The COVID-19 pandemic caused unemployment and layoffs across the world, and hit youth particularly hard. This was particularly the case in South Asia, where the employment deficit was estimated to be above 12 percent in 2020 and 2021, compared to 2019 employment levels. Meanwhile, the deficit was estimated to have turned in Western, Southern, and Northern Europe by 2022.

Reference Layer: Bureau of Labor Statistics Monthly Unemployment (latest 14 months)_This layer contains the latest 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. Most current month: August 2022 (preliminary values at the county level)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 forceData obtained from the U.S. Bureau of Labor Statistics. Data downloaded: October 21, 2022Local Area Unemployment Statistics table download: https://www.bls.gov/lau/#tablesLocal Area Unemployment FTP downloads:State and CountyNationData Notes:This layer is updated automatically when the BLS releases their most current monthly statistics. The layer always contains the most recent estimates. It is updated within days of the BLS's county release schedule. BLS releases their county statistics roughly 2 months after-the-fact. The data is joined to 2021 TIGER boundaries from the U.S. Census Bureau.Monthly values are subject to revision over time.For national values, employed plus unemployed may not sum to total labor force due to rounding.As of the January 2022 estimates released on March 18th, BLS is reporting new data for the two new census areas in Alaska - Copper River and Chugach - and historical data for the previous census area - Valdez Cordova.To better understand the different labor force statistics included in this map, see the diagram below from BLS:

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.

This datasets presents regional estimates of unemployment of Statistical Area Level 2 (SA2) regions for each quarter starting December 2010 up to September 2021. The boundaries used for the dataset follow the 2016 edition of the Australian Statistical Geography Standard (ASGS). Small Area Labour Markets (SALM) presents regional estimates of unemployment and the unemployment rate at two small area levels: Approximately 2,200 ABS SA2s, on a State/Territory and Metropolitan/Non-metropolitan basis. Estimates for the Capital City and the Rest of State are provided for the States and the Northern Territory. For approximately 540 Australian LGAs. The SALM Estimates have been smoothed using a four-quarter average to minimise the variability inherent in small area estimates. A description of the methodology used to prepare the estimates in this publication is available on the Explanatory Notes page. Caution: Highly disaggregated estimates of unemployment and the unemployment rate at the SA2 and LGA level can display significant variability and should be viewed with caution, particularly in regions where the SA4 level unemployment data are showing considerable volatility. As a result, quarter-to-quarter comparisons may not indicate actual movements in the labour market so we recommend using year-on-year comparisons. Even then, large movements in the SA2 and LGA data should be viewed with caution. The COVID-19 pandemic began to have a significant impact on the Australian labour market from March 2020, when Australia recorded its 100th COVID-19 case and the initial shutdown of non-essential services and trading restrictions took effect. Learn more about the dataset at the LMIP (Labour Market Information Portal). AURIN has spatially enabled the original data. Smoothed Estimates are not available for all SA2s and LGAs, for more information see the SALM 2016 ASGS Changeover User Guide.

This datasets presents regional estimates of unemployment of Local Government Area (LGA) regions for each quarter starting December 2010 up to September 2021. The boundaries used for the dataset follow the 2021 edition of the Australian Statistical Geography Standard (ASGS).

Small Area Labour Markets (SALM) presents regional estimates of unemployment and the unemployment rate at two small area levels:

• Approximately 2,200 ABS SA2s, on a State/Territory and Metropolitan/Non-metropolitan basis. Estimates for the Capital City and the Rest of State are provided for the States and the Northern Territory.

• For approximately 540 Australian LGAs.

The SALM Estimates have been smoothed using a four-quarter average to minimise the variability inherent in small area estimates. A description of the methodology used to prepare the estimates in this publication is available on the Explanatory Notes page.

Caution: Highly disaggregated estimates of unemployment and the unemployment rate at the SA2 and LGA level can display significant variability and should be viewed with caution, particularly in regions where the SA4 level unemployment data are showing considerable volatility. As a result, quarter-to-quarter comparisons may not indicate actual movements in the labour market so we recommend using year-on-year comparisons. Even then, large movements in the SA2 and LGA data should be viewed with caution.

The COVID-19 pandemic began to have a significant impact on the Australian labour market from March 2020, when Australia recorded its 100th COVID-19 case and the initial shutdown of non-essential services and trading restrictions took effect. Learn more about the dataset at the LMIP (Labour Market Information Portal).

AURIN has spatially enabled the original data. Smoothed Estimates are not available for all SA2s and LGAs, for more information see the SALM 2016 ASGS Changeover User Guide.

In 2023, it was estimated that over 161 million Americans were in some form of employment, while 3.64 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.

This datasets presents regional estimates of unemployment of Statistical Area Level 2 (SA2) regions for each quarter starting December 2010 up to September 2021. The boundaries used for the dataset follow the 2016 edition of the Australian Statistical Geography Standard (ASGS).

Small Area Labour Markets (SALM) presents regional estimates of unemployment and the unemployment rate at two small area levels:

• Approximately 2,200 ABS SA2s, on a State/Territory and Metropolitan/Non-metropolitan basis. Estimates for the Capital City and the Rest of State are provided for the States and the Northern Territory.

• For approximately 540 Australian LGAs.

The SALM Estimates have been smoothed using a four-quarter average to minimise the variability inherent in small area estimates. A description of the methodology used to prepare the estimates in this publication is available on the Explanatory Notes page.

Caution: Highly disaggregated estimates of unemployment and the unemployment rate at the SA2 and LGA level can display significant variability and should be viewed with caution, particularly in regions where the SA4 level unemployment data are showing considerable volatility. As a result, quarter-to-quarter comparisons may not indicate actual movements in the labour market so we recommend using year-on-year comparisons. Even then, large movements in the SA2 and LGA data should be viewed with caution.

The COVID-19 pandemic began to have a significant impact on the Australian labour market from March 2020, when Australia recorded its 100th COVID-19 case and the initial shutdown of non-essential services and trading restrictions took effect. Learn more about the dataset at the LMIP (Labour Market Information Portal).

AURIN has spatially enabled the original data. Smoothed Estimates are not available for all SA2s and LGAs, for more information see the SALM 2016 ASGS Changeover User Guide.

This graph shows the unemployment rate forecasts following the outbreak of the coronavirus (COVID-19) in France from the first quarter of 2020 to the fourth quarter of 2025. OECD predictions estimated that unemployment will increase gradually in each quarter of 2022 and 2023, before a decrease in 2024.

The seasonally-adjusted national unemployment rate is measured on a monthly basis in the United States. In October 2024, the national unemployment rate was at 4.1 percent. Seasonal adjustment is a statistical method of removing the seasonal component of a time series that is used when analyzing non-seasonal trends. U.S. monthly unemployment rate According to the Bureau of Labor Statistics - the principle fact-finding agency for the U.S. Federal Government in labor economics and statistics - unemployment decreased dramatically between 2010 and 2019. This trend of decreasing unemployment followed after a high in 2010 resulting from the 2008 financial crisis. However, after a smaller financial crisis due to the COVID-19 pandemic, unemployment reached 8.1 percent in 2020. As the economy recovered, the unemployment rate fell to 5.3 in 2021, and fell even further in 2022. Additional statistics from the BLS paint an interesting picture of unemployment in the United States. In November 2023, the states with the highest (seasonally adjusted) unemployment rate were the Nevada and the District of Columbia. Unemployment was the lowest in Maryland, at 1.8 percent. Workers in the agricultural and related industries suffered the highest unemployment rate of any industry at seven percent in December 2023.

Abstract copyright UK Data Service and data collection copyright owner.BackgroundThe Labour Force Survey (LFS) is a unique source of information using international definitions of employment and unemployment and economic inactivity, together with a wide range of related topics such as occupation, training, hours of work and personal characteristics of household members aged 16 years and over. It is used to inform social, economic and employment policy. The Annual Population Survey, also held at the UK Data Archive, is derived from the LFS.The LFS was first conducted biennially from 1973-1983, then annually between 1984 and 1991, comprising a quarterly survey conducted throughout the year and a 'boost' survey in the spring quarter. From 1992 it moved to a quarterly cycle with a sample size approximately equivalent to that of the previous annual data. Northern Ireland was also included in the survey from December 1994. Further information on the background to the QLFS may be found in the documentation.The UK Data Service also holds a Secure Access version of the QLFS (see below); household datasets; two-quarter and five-quarter longitudinal datasets; LFS datasets compiled for Eurostat; and some additional annual Northern Ireland datasets.LFS DocumentationThe documentation available from the Archive to accompany LFS datasets largely consists of the latest version of each user guide volume alongside the appropriate questionnaire for the year concerned (the latest questionnaire available covers July-September 2022). Volumes are updated periodically, so users are advised to check the latest documents on the ONS Labour Force Survey - User Guidance pages before commencing analysis. This is especially important for users of older QLFS studies, where information and guidance in the user guide documents may have changed over time.LFS response to COVID-19From April 2020 to May 2022, additional non-calendar quarter LFS microdata were made available to cover the pandemic period. The first additional microdata to be released covered February to April 2020 and the final non-calendar dataset covered March-May 2022. Publication then returned to calendar quarters only. Within the additional non-calendar COVID-19 quarters, pseudonymised variables Casenop and Hserialp may contain a significant number of missing cases (set as -9). These variables may not be available in full for the additional COVID-19 datasets until the next standard calendar quarter is produced. The income weight variable, PIWT, is not available in the non-calendar quarters, although the person weight (PWT) is included. Please consult the documentation for full details.Occupation data for 2021 and 2022 data filesThe ONS has identified an issue with the collection of some occupational data in 2021 and 2022 data files in a number of their surveys. While they estimate any impacts will be small overall, this will affect the accuracy of the breakdowns of some detailed (four-digit Standard Occupational Classification (SOC)) occupations, and data derived from them. Further information can be found in the ONS article published on 11 July 2023: Revision of miscoded occupational data in the ONS Labour Force Survey, UK: January 2021 to September 2022.2024 ReweightingIn February 2024, reweighted person-level data from July-September 2022 onwards were released. Up to July-September 2023, only the person weight was updated (PWT23); the income weight remains at 2022 (PIWT22). The 2023 income weight (PIWT23) was included from the October-December 2023 quarter. Users are encouraged to read the ONS methodological note of 5 February, Impact of reweighting on Labour Force Survey key indicators: 2024, which includes important information on the 2024 reweighting exercise.End User Licence and Secure Access QLFS dataTwo versions of the QLFS are available from UKDS. One is available under the standard End User Licence (EUL) agreement, and the other is a Secure Access version. The EUL version includes country and Government Office Region geography, 3-digit Standard Occupational Classification (SOC) and 3-digit industry group for main, second and last job (from July-September 2015, 4-digit industry class is available for main job only).The Secure Access version contains more detailed variables relating to:age: single year of age, year and month of birth, age completed full-time education and age obtained highest qualification, age of oldest dependent child and age of youngest dependent childfamily unit and household: including a number of variables concerning the number of dependent children in the family according to their ages, relationship to head of household and relationship to head of familynationality and country of originfiner detail geography: including county, unitary/local authority, place of work, Nomenclature of Territorial Units for Statistics 2 (NUTS2) and NUTS3 regions, and whether lives and works in same local authority district, and other categories;health: including main health problem, and current and past health problemseducation and apprenticeship: including numbers and subjects of various qualifications and variables concerning apprenticeshipsindustry: including industry, industry class and industry group for main, second and last job, and industry made redundant fromoccupation: including 5-digit industry subclass and 4-digit SOC for main, second and last job and job made redundant fromsystem variables: including week number when interview took place and number of households at addressother additional detailed variables may also be included.The Secure Access datasets (SNs 6727 and 7674) have more restrictive access conditions than those made available under the standard EUL. Prospective users will need to gain ONS Accredited Researcher status, complete an extra application form and demonstrate to the data owners exactly why they need access to the additional variables. Users are strongly advised to first obtain the standard EUL version of the data to see if they are sufficient for their research requirements. Latest edition informationFor the second edition (June 2022), 2022 weighting variable PWT22 was added to the study, and the 2020 weight removed. Main Topics:The QLFS questionnaire comprises a 'core' of questions which are included in every survey, together with some 'non-core' questions which vary from quarter to quarter.The questionnaire can be split into two main parts. The first part contains questions on the respondent's household, family structure, basic housing information and demographic details of household members. The second part contains questions covering economic activity, education and health, and also may include a few questions asked on behalf of other government departments (for example the Department for Work and Pensions and the Home Office). Until 1997, the questions on health covered mainly problems which affected the respondent's work. From that quarter onwards, the questions cover all health problems. Detailed questions on income have also been included in each quarter since 1993. The basic questionnaire is revised each year, and a new version published, along with a transitional version that details changes from the previous year's questionnaire. Four sampling frames are used. See documentation for details. Face-to-face interview Telephone interview The first interview is conducted face-to-face, and subsequent interviews by telephone where possible. 2021 ABSENTEEISM ACADEMIC ACHIEVEMENT ACCIDENTS AT WORK ADULT EDUCATION ADVANCED LEVEL EXAM... ADVANCED SUPPLEMENT... AGE ALLERGIES APPRENTICESHIP ATTITUDES BONUS PAYMENTS BUSINESS AND TECHNO... CARDIOVASCULAR DISE... CARE OF DEPENDANTS CERTIFICATE OF SECO... CERTIFICATE OF SIXT... CHILD BENEFITS CHILD CARE CHILDREN CHRONIC ILLNESS CITY AND GUILDS OF ... COHABITATION CONDITIONS OF EMPLO... COVID 19 DEBILITATIVE ILLNESS DEGREES DEPRESSION DIABETES DIGESTIVE SYSTEM DI... DISABILITIES DISABLED PERSONS DISMISSAL DISTANCE LEARNING DOMESTIC RESPONSIBI... EARLY RETIREMENT ECONOMIC ACTIVITY EDUCATIONAL BACKGROUND EDUCATIONAL CERTIFI... EDUCATIONAL COURSES EDUCATIONAL FEES EDUCATIONAL INSTITU... EDUCATIONAL LEVELS EDUCATIONAL OPPORTU... EMPLOYEES EMPLOYER SPONSORED ... EMPLOYMENT EMPLOYMENT HISTORY EMPLOYMENT PROGRAMMES EMPLOYMENT SERVICES ENDOCRINE DISORDERS EPILEPSY ETHNIC GROUPS FAMILIES FAMILY BENEFITS FAMILY MEMBERS FIELDS OF STUDY FULL TIME EMPLOYMENT FURNISHED ACCOMMODA... FURTHER EDUCATION GENERAL CERTIFICATE... GENERAL NATIONAL VO... GENERAL SCOTTISH VO... HEADS OF HOUSEHOLD HEALTH HEARING IMPAIRMENTS HIGHER EDUCATION HIGHER EDUCATION IN... HIGHER NATIONAL CER... HOLIDAY LEAVE HOME BASED WORK HOME OWNERSHIP HOURS OF WORK HOUSEHOLDS HOUSING BENEFITS HOUSING TENURE IMMIGRATION IN SERVICE TRAINING INCOME INDUSTRIES INVOLUNTARY SHORT T... JOB CHANGING JOB DESCRIPTION JOB HUNTING JOB SEEKER S ALLOWANCE LABOUR AND EMPLOYMENT LABOUR FORCE LANDLORDS LEARNING DISABILITIES LEAVE LONGTERM UNEMPLOYMENT Labour and employment MANAGERS MARITAL STATUS MATERNITY LEAVE MATERNITY PAY MENTAL DISORDERS MUSCULOSKELETAL DIS... NATIONAL IDENTITY NATIONAL VOCATIONAL... NATIONALITY NERVOUS SYSTEM DISE... OCCUPATIONAL QUALIF... OCCUPATIONAL SAFETY OCCUPATIONAL STATUS OCCUPATIONAL TRAINING OCCUPATIONS ORDINARY LEVEL EXAM... ORDINARY NATIONAL C... OVERTIME PART TIME COURSES PART TIME EMPLOYMENT PATERNITY LEAVE PENSIONS PHOBIAS PLACE OF BIRTH PLACE OF RESIDENCE PRIVATE PENSIONS PRIVATE SECTOR PUBLIC HEALTH RISKS PUBLIC SECTOR QUALIFICATIONS REBATES RECRUITMENT REDUNDANCY REDUNDANCY PAY RELIGIOUS AFFILIATION RENTED ACCOMMODATION RESIDENTIAL MOBILITY RESPIRATORY TRACT D... RETIREMENT ROYAL SOCIETY OF AR... SANDWICH COURSES SCOTTISH CERTIFICAT... SCOTTISH VOCATIONAL... SCOTTISH VOCATIONAL... SEASONAL EMPLOYMENT SELF EMPLOYED SEX SHARED HOME OWNERSHIP SHIFT WORK SICK LEAVE SICK PAY SICK PERSONS SICKNESS AND DISABI... SKIN DISEASES SMALL BUSINESSES SOCIAL HOUSING SOCIAL SECURITY BEN... SOCIO ECONOMIC STATUS SPEECH IMPAIRMENTS

Abstract copyright UK Data Service and data collection copyright owner.

The Crime Survey for England and Wales (CSEW) asks a sole adult in a random sample of households about their, or their household's, experience of crime victimisation in the previous 12 months. These are recorded in the victim form data file (VF). A wide range of questions are then asked, covering demographics and crime-related subjects such as attitudes to the police and the criminal justice system (CJS). These variables are contained within the non-victim form (NVF) data file. In 2009, the survey was extended to children aged 10-15 years old; one resident of that age range was also selected from the household and asked about their experience of crime and other related topics. The first set of children's data covered January-December 2009 and is held separately under SN 6601. From 2009-2010, the children's data cover the same period as the adult data and are included with the main study.

The Telephone-operated Crime Survey for England and Wales (TCSEW) became operational on 20 May 2020. It was a replacement for the face-to-face CSEW, which was suspended on 17 March 2020 because of the coronavirus (COVID-19) pandemic. It was set up with the intention of measuring the level of crime during the pandemic. As the pandemic continued throughout the 2020/21 survey year, questions have been raised as to whether the year ending March 2021 TCSEW is comparable with estimates produced in earlier years by the face-to-face CSEW. The ONS Comparability between the Telephone-operated Crime Survey for England and Wales and the face-to-face Crime Survey for England and Wales report explores those factors that may have a bearing on the comparability of estimates between the TCSEW and the former CSEW. These include survey design, sample design, questionnaire changes and modal changes.

More general information about the CSEW may be found on the ONS Crime Survey for England and Wales web page and for the previous BCS, from the GOV.UK BCS Methodology web page.

History - the British Crime Survey

The CSEW was formerly known as the British Crime Survey (BCS), and has been in existence since 1981. The 1982 and 1988 BCS waves were also conducted in Scotland (data held separately under SNs 4368 and 4599). Since 1993, separate Scottish Crime and Justice Surveys have been conducted. Up to 2001, the BCS was conducted biennially. From April 2001, the Office for National Statistics took over the survey and it became the CSEW. Interviewing was then carried out continually and reported on in financial year cycles. The crime reference period was altered to accommodate this.

Secure Access CSEW data
In addition to the main survey, a series of questions covering drinking behaviour, drug use, self-offending, gangs and personal security, and intimate personal violence (IPV) (including stalking and sexual victimisation) are asked of adults via a laptop-based self-completion module (questions may vary over the years). Children aged 10-15 years also complete a separate self-completion questionnaire. The questionnaires are included in the main documentation, but the data are only available under Secure Access conditions (see SN 7280), not with the main study. In addition, from 2011 onwards, lower-level geographic variables are also available under Secure Access conditions (see SN 7311).

New methodology for capping the number of incidents from 2017-18
The CSEW datasets available from 2017-18 onwards are based on a new methodology of capping the number of incidents at the 98th percentile. Incidence variables names have remained consistent with previously supplied data but due to the fact they are based on the new 98th percentile cap, and old datasets are not, comparability has been lost with years prior to 2012-2013. More information can be found in the 2017-18 User Guide (see SN 8464) and the article ‘Improving victimisation estimates derived from the Crime Survey for England and Wales’.

Main Topics:

The overall length of the survey needed to be shortened for telephone operation from an average of around 50 minutes down to 25 minutes. As a result, it was felt that the survey should only carry questions required to provide key estimates of crime (victimisation and prevalence rates of crimes recorded by the survey during the coronavirus (COVID-19) pandemic and the previous 12 months), or those questions which would provide essential information during the pandemic.
Some questions considered sufficiently important to measure during the pandemic were omitted from the final questionnaire following ethical consideration. As a result, estimates are not available in relation to sexual assault, partner abuse or abuse during childhood. This includes the preferred measures of domestic abuse and domestic violence.

An October 2021 report examined the number of job losses in the out-of-home leisure economy due to the coronavirus (COVID-19) pandemic in the United Kingdom in 2020. According to the study's estimates, the food-led subsector suffered the most from within the out-of-home leisure industry, having lost roughly 241 thousand jobs in the first year of the pandemic.

This datasets presents regional estimates of the labour force of Statistical Area Level 2 (SA2) regions for each quarter starting December 2010 up to September 2021. The boundaries used for the dataset follow the 2016 edition of the Australian Statistical Geography Standard (ASGS). Small Area Labour Markets (SALM) presents regional estimates of unemployment and the unemployment rate at two small area levels: Approximately 2,200 ABS SA2s, on a State/Territory and Metropolitan/Non-metropolitan basis. Estimates for the Capital City and the Rest of State are provided for the States and the Northern Territory. For approximately 540 Australian LGAs. The SALM Estimates have been smoothed using a four-quarter average to minimise the variability inherent in small area estimates. A description of the methodology used to prepare the estimates in this publication is available on the Explanatory Notes page. Caution: Highly disaggregated estimates of unemployment and the unemployment rate at the SA2 and LGA level can display significant variability and should be viewed with caution, particularly in regions where the SA4 level unemployment data are showing considerable volatility. As a result, quarter-to-quarter comparisons may not indicate actual movements in the labour market so we recommend using year-on-year comparisons. Even then, large movements in the SA2 and LGA data should be viewed with caution. The COVID-19 pandemic began to have a significant impact on the Australian labour market from March 2020, when Australia recorded its 100th COVID-19 case and the initial shutdown of non-essential services and trading restrictions took effect. Learn more about the dataset at the LMIP (Labour Market Information Portal). AURIN has spatially enabled the original data. Smoothed Estimates are not available for all SA2s and LGAs, for more information see the SALM 2016 ASGS Changeover User Guide.

In November 2024, the unemployment rate in Russia exceeded two percent, having stayed on the same level as in the previous month. By comparison, 3.7 percent of the workforce aged 15 years and older nationwide were unemployed in the corresponding period two years prior. In 2022, the annual unemployment rate in Russia was measured at approximately 3.2 percent. Causes of unemployment in Russia The country’s labor market situation deteriorated in the summer of 2020 due to the coronavirus (COVID-19) pandemic. The number of jobs contributed by the travel and tourism industry decreased from 3.3 million to 3 million between 2019 and 2022, though the figures started to recuperate again in 2023. Furthermore, Russia has witnessed an exodus of companies due to the invasion of Ukraine in 2022. Leading international companies like McDonald’s, Renault Group, and PepsiCo suspended their operations in the country, thus putting thousands of employees in Russia at risk of unemployment. Russia’s unemployment in global perspective Russia’s unemployment rate is lower than in most other G20 countries. This is largely due to a low fertility rate in the 1990s which has resulted in a demographic dip and left the country with fewer young workers actively seeking employment. Moreover, Russia’s weak social protection, as expressed by unemployment benefits lower than in most European countries, encourages people to find a new job rapidly. An estimated 30 million Russians were not officially registered as unemployed by working in the shadow economy as of 2021.

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

Unemployment Rate in China increased to 5.40 percent in February from 5.20 percent in January of 2025. This dataset provides - China Unemployment Rate - actual values, historical data, forecast, chart, statistics, economic calendar and news.

According to one of the scenarios, it is assumed that the outbreak of the coronavirus (COVID-19) will cause a deeper recession in Poland. It is estimated that by the end of 2020, GDP will fall to -4 percent, the inflation rate will reach 2.1 percent and unemployment 13 percent. The inflation rate will be significantly affected by global oil prices.

For further information about the coronavirus (COVID-19) pandemic, please visit our dedicated Facts and Figures page.

In September 2024, the global PMI amounted to 47.5 for new export orders and 48.8 for manufacturing. The manufacturing PMI was at its lowest point in August 2020. It decreased over the last months of 2022 after the effects of the Russia-Ukraine war and rising inflation hit the world economy, and remained around 50 since.

As of October 2024, there were 133.89 million full-time employees in the United States. This is a slight decrease from the previous month, when there were 134.15 million full-time employees. The impact COVID-19 on employment In December 2019, the COVID-19 virus began its spread across the globe. Since being classified as a pandemic, the virus caused a global health crisis that has taken the lives of millions of people worldwide. The COVID-19 pandemic changed many facets of society, most significantly, the economy. In the first years, many businesses across all industries were forced to shut down, with large numbers of employees being laid off. The economy continued its recovery in 2022 with the nationwide unemployment rate returning to a more normal 3.4 percent as of April 2023. Unemployment benefits Because so many people in the United States lost their jobs, record numbers of individuals applied for unemployment insurance for the first time. As an early response to this nation-wide upheaval, the government issued relief checks and extended the benefits paid by unemployment insurance. In May 2020, the amount of unemployment insurance benefits paid rose to 23.73 billion U.S. dollars. As of December 2022, this value had declined to 2.24 billion U.S. dollars.

As of November 2021, the U.S. goverment dedicated 26.46 percent of the GDP to soften the effects of the coronavirus pandemic. This translates to stimulus packages worth 5.54 trillion U.S. dollars

Economic impact of the Coronavirus pandemic

The impact of the COVID-19 pandemic was felt throughout the whole world. Lockdowns forced many industries to close completely for many months and restrictions were put on almost all economic activity. In 2020, the worldwide GDP loss due to Covid was 6.7 percent. The global unemployment rate rocketed to 6.47 percent in 2020 and confidence in governments’ ability to deal with the crisis diminished significantly.

Governmental response

In order to stimulate the economies and bring them out of recession, many countries have decided to release so called stimulus packages. These are fiscal and monetary policies used to support the recovery process. Through application of lower taxes and interest rates, direct financial aid, or facilitated access to funding, the governments aim to boost the employment, investment, and demand.

Stimulus packages

Until November 2021, Japan has dedicated the largest share of the GDP to stimulus packages among the G20 countries, with 53.69 percent (308 trillion Yen or 2.71 trillion U.S. dollars). While the first help package aimed at maintaining employment and securing businesses, the second and third ones focused more on structural changes and positive developments in the country in the post-pandemic future.