Graph and download economic data for Unemployment Level - Job Losers on Layoff (LNU03023653) from Jan 1967 to Jun 2025 about job losers, layoffs, 16 years +, household survey, unemployment, and USA.

United States Unemployment: Job Losers On Layoff data was reported at 952.000 Person th in Jun 2018. This records an increase from the previous number of 533.000 Person th for May 2018. United States Unemployment: Job Losers On Layoff data is updated monthly, averaging 976.000 Person th from Jan 1967 (Median) to Jun 2018, with 618 observations. The data reached an all-time high of 2,947.000 Person th in Jan 1983 and a record low of 235.000 Person th in Oct 1968. United States Unemployment: Job Losers On Layoff 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.G016: Current Population Survey: Unemployment.

In 2024, over 25,000 job losses were accounted for in the U.S. media industry, down by 30 percent compared to a year prior. The media industry in the United States has been deeply impacted by the pandemic and the following inflation, as well as the introduction of Generative AI technologies, resulting in an increasing number of layoffs. While about 10,000 job cuts in media were reported in 2019, that value had tripled the following year.

Graph and download economic data for Job Losers on Layoff as a Percent of Total Unemployed (LNS13023654) from Jan 1967 to Jun 2025 about job losers, layoffs, 16 years +, percent, household survey, unemployment, and USA.

United States Unemployment: sa: Job Losers On Layoff data was reported at 890.000 Person th in Jul 2018. This records a decrease from the previous number of 906.000 Person th for Jun 2018. United States Unemployment: sa: Job Losers On Layoff data is updated monthly, averaging 1,000.000 Person th from Jan 1967 (Median) to Jul 2018, with 619 observations. The data reached an all-time high of 2,519.000 Person th in Sep 1982 and a record low of 250.000 Person th in Mar 1969. United States Unemployment: sa: Job Losers On Layoff 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.G017: Current Population Survey: Unemployment: Seasonally Adjusted.

The tech industry had a rough start to 2024. Technology companies worldwide saw a significant reduction in their workforce in the first quarter of 2024, with over 57 thousand employees being laid off. By the second quarter, layoffs impacted more than 43 thousand tech employees. In the final quarter of the year around 12 thousand employees were laid off. Layoffs impacting all global tech giants Layoffs in the global market escalated dramatically in the first quarter of 2023, when the sector saw a staggering record high of 167.6 thousand employees losing their jobs. Major tech giants such as Google, Microsoft, Meta, and IBM all contributed to this figure during this quarter. Amazon, in particular, conducted the most rounds of layoffs with the highest number of employees laid off among global tech giants. Industries most affected include the consumer, hardware, food, and healthcare sectors. Notable companies that have laid off a significant number of staff include Flink, Booking.com, Uber, PayPal, LinkedIn, and Peloton, among others. Overhiring led the trend, but will AI keep it going? Layoffs in the technology sector started following an overhiring spree during the COVID-19 pandemic. Initially, companies expanded their workforce to meet increased demand for digital services during lockdowns. However, as lockdowns ended, economic uncertainties persisted and companies reevaluated their strategies, layoffs became inevitable, resulting in a record number of 263 thousand laid off employees in the global tech sector by trhe end of 2022. Moreover, it is still unclear how advancements in artificial intelligence (AI) will impact layoff trends in the tech sector. AI-driven automation can replace manual tasks leading to workforce redundancies. Whether through chatbots handling customer inquiries or predictive algorithms optimizing supply chains, the pursuit of efficiency and cost savings may result in more tech industry layoffs in the future.

United States Unemployment: Job Losers Not On Layoff (NL) data was reported at 2,070.000 Person th in Jun 2018. This records an increase from the previous number of 1,960.000 Person th for May 2018. United States Unemployment: Job Losers Not On Layoff (NL) data is updated monthly, averaging 2,595.000 Person th from Jan 1967 (Median) to Jun 2018, with 618 observations. The data reached an all-time high of 8,564.000 Person th in Feb 2010 and a record low of 577.000 Person th in Sep 1969. United States Unemployment: Job Losers Not On Layoff (NL) 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.G016: Current Population Survey: Unemployment.

Challenger Job Cuts in the United States decreased to 47999 Persons in June from 93816 Persons in May of 2025. This dataset provides the latest reported value for - United States Challenger Job Cuts - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

In February 2025, the number of job losers and persons who completed temporary jobs in the United States stood at about 3.3 million and is used when analyzing non-seasonal trends. The monthly unemployment rate can be found here.

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.

Supplementary information on involuntary job loss and occupational training programs is provided in this collection, in addition to standard monthly Current Populaion Survey data on labor force activity. Workers who lost a job within the previous five years due to operating decisions of their employer were surveyed. Data include the reasons for job displacement, industry and occupation, job tenure and earnings, and health and unemployment benefits. The occupational training portion of the collection contains data on training program attended within the past two years, including the number, length, and type of programs attended, as well as the source of payment. The monthly labor force information includes data for persons age 14 and older on employment status, occupation, and industry. Demographic data such as age, sex, race, marital status, veteran status, education, household relationship, and Spanish origin are also provided.

To ensure respondent confidentiality, estimates below a certain threshold are suppressed. For Canada, Quebec, Ontario, Alberta and British Columbia suppression is applied to all data below 1,500. The threshold level for Newfoundland and Labrador, Nova Scotia, New Brunswick, Manitoba and Saskatchewan is 500, while in Prince Edward Island, estimates under 200 are suppressed. For census metropolitan areas (CMAs) and economic regions (ERs), use their respective provincial suppression levels mentioned above. Estimates are based on smaller sample sizes the more detailed the table becomes, which could result in lower data quality. Fluctuations in economic time series are caused by seasonal, cyclical and irregular movements. A seasonally adjusted series is one from which seasonal movements have been eliminated. Seasonal movements are defined as those which are caused by regular annual events such as climate, holidays, vacation periods and cycles related to crops, production and retail sales associated with Christmas and Easter. It should be noted that the seasonally adjusted series contain irregular as well as longer-term cyclical fluctuations. The seasonal adjustment program is a complicated computer program which differentiates between these seasonal, cyclical and irregular movements in a series over a number of years and, on the basis of past movements, estimates appropriate seasonal factors for current data. On an annual basis, the historic series of seasonally adjusted data are revised in light of the most recent information on changes in seasonality. Number of civilian, non-institutionalized persons 15 years of age and over who, during the reference week, were employed or unemployed. Estimates in thousands, rounded to the nearest hundred. Number of persons who, during the reference week, worked for pay or profit, or performed unpaid family work or had a job but were not at work due to own illness or disability, personal or family responsibilities, labour dispute, vacation, or other reason. Those persons on layoff and persons without work but who had a job to start at a definite date in the future are not considered employed. Estimates in thousands, rounded to the nearest hundred. Number of persons who, during the reference week, were without work, had looked for work in the past four weeks, and were available for work. Those persons on layoff or who had a new job to start in four weeks or less are considered unemployed. Estimates in thousands, rounded to the nearest hundred. The unemployment rate is the number of unemployed persons expressed as a percentage of the labour force. The unemployment rate for a particular group (age, gender, marital status, etc.) is the number unemployed in that group expressed as a percentage of the labour force for that group. Estimates are percentages, rounded to the nearest tenth. Industry refers to the general nature of the business carried out by the employer for whom the respondent works (main job only). Industry estimates in this table are based on the 2022 North American Industry Classification System (NAICS). Formerly Management of companies and administrative and other support services"." This combines the North American Industry Classification System (NAICS) codes 11 to 91. This combines the North American Industry Classification System (NAICS) codes 11 to 33. This combines the North American Industry Classification System (NAICS) codes 41 to 91. Unemployed persons who have never worked before, and those unemployed persons who last worked more than 1 year ago. For more information on seasonal adjustment see Seasonally adjusted data - Frequently asked questions." Labour Force Survey (LFS) North American Industry Classification System (NAICS) code exception: add group 1100 - Farming - not elsewhere classified (nec). When the type of farm activity cannot be distinguished between crop and livestock, (for example: mixed farming). Labour Force Survey (LFS) North American Industry Classification System (NAICS) code exception: add group 2100 - Mining - not elsewhere classified (nec). Whenever the type of mining activity cannot be distinguished. Also referred to as Natural resources. The standard error (SE) of an estimate is an indicator of the variability associated with this estimate, as the estimate is based on a sample rather than the entire population. The SE can be used to construct confidence intervals and calculate coefficients of variation (CVs). The confidence interval can be built by adding the SE to an estimate in order to determine the upper limit of this interval, and by subtracting the same amount from the estimate to determine the lower limit. The CV can be calculated by dividing the SE by the estimate. See Section 7 of the Guide to the Labour Force Survey (opens new window) for more information. The standard errors presented in this table are the average of the standard errors for 12 previous months The standard error (SE) for the month-to-month change is an indicator of the variability associated with the estimate of the change between two consecutive months, because each monthly estimate is based on a sample rather than the entire population. To construct confidence intervals, the SE is added to an estimate in order to determine the upper limit of this interval, and then subtracted from the estimate to determine the lower limit. Using this method, the true value will fall within one SE of the estimate approximately 68% of the time, and within two standard errors approximately 95% of the time. For example, if the estimated employment level increases by 20,000 from one month to another and the associated SE is 29,000, the true value of the employment change has a 68% chance of falling between -9,000 and +49,000. Because such a confidence interval includes zero, the 20,000 change would not be considered statistically significant. However, if the increase is 30,000, the confidence interval would be +1,000 to +59,000, and the 30,000 increase would be considered statistically significant. (Note that 30,000 is above the SE of 29,000, and that the confidence interval does not include zero.) Similarly, if the estimated employment declines by 30,000, then the true value of the decline would fall between -59,000 and -1,000. See Section 7 of the Guide to the Labour Force Survey (opens new window) for more information. The standard errors presented in this table are the average of standard errors for 12 previous months. They are updated twice a year The standard error (SE) for the year-over-year change is an indicator of the variability associated with the estimate of the change between a given month in a given year and the same month of the previous year, because each month's estimate is based on a sample rather than the entire population. The SE can be used to construct confidence intervals: it can be added to an estimate in order to determine the upper limit of this interval, and then subtracted from the same estimate to determine the lower limit. Using this method, the true value will fall within one SE of the estimate, approximately 68% of the time, and within two standard errors, approximately 95% of the time. For example, if the estimated employment level increases by 160,000 over 12 months and the associated SE is 55,000, the true value of the change in employment has approximately a 68% chance of falling between +105,000 and +215,000. This change would be considered statistically significant at the 68% level as the confidence interval excludes zero. However, if the increase is 40,000, the interval would be -15,000 to +95,000, and this increase would not be considered statistically significant since the interval includes zero. See Section 7 of the Guide to the Labour Force Survey (opens new window) for more information. The standard errors presented in this table are the average of standard errors for 12 previous months and are updated twice a year Excluding the territories. Starting in 2006, enhancements to the Labour Force Survey data processing system may have introduced a level shift in some estimates, particularly for less common labour force characteristics. Use caution when comparing estimates before and after 2006. For more information, contact statcan.labour-travail.statcan@statcan.gc.ca

失业：因裁员而失业者在06-01-2018达952.000千人，相较于05-01-2018的533.000千人有所增长。失业：因裁员而失业者数据按月更新，01-01-1967至06-01-2018期间平均值为976.000千人，共618份观测结果。该数据的历史最高值出现于01-01-1983，达2,947.000千人，而历史最低值则出现于10-01-1968，为235.000千人。CEIC提供的失业：因裁员而失业者数据处于定期更新的状态，数据来源于Bureau of Labor Statistics，数据归类于Global Database的美国 – 表 US.G016：当前人口调查：失业。

Graph and download economic data for Monthly Share of Prime-Age U.S. Workers Who Leave the Labor Force After a Layoff (EMSHRNLP) from Jan 1978 to Apr 2025 about flow, labor force, labor, unemployment, employment, and USA.

Graph and download economic data for Monthly Transition Rate of Prime-Age U.S. Workers From Employment to Non-Employment Due to a Quit (EMEQPSA) from Jan 1978 to May 2025 about flow, labor force, labor, unemployment, employment, and USA.

失业：季节性调整后：因裁员而失业者在07-01-2018达890.000千人，相较于06-01-2018的906.000千人有所下降。失业：季节性调整后：因裁员而失业者数据按月更新，01-01-1967至07-01-2018期间平均值为1,000.000千人，共619份观测结果。该数据的历史最高值出现于09-01-1982，达2,519.000千人，而历史最低值则出现于03-01-1969，为250.000千人。CEIC提供的失业：季节性调整后：因裁员而失业者数据处于定期更新的状态，数据来源于Bureau of Labor Statistics，数据归类于Global Database的美国 – 表 US.G017：当前人口调查：失业：季节性调整后。

The statistic shows the unemployment rate in selected world regions between 2015 and 2023. In 2023, the unemployment rate in the Arab World was estimated to have been at 9.88 percent. Unemployment around the globe Following the global financial crisis in 2008, unemployment saw considerable downturns around the globe, most notably in 2009. Unemployment rates, despite experiencing dramatic improvements over the years following the crisis, still have not reached pre-2009 levels for the large majority of countries. The same trend is followed with unemployment among the youth between the ages of 15 and 24, around the world. Many youth experienced layoffs after 2008, mainly because their skills were interchangeable and easily replaceable and as a result, youth unemployment increased, although the situation has improved slightly. The unemployment rate in selected world regions remained relatively stagnant year-over-year from 2012 to 2013, however is expected to improve over the long run based on current employment trends. Economic improvement around the world is primarily evident from growth of real gross domestic product , which has been relatively positive in most countries with the exception of those in the euro area. Growth of real gross domestic product points to economic growth as well as a higher productivity within each country. On the other hand, other indicators of economic health, such as inflation, point to further economic distraught, as inflation is expected to increase globally, most prominently in non-developed countries.

Graph and download economic data for Monthly Transition Rate of All U.S. Workers From Employment to Non-Employment Due to a Layoff (EMELASA) from Jan 1978 to May 2025 about flow, labor force, labor, unemployment, employment, and USA.

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.

Graph and download economic data for Unemployment Level - Permanent Job Losers (LNS13026638) from Jan 1994 to May 2025 about job losers, 16 years +, household survey, unemployment, and USA.