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.

Italy's unemployment rate was 6.6 percent in 2024, the lowest value since 2008. Forecasts suggest that it will stabilize around six percent between 2025 and 2027. The regions with the highest unemployment rates were in the south. Campania, Calabria, and Sicily registered rates from 16.1 percent to 17.8 percent, a large difference when compared to the northern regions, as only 2.9 percent of residents in Trentino-South Tyrol were unemployed, the lowest share nationwide. Young people mostly impacted Figures about the youth unemployment rate show that the financial crisis impacted the young working population significantly. Between 2004 and 2007, the share of unemployed individuals aged 15 to 24 years was declining. Subsequently, between 2008 and 2014, the rate almost doubled. In this case, southern regions had the largest share of young people without a job. In Sicily, Campania, and Calabria, more than one third of the population aged between 15 and 24 years was unemployed in 2022. Women more often unemployed In most of the Italian regions, the share of young unemployed women was higher than that of young males. In both Campania and Sicily, 50 percent of women aged 15 to 24 years did not have a job. Sicily was the region in Italy with the highest rate of unemployed young men. In this region, 51 percent of males were unemployed, almost five times more than in Trentino-South Tyrol, where the unemployment rate of young men stood at around nine percent.

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

Total unemployed as a percentage of the 15-65-year-old population in 2008 at the level of the planning areas (status 1 - LOR)(Monitoring of social urban development 2009 at the LOR level)

With the collapse of the U.S. housing market and the subsequent financial crisis on Wall Street in 2007 and 2008, economies across the globe began to enter into deep recessions. What had started out as a crisis centered on the United States quickly became global in nature, as it became apparent that not only had the economies of other advanced countries (grouped together as the G7) become intimately tied to the U.S. financial system, but that many of them had experienced housing and asset price bubbles similar to that in the U.S.. The United Kingdom had experienced a huge inflation of housing prices since the 1990s, while Eurozone members (such as Germany, France and Italy) had financial sectors which had become involved in reckless lending to economies on the periphery of the EU, such as Greece, Ireland and Portugal. Other countries, such as Japan, were hit heavily due their export-led growth models which suffered from the decline in international trade. Unemployment during the Great Recession As business and consumer confidence crashed, credit markets froze, and international trade contracted, the unemployment rate in the most advanced economies shot up. While four to five percent is generally considered to be a healthy unemployment rate, nearing full employment in the economy (when any remaining unemployment is not related to a lack of consumer demand), many of these countries experienced rates at least double that, with unemployment in the United States peaking at almost 10 percent in 2010. In large countries, unemployment rates of this level meant millions or tens of millions of people being out of work, which led to political pressures to stimulate economies and create jobs. By 2012, many of these countries were seeing declining unemployment rates, however, in France and Italy rates of joblessness continued to increase as the Euro crisis took hold. These countries suffered from having a monetary policy which was too tight for their economies (due to the ECB controlling interest rates) and fiscal policy which was constrained by EU debt rules. Left with the option of deregulating their labor markets and pursuing austerity policies, their unemployment rates remained over 10 percent well into the 2010s. Differences in labor markets The differences in unemployment rates at the peak of the crisis (2009-2010) reflect not only the differences in how economies were affected by the downturn, but also the differing labor market institutions and programs in the various countries. Countries with more 'liberalized' labor markets, such as the United States and United Kingdom experienced sharp jumps in their unemployment rate due to the ease at which employers can lay off workers in these countries. When the crisis subsided in these countries, however, their unemployment rates quickly began to drop below those of the other countries, due to their more dynamic labor markets which make it easier to hire workers when the economy is doing well. On the other hand, countries with more 'coordinated' labor market institutions, such as Germany and Japan, experiences lower rates of unemployment during the crisis, as programs such as short-time work, job sharing, and wage restraint agreements were used to keep workers in their jobs. While these countries are less likely to experience spikes in unemployment during crises, the highly regulated nature of their labor markets mean that they are slower to add jobs during periods of economic prosperity.

Unemployment Rate in Serbia decreased to 8.50 percent in the second quarter of 2025 from 9.10 percent in the first quarter of 2025. This dataset provides - Serbia Unemployment Rate - actual values, historical data, forecast, chart, statistics, economic calendar and news.

Graph and download economic data for Total Unemployed, Plus All Persons Marginally Attached to the Labor Force, Plus Total Employed Part Time for Economic Reasons, as a Percent of the Civilian Labor Force Plus All Persons Marginally Attached to the Labor Force (U-6) (U6RATE) from Jan 1994 to Aug 2025 about marginally attached, part-time, labor underutilization, workers, 16 years +, labor, household survey, unemployment, and USA.

This is the monthly data for U.S. employment and unemployment by state including some numbers for Puerto Rico. This dataset was accessed on April 7th 2008. The data for February 2008 are preliminary. The data presented are seasonally adjusted although the unadjusted numbers are also available. Unavailable data are represented as -1. The dataset is taken from Tables 3 and 5 from the United States Department of Labor, Bureau of Labor Statistics. It includes the civilian labor force, the unemployed in numbers and percentages, and employment by industry. Data from table 3 "refer to place of residence. Data for Puerto Rico are derived from a monthly household survey similar to the Current Population Survey. Area definitions are based on Office of Management and Budget Bulletin No. 08-01, dated November 20, 2007, and are available at http://www.bls.gov/lau/lausmsa.htm. Estimates for the latest month are subject to revision the following month". Data from table 5 "are counts of jobs by place of work. Estimates are currently projected from 2007 benchmark levels. Estimates subsequent to the current benchmarks are provisional and will be revised when new information becomes available. Data reflect the conversion to the 2007 version of the North American Industry Classification System (NAICS) as the basis for the assignment and tabulation of economic data by industry, replacing NAICS 2002. For more details, see http://www.bls.gov/sae/saenaics07.htm.

Switzerland Registered Unemployment Rate: NOGA 2008: SS: Electrical and Electronic Equipt data was reported at 2.400 % in Oct 2018. This records a decrease from the previous number of 2.500 % for Sep 2018. Switzerland Registered Unemployment Rate: NOGA 2008: SS: Electrical and Electronic Equipt data is updated monthly, averaging 3.879 % from Jan 2004 (Median) to Oct 2018, with 178 observations. The data reached an all-time high of 6.700 % in Dec 2009 and a record low of 2.400 % in Oct 2018. Switzerland Registered Unemployment Rate: NOGA 2008: SS: Electrical and Electronic Equipt data remains active status in CEIC and is reported by State Secretariat for Economic Affairs. The data is categorized under Global Database’s Switzerland – Table CH.G024: Registered Unemployment Rate: by NOGA 2008 Economic Sector.

Monthly metrics on unemployment insurance from the Department of Labor, Licensing and Regulation.

Graph and download economic data for Unemployment Rate - 18 Years and over, Men (LNU04076980) from Dec 2008 to Aug 2025 about 18 years +, males, unemployment, rate, and USA.

Unemployment Rate - With a Disability - Historical chart and current data through 2025.

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.

Israel Unemployment: 2008 Census: Chained Linked: Seasonal Adjusted data was reported at 165.290 Person th in Sep 2018. This records an increase from the previous number of 161.200 Person th for Jun 2018. Israel Unemployment: 2008 Census: Chained Linked: Seasonal Adjusted data is updated quarterly, averaging 262.869 Person th from Mar 1995 (Median) to Sep 2018, with 95 observations. The data reached an all-time high of 404.425 Person th in Mar 2004 and a record low of 150.490 Person th in Mar 2018. Israel Unemployment: 2008 Census: Chained Linked: Seasonal Adjusted data remains active status in CEIC and is reported by Bank of Israel. The data is categorized under Global Database’s Israel – Table IL.G030: Unemployment: 2008 Census: Chain Linked: Bank of Israel.

In 2010, unemployment rate in France reached a record level of 10.4 percent. Unemployment remains a rampant issue for French economy, being stagnant year-over-year since the financial and economical crisis in 2008. During the first quarter of 2018, more than 1.4 million people aged between 25 and 49 years were unemployed in France.

Change in unemployment since 2008

In 2008, year of the financial crisis, unemployment rate in France reached its lowest level since 2004. That year, France had an unemployment rate of 7.4 percent while, one year before it had reached 8 eight percent. Unemployment is an important economic factor for a country and a measure of a region’s economic health. Despite its low level in 2008, unemployment rate in France increased steadily between 2009 and 2016. In 2015, it even reached its highest level since the mid-2000s with a percentage of unemployed people among the French population which was of 10.4 percent. That year, unemployed people represented 11.5 percent of the urban population in France. However, French unemployment rate seemed to be experiencing improvements in recent years. In 2017, long-term employment rate decreased after several years of constant growth.

Unemployment in France and the EU

European markets were particularly affected by the 2008 global financial crisis and the recession which followed. Nevertheless, Unemployment rate in the EU reached 6.5 percent in January 2019, compared to 7.2 percent one year before and the number of unemployed persons in the European Union and the Euro area is declining since 2018. This improvement seems to be affecting France to a lesser extent. France was one of the EU members with the highest unemployment rate in 2019, and youth unemployment still reaches a record number in the country.

This dataset shows the evolution of the unemployment rate in the regions of the European Union between 2008 and 2013.

The unemployment rate in the EU-28 fell from 9.3% in 2004 to 7.1% in 2008. Between 2008 and 2013, however, it rose to 10.9%, higher than at any time for which data are available (since 2000). In the EU-15, unemployment was 11.1% in 2013, which is also higher than at any time for which comparable figures are available.

EU-28 = 3.5; Source: Eurostat, DG REGIO

Youth Unemployment Rate in Serbia decreased to 22.80 percent in the second quarter of 2025 from 24.10 percent in the first quarter of 2025. This dataset provides - Serbia Youth Unemployment Rate- actual values, historical data, forecast, chart, statistics, economic calendar and news.

Descriptiondata presented as spreadsheet; Provides an overview of the official unemployment rate by narrow definition across all provinces and metros in South Africa since 2008.Artefact TypeDataset (non-spatial)LineageThe data presented is extracted from Statistics South Africa (Stats SA) Quarterly Labour Force Survey (QLFS) trends as published on https://www.statssa.gov.za/Publication Date13 May 2025Data Sources / LayersQLFS Trends 2008-2025Q1, Stats SA, published 13 May 2025Terms of useNo special restrictions or limitations on using the item's content have been provided Contact PersonElize van der Berg, Department of the Premier, Elize.VanDerBerg@westerncape.gov.za

Graph and download economic data for Infra-Annual Labor Statistics: Unemployment Rate Male: 15 Years or over for Indonesia (LRUNTTMAIDA156N) from 2008 to 2008 about 15 years +, Indonesia, males, unemployment, and rate.

Switzerland Registered Unemployment Rate: NOGA 2008: SS: Mining and Quarrying data was reported at 1.400 % in Jun 2018. This records a decrease from the previous number of 1.500 % for May 2018. Switzerland Registered Unemployment Rate: NOGA 2008: SS: Mining and Quarrying data is updated monthly, averaging 1.700 % from Jan 2004 (Median) to Jun 2018, with 174 observations. The data reached an all-time high of 3.800 % in Jan 2013 and a record low of 0.600 % in Sep 2007. Switzerland Registered Unemployment Rate: NOGA 2008: SS: Mining and Quarrying data remains active status in CEIC and is reported by State Secretariat for Economic Affairs. The data is categorized under Global Database’s Switzerland – Table CH.G024: Registered Unemployment Rate: by NOGA 2008 Economic Sector.