing economic uncertainty. In the fourth quarter of 2022, more than 70,000 workers were laid off, despite low unemployment nationwide. The unemployment rate in the United States varies from state to state. In 2021, California had the highest number of unemployed persons with 1.38 million out of work.

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.

The unemployment rate in fiscal year 2204 rose to 3.9 percent. The unemployment rate of the United States which has been steadily decreasing since the 2008 financial crisis, spiked to 8.1 percent in 2020 due to the COVID-19 pandemic. The annual unemployment rate of the U.S. since 1990 can be found here. Falling unemployment The unemployment rate, or the part of the U.S. labor force that is without a job, fell again in 2022 after peaking at 8.1 percent in 2020 - a rate that has not been seen since the years following the 2008 financial crisis. The financial crash caused unemployment in the U.S. to soar from 4.6 percent in 2007 to 9.6 percent in 2010. Since 2010, the unemployment rate had been steadily falling, meaning that more and more people are finding work, whether that be through full-time employment or part-time employment. However, the affects of the COVID-19 pandemic created a spike in unemployment across the country. U.S. unemployment in comparison Compared to unemployment rates in the European Union, U.S. unemployment is relatively low. Greece was hit particularly hard by the 2008 financial crisis and faced a government debt crisis that sent the Greek economy into a tailspin. Due to this crisis, and the added impact of the pandemic, Greece still has the highest unemployment rate in the European Union.

Graph and download economic data for Unemployment Rate - 16-24 Yrs. (LNS14024887) from Jan 1948 to Sep 2025 about 16 to 24 years, unemployment, rate, and USA.

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.

Unemployment rate, participation rate, and employment rate by educational attainment, gender and age group, annual.

Unemployment Rate in Australia decreased to 4.30 percent in October from 4.50 percent in September of 2025. This dataset provides - Australia Unemployment Rate at 5.8% in December - actual values, historical data, forecast, chart, statistics, economic calendar and news.

United States Unemployment Rate: sa: West Virginia data was reported at 5.300 % in Jun 2018. This records a decrease from the previous number of 5.400 % for May 2018. United States Unemployment Rate: sa: West Virginia data is updated monthly, averaging 7.300 % from Jan 1976 (Median) to Jun 2018, with 510 observations. The data reached an all-time high of 18.800 % in Feb 1983 and a record low of 4.000 % in Jul 2008. United States Unemployment Rate: sa: West Virginia data remains active status in CEIC and is reported by Bureau of Labor Statistics. The data is categorized under Global Database’s USA – Table US.G058: Unemployment Rate: By State: Seasonally Adjusted.

Unemployment Rate in Greece decreased to 8.60 percent in October from 8.70 percent in September of 2025. This dataset provides the latest reported value for - Greece Unemployment Rate - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

This table includes the Labor force data by county files for 2008, 2009, and 2010 annual averages. It comes from the U.S. Bureau of Labor Statistics Local Area Unemployment Statistics webpage.

United States Unemployment Rate: Louisiana data was reported at 4.700 % in Oct 2018. This records a decrease from the previous number of 5.000 % for Sep 2018. United States Unemployment Rate: Louisiana data is updated monthly, averaging 6.800 % from Jan 1976 (Median) to Oct 2018, with 514 observations. The data reached an all-time high of 13.700 % in Jan 1987 and a record low of 3.600 % in Apr 2008. United States Unemployment Rate: Louisiana data remains active status in CEIC and is reported by Bureau of Labor Statistics. The data is categorized under Global Database’s United States – Table US.G057: Unemployment Rate: By State.

Context

This dataset lists the natural rate of unemployment (NAIRU) in the U.S., which is the rate of unemployment arising from all sources except fluctuations in aggregate demand. Estimates of potential GDP are based on the long-term natural rate. The short-term natural rate incorporates structural factors that are temporarily boosting the natural rate beginning in 2008. The short-term natural rate is used to gauge the amount of current and projected slack in labor markets, which is a key input into CBO's projections of inflation.

Content

Data includes the date of the quarterly collection and the natural rate of unemployment from January 1, 1949 through October 1, 2016.

Inspiration

• What is the general trend of unemployment?
• Can you compare this unemployment data with other factors found in any of the BLS databases, such as manufacturing employment rates and GDP?

Acknowledgement

This dataset is part of the US Department of Labor Bureau of Labor Statistics Datasets (the Federal Reserve Economic Data database), and the original source can be found here.

Oman OM: Unemployment: National Estimate: % of Total Labour Force data was reported at 4.142 % in 2008. This records a decrease from the previous number of 17.270 % for 1996. Oman OM: Unemployment: National Estimate: % of Total Labour Force data is updated yearly, averaging 10.706 % from Dec 1996 (Median) to 2008, with 2 observations. The data reached an all-time high of 17.270 % in 1996 and a record low of 4.142 % in 2008. Oman OM: Unemployment: National Estimate: % of Total Labour Force data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Oman – Table OM.World Bank: Employment and Unemployment. Unemployment refers to the share of the labor force that is without work but available for and seeking employment. Definitions of labor force and unemployment differ by country.; ; International Labour Organization, ILOSTAT database. Data retrieved in November 2017.; Weighted Average; The series for ILO estimates is also available in the WDI database. Caution should be used when comparing ILO estimates with national estimates.

In 2025, it was estimated that over 163 million Americans were in some form of employment, while 4.16 percent of the total workforce was unemployed. This was the lowest unemployment rate since the 1950s, although these figures are expected to rise in 2023 and beyond. 1980s-2010s Since the 1980s, the total United States labor force has generally risen as the population has grown, however, the annual average unemployment rate has fluctuated significantly, usually increasing in times of crisis, before falling more slowly during periods of recovery and economic stability. For example, unemployment peaked at 9.7 percent during the early 1980s recession, which was largely caused by the ripple effects of the Iranian Revolution on global oil prices and inflation. Other notable spikes came during the early 1990s; again, largely due to inflation caused by another oil shock, and during the early 2000s recession. The Great Recession then saw the U.S. unemployment rate soar to 9.6 percent, following the collapse of the U.S. housing market and its impact on the banking sector, and it was not until 2016 that unemployment returned to pre-recession levels. 2020s 2019 had marked a decade-long low in unemployment, before the economic impact of the Covid-19 pandemic saw the sharpest year-on-year increase in unemployment since the Great Depression, and the total number of workers fell by almost 10 million people. Despite the continuation of the pandemic in the years that followed, alongside the associated supply-chain issues and onset of the inflation crisis, unemployment reached just 3.67 percent in 2022 - current projections are for this figure to rise in 2023 and the years that follow, although these forecasts are subject to change if recent years are anything to go by.

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 2008 Employment and Unemployment Survey (EUS) during February, May, August and November 2008. The survey rounds covered a total sample of about fifty three thousand households Nation-wide. The sampled households were selected using a stratified multi-stage cluster sampling design. It is noteworthy that the sample represents the national level (Kingdom), governorates, the three Regions (Central, North and South), and the urban/rural areas.

The importance of this survey lies in that it provides a comprehensive data base on employment and unemployment that serves decision makers, researchers as well as other parties concerned with policies related to the organization of the Jordanian labor market.

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, the three Regions (Central, North and South), and the urban/rural areas.

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

Survey Frame

The sample of this survey is based on the frame provided by the data of the Population and Housing Census, 2004. The Kingdom was divided into strata, where each city with a population of 100,000 persons or more was considered as a large city. The total number of these cities is 6. Each governorate (except for the 6 large cities) was divided into rural and urban areas. The rest of the urban areas in each governorate was considered as an independent stratum. The same was applied to rural areas where it was considered as an independent stratum. The total number of strata was 30.

In view of the existing significant variation in the socio-economic characteristics in large cities in particular and in urban in general, each stratum of the large cities and urban strata was divided into four sub-stratum according to the socio- economic characteristics provided by the population and housing census with the purpose of providing homogeneous strata.

The frame excludes the population living in remote areas (most of whom are nomads). In addition to that, the frame does not include collective dwellings, such as hotels, hospitals, work camps, prisons and alike.

Sample Design

The sample of this survey was designed, using the two-stage cluster stratified sampling method. The main sample was designed in 2007 based on the data of the population and housing census 2004 for carrying out household surveys. The sample is representative on the Kingdom, rural-urban regions and governorates levels. The total sample size for each round was 1336 Primary Sampling Units (PSUs) (clusters). These units were distributed to urban and rural regions in the governorates, in addition to the large cities in each governorate according to the weight of persons and households, and according to the variance within each stratum. Slight modifications regarding the number of these units were made to cope with the multiple of 8, the number of clusters for four rounds was 5344.

The main sample consists of 40 replicates, each replicate consists of 167 PSUs. For the purpose of each round, eight replicates of the main sample were used. The PSUs were ordered within each stratum according to geographic characteristics and then according to socio-economic characteristics in order to ensure good spread of the sample. Then, the sample was selected on two stages. In the first stage, the PSUs were selected using the Probability Proportionate to Size with systematic selection procedure. The number of households in each PSU served as its weight or size. In the second stage, the blocks of the PSUs (cluster) which were selected in the first stage have been updated. Then a constant number of households (10 households) was selected, using the random systematic sampling method as final PSUs from each PSU (cluster).

Sampling notes

It is noteworthy that the sample of the present survey does not represent the non-Jordanian population, due to the fact that it is based on households living in conventional dwellings. In other words, it does not cover the collective households living in collective dwellings. Therefore, the non-Jordanian households covered in the present survey are either private households or collective households living in conventional dwellings. In Jordan, it is well known that a large number of non-Jordanian workers live as groups and spend most of their time at their work places. Hence, it is more unlikely to find them at their residences during daytime (i.e. the time when the data of the survey is collected). Furthermore, most of them live in their work places, such as: workshops, sales stores, guard places, or under construction building's sites. Such places are not classified as occupied dwellings for household sampling purposes. Due to all of the above, the coverage of such population would not be complete in household surveys.

Mode of data collection

Computer Assisted Personal Interview [capi]

Research instrument

The questionnaire is divided into main topics, each containing a clear and consistent group of questions, and designed in a way that facilitates the electronic data entry and verification. The questionnaire includes the characteristics of household members in addition to the identification information, which reflects the administrative as well as the statistical divisions of the Kingdom.

Cleaning operations

Raw Data

The plan of the tabulation of survey results was guided by former Employment and Unemployment Surveys which were previously prepared and tested. When all data processing procedures were completed, the actual survey results were tabulated using an ORACLE package. The tabulations were then thoroughly checked for consistency of data such as titles, inputs, concepts, as well as the figures. The final survey report was then prepared to include all 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.

United States Unemployment Rate: West Virginia data was reported at 5.400 % in Jun 2018. This records an increase from the previous number of 5.100 % for May 2018. United States Unemployment Rate: West Virginia data is updated monthly, averaging 7.500 % from Jan 1976 (Median) to Jun 2018, with 510 observations. The data reached an all-time high of 20.400 % in Feb 1983 and a record low of 3.600 % in Sep 2008. United States Unemployment Rate: West Virginia data remains active status in CEIC and is reported by Bureau of Labor Statistics. The data is categorized under Global Database’s USA – Table US.G057: Unemployment Rate: By State.

Unemployment rate between 2008 and 2017

Cuba CU: Unemployment: National Estimate: % of Total Labour Force data was reported at 1.700 % in 2018. This stayed constant from the previous number of 1.700 % for 2017. Cuba CU: Unemployment: National Estimate: % of Total Labour Force data is updated yearly, averaging 2.600 % from Dec 1995 (Median) to 2018, with 24 observations. The data reached an all-time high of 8.270 % in 1995 and a record low of 1.583 % in 2008. Cuba CU: Unemployment: National Estimate: % of Total Labour Force data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Cuba – Table CU.World Bank.WDI: Employment and Unemployment. Unemployment refers to the share of the labor force that is without work but available for and seeking employment. Definitions of labor force and unemployment differ by country.;International Labour Organization. “Labour Force Statistics database (LFS)” ILOSTAT. Accessed January 07, 2025. https://ilostat.ilo.org/data/.;Weighted average;The series for ILO estimates is also available in the WDI database. Caution should be used when comparing ILO estimates with national estimates.

Creating datasets like this takes significant time and effort. If you found this dataset useful, a kind upvote would be greatly appreciated!!

This dataset provides a 30 year comprehensive view of global employment, unemployment, and GDP trends from 1991 to 2022. It includes data of approx 183 countries on employment distribution across agriculture, industry, and services sectors, alongside unemployment rates and GDP figures.

What You Can Do with This Dataset: This dataset opens up several possibilities for analysis and exploration. You can study long-term trends in employment, unemployment, and GDP across countries and regions, and visualize how labor distribution has shifted from agriculture to services over the years. It also allows you to examine the impact of major global events, such as the 2008 Financial Crisis and the 2020 COVID-19 pandemic, on economic and employment patterns. Furthermore, the dataset can be used for time-series forecasting and predictive modeling, helping to estimate future employment trends and GDP growth.

Description of columns:

Country Name – The name of the country.

Year – The year of observation (1991–2022).

Employment Sector: Agriculture – Percentage of total employment in agriculture.

Employment Sector: Industry – Percentage of total employment in industry.

Employment Sector: Services – Percentage of total employment in services.

Unemployment Rate – Percentage of the labor force that is unemployed.

GDP (in USD) – Gross Domestic Product of the country (in U.S. dollars).

Context

The Federal Reserve sets interest rates to promote conditions that achieve the mandate set by the Congress — high employment, low and stable inflation, sustainable economic growth, and moderate long-term interest rates. Interest rates set by the Fed directly influence the cost of borrowing money. Lower interest rates encourage more people to obtain a mortgage for a new home or to borrow money for an automobile or for home improvement. Lower rates encourage businesses to borrow funds to invest in expansion such as purchasing new equipment, updating plants, or hiring more workers. Higher interest rates restrain such borrowing by consumers and businesses.

Content

This dataset includes data on the economic conditions in the United States on a monthly basis since 1954. The federal funds rate is the interest rate at which depository institutions trade federal funds (balances held at Federal Reserve Banks) with each other overnight. The rate that the borrowing institution pays to the lending institution is determined between the two banks; the weighted average rate for all of these types of negotiations is called the effective federal funds rate. The effective federal funds rate is determined by the market but is influenced by the Federal Reserve through open market operations to reach the federal funds rate target. The Federal Open Market Committee (FOMC) meets eight times a year to determine the federal funds target rate; the target rate transitioned to a target range with an upper and lower limit in December 2008. The real gross domestic product is calculated as the seasonally adjusted quarterly rate of change in the gross domestic product based on chained 2009 dollars. The unemployment rate represents the number of unemployed as a seasonally adjusted percentage of the labor force. The inflation rate reflects the monthly change in the Consumer Price Index of products excluding food and energy.

Acknowledgements

The interest rate data was published by the Federal Reserve Bank of St. Louis' economic data portal. The gross domestic product data was provided by the US Bureau of Economic Analysis; the unemployment and consumer price index data was provided by the US Bureau of Labor Statistics.

Inspiration

How does economic growth, unemployment, and inflation impact the Federal Reserve's interest rates decisions? How has the interest rate policy changed over time? Can you predict the Federal Reserve's next decision? Will the target range set in March 2017 be increased, decreased, or remain the same?