Unemployment Rate in South Africa increased to 33.20 percent in the second quarter of 2025 from 32.90 percent in the first quarter of 2025. This dataset provides - South Africa Unemployment Rate - actual values, historical data, forecast, chart, statistics, economic calendar and news.

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 CENTRAL STATISTICAL ORGANIZATION OF YEMEN (CSO)

The primary objective of LFS 2013-2014 was to provide current data on the employment and unemployment situation at national and governorate level using the preliminary version of the new standards concerning statistics of work, employment and labour underutilization on adopted by the 19th International Conference of Labour Statisticians (Geneva, October 2013).

---> The survey was then designed to meet five main measurement objectives as follows: 1- To provide current data on the number of employed, unemployed, and underemployed, and their demographic and social characteristics, including the size of women's participation in economic activity with a view to future policies in expanding their participation in the labour market. 2- To collect data on qualifications of the labour force and participation in training programmes of the youth population and other data requirements for improving the performance of employers through knowledge on the levels of skill available to them. 3- To measure the volume and characteristics of labour migration of Yemenis outside the country. 4- To provide information on the amount of wages and employment-related income in different occupations, branches of economic activity and sectors of employment. 5- To collect appropriate data for evaluating the microfinance projects funded through the Social Fund for Development.

Given the extent and diversity of data requirements, the survey was designed to spread over a one-year period, built around the five objectives of the survey. The core labour force survey was conducted throughout the four quarters of the survey period and incorporated the measurement of income from employment along the conventional items of data collection. Data on qualifications and participation in training was collected on the third quarter and on labour migration on the second quarter of the survey programme. Data collection on microfinance was undertaken as a separate survey over the four quarters.

Geographic coverage

Survey operations were carried out in all governorates except parts where recent events have disturbed the normal course of economic activity. In these circumstances, special procedures were used for compensation, either through the replacement of those areas with other areas having otherwise similar characteristics in the respective strata or through the adjustment of the sampling weights for missing values. There were 14 such cases, 5 each in quarters 1 and 4, and 2 each in quarters 2 and 3.

Analysis unit

1- Household/family. 2- Individual/person.

Universe

The labour force survey covered the civilian non-institutional settled population excluding certain areas with difficult access or low population densities, in particular, the nomad population, displaced populations who are homeless, population living in public housing (boarding, hotels, prisons, hospitals, etc.), individuals enlisted in the Armed Forces, who are residing permanently within camps and do not spend most days of the year with their families. Similarly, for marine crews and expatriates outside the country and other categories of persons in remote islands.

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 CENTRAL STATISTICAL ORGANIZATION OF YEMEN (CSO)

The sample design of the labour force survey of Yemen 2013-2014 is a two-stage stratified sample of enumeration areas in the first stage of sampling and a fixed number of sample households at the second stage of sampling. The resulting sample is spread evenly over the four quarters of the survey period.

Accordingly, the Central Statistics Organization (CSO) has drawn a stratified sample of census enumeration areas recomposed as primary sampling units (PSUs). Sample selection has been made with probability proportional to the number of households as determined in the 2004 population on census. In the second stage of sampling, after relisting of the sample enumeration areas, a fixed number of households (16 sample households) are drawn as clusters with equal probability from each sample enumeration area. The strata consist of the urban and rural areas of the 21 governorates in Yemen.

According to the sample design, urban areas are oversampled and rural areas under-sampled. This is because a relatively larger sample size is required in urban areas where heterogeneity is greater in comparison with rural areas. Also, because the cost of transportation and field operations is relatively greater in rural areas, it is more cost effective to under sample the rural areas relative to the less costly operations in urban areas. The differential sampling rates are then corrected through the sample weights so that the final results accurately reflect to the overall employment pattern.

The sample selection of the cluster of 16 households in each sample enumeration area was drawn after fresh listing of the totality of the households living in the sample enumeration area at the time of listing. This procedure updates the census information that dates back to 2004. The listing operations are carried out in each quarter before survey interviewing. The updated lists are send to CSO in Sana'a for data entry and sample selection of households for transmission to the survey team in each area. Instructions were given so that sample households that could not be found in the field or were absent or refused to be interview should not be substituted with other households as this procedure may introduce bias in the results. Instructions were also given that in cases where the minimum number of households in the sample enumeration areas was to be found to be less than the required 16 in each quarter, all households in the enumeration area should be taken in the sample.

The total sample size was determined on the basis of the requirement of producing national estimates of the unemployment rate with 1.5% margin of errors at the national level, assuming an overall non-response rate of 15%, and a design effect of 3. For the determination of the national sample size, the expected unemployment rate was set at 15% and the expected number of sample households to reach one person of working age, 15 years old and over, in the labour force was set at 0.6.

A more detailed description of the allocation of sample across governorates is provided in the report document available among external resources in English.

Mode of data collection

Face-to-face [f2f]

Research instrument

The questionnaire of the Yemen LFS 2013-2014 was designed on the basis of the ILO model LFS questionnaire (version A) and other national LFS questionnaires used in the region. The draft questionnaire was field tested with six households in Sana’a, each member of the field staff interviewing one sample household in his or her area. The experience gained in the field test was reviewed and led to some modifications of the draft questionnaire.

Apart from the cover page and the back page, the core LFS questionnaire contains 52 questions. There are 11 questions on the social and demographic characteristics of the household members in the household roster. In the individual questionnaire addressed to the working age population 15 years of age or older, there are 3 questions to identify the employed persons and 19 questions on their employment characteristics including timerelated underemployment followed by 8 additional questions on income from employment. The individual questionnaire also includes 5 questions to identify the unemployment and the potential labour force and 5 follow-up questions on unemployment characteristics.

Cleaning operations

----> Raw Data

Data processing involved data entry, coding, editing and tabulation of the survey results. Data entry was carried out in parallel with the interviewing of sample households. It was conducted at the Central Statistical Organization headquarter in Sana'a where all data processing operations except tabulation were centralized.

The supervisory staff of the data entry operations was responsible for editing the questionnaires before actual data entry. Editing at this stage involved review of the questionnaire regarding its filled-in contents including ensuring that there is no missing block of information for household members aged 15 years old and over and correct coding of occupation, branch of economic activity and other variables.

The data files were further processed at ILO headquarters in Geneva. They were first converted into a single file with 86,778 records and augmented with several fields, in particular, the sampling weights (“weight”) and the key derived variables: employed (E), unemployed (U), time-related underemployment (TRU), potential labour force (PLF) as well as other derived variables such as informal sector employment (IS) and informal employment (IE).

----> 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

Revenue in the Temporary Employment Agency industry is anticipated to drop at a compound annual rate of 4% in the five years through 2024 to €236.5 billion. The COVID-19 outbreak meant key employers of temporary workers in the hospitality and tourist sector shut their doors, and companies froze hiring due to economic uncertainty - a sizeable blow to revenue in the three years through 2022. Workers on temporary contracts represented a significant chuck of employment losses in all quarters of 2020. According to Eurostat data, temporary employment declined across Europe in the four years from 2017 to 2020, dipping from 13.8% to 11.9%. Since COVID-19 has slowed, companies have resumed hiring as confidence levels have been restored and vacancy levels have soared. An increasingly tight labour market encourages employers to rely on temporary employment placement agencies to fight in an increasingly competitive market. Several countries rank highly in terms of temporary workers with a large short-term job market. In 2022, the Netherlands and Spain have more than 15% of employed people under temporary contracts, according to Eurostat. Industry revenue is expected to shrink by 1.6% in 2024. Revenue is expected to grow at an annual rate of 4.5% in the five years through 2029 to €295.4 billion. With the labour market is likely to remain tight in many countries due to skill mismatches, employers will keep turning to placement agencies for their databases to track and identify the right candidates. Companies will lean on temporary hires as the economic outlook remains unclear and inflation keeps squeezing budgets. The automation of more routine jobs will be a threat to some long-standing temporary jobs. Across Europe, countries that traditionally rely on a strong network of short-term workers are implanting policies that may disrupt or expand services. Spain has already introduced reforms that are taking effect to increase permanent positions and remove temporary contracts, while Italy is expanding its voucher scheme to encourage temporary hires.

Abstract

The Labour Force Survey (LFS) 2013-14 is the second such survey that has been carried out in the last 15 years in Yemen. Similar to the first survey in 1999, the LFS 2013-14 was conducted by the Central Statistical Organization with assistance from the International Labour Office. More recently, CSO has conducted a population census in 2004 and a household child labour survey of adults and children in 2010. The primary objective of LFS 2013-14 was to provide current data on the employment and unemployment situation at national and governorate level using the preliminary version of the new standards concerning statistics of work, employment and labour underutilization adopted by the 19th International Conference of Labour Statisticians (Geneva, October 2013).

After reprocessing the LFS 2013-14 data according to the international standards of 1982 (13th ICLS) to make the results comparable to the definitions used in the population census of 2004 and the household child labour survey of adults and children conducted in 2010, the results show that the labour force participation rate has somewhat increased during the ten-year period from 2004 to 2013-14. Both the number of unemployed and the unemployment rate, measured on a comparable basis, show a slight increase from 2004 to 2010 before a sharp decrease in 2013-14.

The survey covered all civilian non-institutional households living in urban and rural areas of the country. During field operations, certain sample areas could be covered due to particular circumstances.

Geographic coverage

National Coverage.

Analysis unit

• Individuals

• Households

Universe

The survey covered the civilian non-institutional settled population excluding certain areas with difficult access or low population densities, in particular, the nomad population, displaced populations who are homeless, population living in public housing (boarding, hotels, prisons, hospitals, etc.), individuals enlisted in the Armed Forces, who are residing permanently within camps and do not spend most days of the year with their families. Similarly, for marine crews and expatriates outside the country and other categories of persons in remote islands.

Kind of data

Sample survey data [ssd]

Sampling procedure

The sample design is a two-stage stratified sample of enumeration areas in the first stage of sampling and a fixed number of sample households at the second stage of sampling. The resulting sample is spread evenly over the four quarters of the survey period.

Accordingly, the Central Statistics Organization (CSO) has drawn a stratified sample of census enumeration areas recomposed as primary sampling units (PSUs). Sample selection has been made with probability proportional to the number of households as determined in the 2004 population census. In the second stage of sampling, after relisting of the sample enumeration areas, a fixed number of households (16 sample households) are drawn as clusters with equal probability from each sample enumeration area. The strata consist of the urban and rural areas of the 21 governorates in Yemen.

According to the sample design, urban areas are oversampled and rural areas under-sampled. This is because a relatively larger sample size is required in urban areas where heterogeneity is greater in comparison with rural areas. Also, because the cost of transportation and field operations is relatively greater in rural areas, it is more cost effective to under sample the rural areas relative to the less costly operations in urban areas. The differential sampling rates are then corrected through the sample weights so that the final results accurately reflect to the overall employment pattern.

The sample selection of the cluster of 16 households in each sample enumeration area was drawn after fresh listing of the totality of the households living in the sample enumeration area at the time of listing. This procedure updates the census information that dates back to 2004. The listing operations are carried out in each quarter before survey interviewing. The updated lists are send to CSO in Sana'a for data entry and sample selection of households for transmission to the survey team in each area. Instructions were given so that sample households that could not be found in the field or were absent or refused to be interview should not be substituted with other households as this procedure may introduce bias in the results. Instructions were also given that in cases where the minimum number of

households in the sample enumeration areas was to be found to be less than the required 16 in each quarter, all households in the enumerate on area should be taken in the sample.

The sample size in terms of number of sample households is given in Table B2 below for each quarter and for urban and rural areas separately. The effective sample size was lower due to non-response and other problems of coverage. 13376 households at national level (3344 per quarter), where 6656 were urban (1664 per quarter) and 6720 were rural (1680 per quarter).

The total sample size was determined on the basis of the requirement of producing national estimates of the unemployment rate with 1.5% margin of errors at the national level, assuming an overall non-response rate of 15%, and a design effect of 3. For the determination of the national sample size, the expected unemployment rate was set at 15% and the expected number of sample households to reach one person of working age, 15 years old and over, in the labour force was set at 0.6.

Mode of data collection

Face-to-face [f2f]

Research instrument

The questionnaire of the Yemen LFS 2013-14 was designed on the basis of the ILO model LFS questionnaire (version A) and other national LFS questionnaires used in the region. The draft questionnaire was field tested with six households in Sana’a, each member of the field staff interviewing one sample household in his or her area. The experience gained in the field test was reviewed and led to some modifications of the draft questionnaire. The English version of the final questionnaire is reproduced in Annex C of the revised report.

Apart from the cover page and the back page, the core LFS questionnaire contains 52 questions. There are 11 questions on the social and demographic characteristics of the household members in the household roster. In the individual questionnaire addressed to the working age population on 15 years of age or older, there are 3 questions to identify the employed persons and 19 questions on their employment characteristics including time-related underemployment followed by 8 additional questions on income from employment. The individual questionnaire also includes 5 questions to identify the unemployment and the potential labour force and 5 follow-up questions on unemployment characteristics.

Cleaning operations

Data entry was carried out in parallel with the interviewing of sample households. It was conducted at the Central Statistical Organization headquarter in Sana’a where all data processing operations except tabulation were centralized.

The supervisory staff of the data entry operations was responsible for editing the questionnaires before actual data entry. Editing at this stage involved review of the questionnaire regarding its filled-in contents including ensuring that there is no missing block of information for household members aged 15 years old and over and correct coding of occupation, branch of economic activity and other variables.

Occupation was coded at the 6-digit level using the International Standard Classification of Occupations (ISCO-88). Branch of economic activity was coded at the 5-digit level, based on the International Industrial Classification of All Economic Activities (ISIC Rev3.1).

The data files were further processed at ILO headquarters in Geneva. They were first converted into a single file with 86,778 records and augmented with several fields, in particular, the sampling weights (“weight”) and the key derived variables: employed (E), unemployed (U), time-related underemployment (TRU), potential labour force (PLF) as well as other derived variables such as informal sector employment (IS) and informal employment (IE).

The following rounding rule was adopted for the presentation of the results. Estimates of levels are rounded to three zeros (’000) for values equal or above 1000. Estimates of percentage rates are rounded to the first decimal point.

Sampling error estimates

Sampling errors arise due to the fact that the survey does not cover all elements of the population, but only a selected portion. The sampling error of an estimate is based on the difference between the estimate and the value that would have been obtained on the basis of a complete count of the population under otherwise identical conditions.

Knowing about the magnitude of sampling errors is crucial for interpreting the survey results. It allows decision on the precision of the estimates and on the degree of confidence that may be attached to them, especially relevant in the case of small population subgroups for which the survey results may not be statistically significant due to the small number of observations on which the estimates may be based. Information on sampling errors is also crucial for sample design for future surveys.

In principle, sampling errors may be decomposed into two components: (i) sampling bias; and (ii) sampling variance. Sampling bias reflects the systematic error that may occur due to the failures of the sample design, for example, certain elements of the population receiving zero probability

Revenue in the Temporary Employment Agency industry is anticipated to drop at a compound annual rate of 4% in the five years through 2024 to €236.5 billion. The COVID-19 outbreak meant key employers of temporary workers in the hospitality and tourist sector shut their doors, and companies froze hiring due to economic uncertainty - a sizeable blow to revenue in the three years through 2022. Workers on temporary contracts represented a significant chuck of employment losses in all quarters of 2020. According to Eurostat data, temporary employment declined across Europe in the four years from 2017 to 2020, dipping from 13.8% to 11.9%. Since COVID-19 has slowed, companies have resumed hiring as confidence levels have been restored and vacancy levels have soared. An increasingly tight labour market encourages employers to rely on temporary employment placement agencies to fight in an increasingly competitive market. Several countries rank highly in terms of temporary workers with a large short-term job market. In 2022, the Netherlands and Spain have more than 15% of employed people under temporary contracts, according to Eurostat. Industry revenue is expected to shrink by 1.6% in 2024. Revenue is expected to grow at an annual rate of 4.5% in the five years through 2029 to €295.4 billion. With the labour market is likely to remain tight in many countries due to skill mismatches, employers will keep turning to placement agencies for their databases to track and identify the right candidates. Companies will lean on temporary hires as the economic outlook remains unclear and inflation keeps squeezing budgets. The automation of more routine jobs will be a threat to some long-standing temporary jobs. Across Europe, countries that traditionally rely on a strong network of short-term workers are implanting policies that may disrupt or expand services. Spain has already introduced reforms that are taking effect to increase permanent positions and remove temporary contracts, while Italy is expanding its voucher scheme to encourage temporary hires.

Revenue in the Temporary Employment Agency industry is anticipated to drop at a compound annual rate of 4% in the five years through 2024 to €236.5 billion. The COVID-19 outbreak meant key employers of temporary workers in the hospitality and tourist sector shut their doors, and companies froze hiring due to economic uncertainty - a sizeable blow to revenue in the three years through 2022. Workers on temporary contracts represented a significant chuck of employment losses in all quarters of 2020. According to Eurostat data, temporary employment declined across Europe in the four years from 2017 to 2020, dipping from 13.8% to 11.9%. Since COVID-19 has slowed, companies have resumed hiring as confidence levels have been restored and vacancy levels have soared. An increasingly tight labour market encourages employers to rely on temporary employment placement agencies to fight in an increasingly competitive market. Several countries rank highly in terms of temporary workers with a large short-term job market. In 2022, the Netherlands and Spain have more than 15% of employed people under temporary contracts, according to Eurostat. Industry revenue is expected to shrink by 1.6% in 2024. Revenue is expected to grow at an annual rate of 4.5% in the five years through 2029 to €295.4 billion. With the labour market is likely to remain tight in many countries due to skill mismatches, employers will keep turning to placement agencies for their databases to track and identify the right candidates. Companies will lean on temporary hires as the economic outlook remains unclear and inflation keeps squeezing budgets. The automation of more routine jobs will be a threat to some long-standing temporary jobs. Across Europe, countries that traditionally rely on a strong network of short-term workers are implanting policies that may disrupt or expand services. Spain has already introduced reforms that are taking effect to increase permanent positions and remove temporary contracts, while Italy is expanding its voucher scheme to encourage temporary hires.

Revenue in the Temporary Employment Agency industry is anticipated to drop at a compound annual rate of 4% in the five years through 2024 to €236.5 billion. The COVID-19 outbreak meant key employers of temporary workers in the hospitality and tourist sector shut their doors, and companies froze hiring due to economic uncertainty - a sizeable blow to revenue in the three years through 2022. Workers on temporary contracts represented a significant chuck of employment losses in all quarters of 2020. According to Eurostat data, temporary employment declined across Europe in the four years from 2017 to 2020, dipping from 13.8% to 11.9%. Since COVID-19 has slowed, companies have resumed hiring as confidence levels have been restored and vacancy levels have soared. An increasingly tight labour market encourages employers to rely on temporary employment placement agencies to fight in an increasingly competitive market. Several countries rank highly in terms of temporary workers with a large short-term job market. In 2022, the Netherlands and Spain have more than 15% of employed people under temporary contracts, according to Eurostat. Industry revenue is expected to shrink by 1.6% in 2024. Revenue is expected to grow at an annual rate of 4.5% in the five years through 2029 to €295.4 billion. With the labour market is likely to remain tight in many countries due to skill mismatches, employers will keep turning to placement agencies for their databases to track and identify the right candidates. Companies will lean on temporary hires as the economic outlook remains unclear and inflation keeps squeezing budgets. The automation of more routine jobs will be a threat to some long-standing temporary jobs. Across Europe, countries that traditionally rely on a strong network of short-term workers are implanting policies that may disrupt or expand services. Spain has already introduced reforms that are taking effect to increase permanent positions and remove temporary contracts, while Italy is expanding its voucher scheme to encourage temporary hires.

The pre-employment assessment testing software market is experiencing robust growth, driven by the increasing need for efficient and effective talent acquisition strategies across diverse industries. The market, currently valued at approximately $2 billion in 2025, is projected to exhibit a Compound Annual Growth Rate (CAGR) of 15% from 2025 to 2033. This significant expansion is fueled by several factors. Firstly, organizations are increasingly adopting technology to streamline their hiring processes, reducing time-to-hire and improving candidate quality. Secondly, the demand for data-driven insights into candidate suitability is rising, enabling better alignment between candidate skills and job requirements. Thirdly, the growing adoption of cloud-based solutions enhances accessibility, scalability, and cost-effectiveness for businesses of all sizes. Finally, the market is segmented by deployment type (cloud-based and web-based) and target company size (large, medium, and small enterprises), allowing vendors to cater to specific needs and preferences. This segmentation, combined with the continuous innovation in assessment methodologies and technological advancements, will further propel market growth in the coming years. The competitive landscape is characterized by a mix of established players and emerging technology providers. Companies like Criteria, Berke, and Wonderlic are well-established names leveraging their extensive experience and comprehensive product portfolios. However, newer entrants are also gaining traction by offering innovative solutions that leverage AI and machine learning to enhance assessment accuracy and efficiency. The market's geographical distribution shows strong growth across North America and Europe, driven by high technology adoption rates and robust economic conditions. However, growth in regions like Asia-Pacific is also gaining momentum, driven by increasing digitalization and expanding business operations. While challenges such as data security concerns and the need for robust regulatory compliance exist, the overall market outlook remains optimistic, with significant potential for continued expansion throughout the forecast period.

The global market for screening software for background checks is experiencing robust growth, driven by increasing concerns about workplace safety and regulatory compliance across various industries. The rising adoption of cloud-based solutions, offering scalability and cost-effectiveness, further fuels this expansion. While precise market sizing data is unavailable, a logical estimation based on industry trends and comparable markets suggests a current market valuation in the billions of dollars, with a Compound Annual Growth Rate (CAGR) projected between 10% and 15% for the forecast period (2025-2033). This growth is propelled by several factors: the increasing need for efficient and thorough background checks to mitigate risks associated with hiring unsuitable candidates, the growing awareness of potential legal liabilities related to negligent hiring, and the continuous evolution of technologies that enhance the accuracy and speed of background screening processes. The market is segmented by application (SMEs and large enterprises) and deployment type (cloud-based and on-premises), with cloud-based solutions gaining significant traction due to their accessibility and flexible pricing models. Large enterprises, with their stricter compliance requirements and larger workforce, represent a considerable portion of the market, driving demand for sophisticated, integrated screening solutions. Geographic regions like North America and Europe currently dominate the market, fueled by stringent regulations and higher adoption rates, but significant growth potential exists in emerging markets in Asia-Pacific and Middle East & Africa as awareness of best hiring practices increases. However, challenges such as data privacy concerns, escalating costs associated with comprehensive background checks, and the complexities of navigating diverse global regulations pose restraints to market expansion. The competitive landscape is dynamic, with several established players and emerging startups offering a diverse range of solutions catering to specific needs and budgets. The key players compete based on features, pricing, compliance certifications, and integration capabilities with existing HR systems. Future growth will likely be shaped by innovation in areas such as AI-powered candidate screening, improved data analytics for risk assessment, and the integration of background checks with broader HR technology platforms. Furthermore, the market will see increased demand for solutions addressing evolving legal requirements and data security standards, creating opportunities for vendors to differentiate their offerings and capitalize on the ongoing growth of this essential sector.

The pre-employment background check software market is experiencing robust growth, driven by increasing concerns about workplace safety and the need for efficient hiring processes. The market, estimated at $2 billion in 2025, is projected to grow at a Compound Annual Growth Rate (CAGR) of 15% from 2025 to 2033, reaching approximately $6 billion by 2033. This expansion is fueled by several key factors. Firstly, stringent government regulations and increased liability concerns are pushing organizations to implement comprehensive background checks to mitigate risks associated with negligent hiring. Secondly, the rising adoption of cloud-based solutions offers scalability, cost-effectiveness, and improved data security, driving market penetration. Furthermore, technological advancements, such as AI-powered candidate screening tools and integration with Applicant Tracking Systems (ATS), are streamlining the background check process and enhancing efficiency. The market segmentation reveals a strong preference for cloud-based solutions, with the enterprise sector leading in adoption. Geographically, North America currently holds the largest market share, but regions like Asia Pacific are demonstrating significant growth potential due to increasing urbanization and a expanding workforce. However, data privacy concerns and the complexities of navigating varying regulations across different jurisdictions present significant restraints to market growth. Despite the promising outlook, challenges remain. The increasing complexity of compliance regulations necessitates continuous software updates and necessitates ongoing investment in robust security measures to maintain data integrity and privacy. Competition among established players and new entrants is intensifying, requiring companies to differentiate through innovation and specialized services. Furthermore, the need for accurate and unbiased background checks is paramount, demanding careful consideration of potential biases embedded within algorithms and data sources. The ongoing evolution of employment laws and best practices requires software providers to remain adaptable and responsive to legislative changes. Despite these challenges, the long-term outlook for the pre-employment background check software market remains positive, driven by the enduring need for secure and efficient hiring practices across diverse industries.

Revenue in the Temporary Employment Agency industry is anticipated to drop at a compound annual rate of 4% in the five years through 2024 to €236.5 billion. The COVID-19 outbreak meant key employers of temporary workers in the hospitality and tourist sector shut their doors, and companies froze hiring due to economic uncertainty - a sizeable blow to revenue in the three years through 2022. Workers on temporary contracts represented a significant chuck of employment losses in all quarters of 2020. According to Eurostat data, temporary employment declined across Europe in the four years from 2017 to 2020, dipping from 13.8% to 11.9%. Since COVID-19 has slowed, companies have resumed hiring as confidence levels have been restored and vacancy levels have soared. An increasingly tight labour market encourages employers to rely on temporary employment placement agencies to fight in an increasingly competitive market. Several countries rank highly in terms of temporary workers with a large short-term job market. In 2022, the Netherlands and Spain have more than 15% of employed people under temporary contracts, according to Eurostat. Industry revenue is expected to shrink by 1.6% in 2024. Revenue is expected to grow at an annual rate of 4.5% in the five years through 2029 to €295.4 billion. With the labour market is likely to remain tight in many countries due to skill mismatches, employers will keep turning to placement agencies for their databases to track and identify the right candidates. Companies will lean on temporary hires as the economic outlook remains unclear and inflation keeps squeezing budgets. The automation of more routine jobs will be a threat to some long-standing temporary jobs. Across Europe, countries that traditionally rely on a strong network of short-term workers are implanting policies that may disrupt or expand services. Spain has already introduced reforms that are taking effect to increase permanent positions and remove temporary contracts, while Italy is expanding its voucher scheme to encourage temporary hires.

The global financial background check market is experiencing robust growth, driven by increasing regulatory scrutiny, heightened concerns about fraud and financial misconduct, and the expanding adoption of digital technologies in the hiring process. The market's size in 2025 is estimated at $5 billion, reflecting a Compound Annual Growth Rate (CAGR) of approximately 15% during the period 2019-2024. This growth trajectory is projected to continue throughout the forecast period (2025-2033), reaching an estimated market value exceeding $12 billion by 2033. Key drivers include the rising prevalence of identity theft and financial fraud, necessitating thorough background checks for enhanced security and risk mitigation. Furthermore, the increasing reliance on automated and online verification systems is streamlining the background check process, reducing costs and improving efficiency for businesses. The market is segmented by type of check (credit history, bankruptcy filings, asset verification, etc.), industry (banking, finance, healthcare, etc.), and geography. Leading companies like Sterling Check, First Advantage, and Checkr are driving innovation with advanced technologies and expanding service offerings, consolidating their market position. However, factors such as data privacy concerns and increasing compliance costs pose potential restraints on market growth. Despite these challenges, the market exhibits promising long-term prospects. The continuing digital transformation across industries fuels the demand for efficient and reliable background check solutions. Emerging trends, like the integration of AI and machine learning for enhanced accuracy and speed, are shaping the market landscape. Geographic expansion into emerging economies with growing financial sectors also presents significant growth opportunities for market players. Competitive strategies like mergers and acquisitions, strategic partnerships, and technological advancements will further shape the industry's evolution over the forecast period. The increasing demand for comprehensive financial background checks across diverse sectors indicates a sustained and expanding market with significant potential for future growth.

The global background screening software market is experiencing robust growth, driven by increasing regulatory compliance needs, heightened security concerns across industries, and the rising adoption of cloud-based solutions. The market, estimated at $2 billion in 2025, is projected to maintain a healthy Compound Annual Growth Rate (CAGR) of approximately 15% through 2033. This expansion is fueled by several key factors. Firstly, the demand for efficient and reliable pre-employment screening is soaring across both SMEs and large enterprises, streamlining the hiring process and mitigating risks. Secondly, the shift towards cloud-based solutions offers scalability, cost-effectiveness, and enhanced accessibility, attracting a wider user base. Thirdly, technological advancements, such as AI-powered candidate vetting and improved data analytics, are optimizing screening processes and providing richer insights. However, factors like data privacy regulations and the potential for bias in automated screening systems present challenges that need careful consideration. The market segmentation reveals significant opportunities in different sectors. While large enterprises currently dominate the market share, the SME segment shows strong growth potential as awareness of background checks increases and businesses seek to leverage technology for streamlined processes. Similarly, the cloud-based segment is expected to witness substantial growth due to its inherent advantages. Regionally, North America currently holds the largest market share, followed by Europe and Asia Pacific. However, developing economies in Asia Pacific are demonstrating remarkable growth potential, driven by increasing urbanization and the expansion of various industries. Key players such as Certifix, Checkr, and Sterling Infosystems are actively shaping the market landscape through technological innovation, strategic partnerships, and mergers and acquisitions. The forecast period suggests a continued trajectory of growth, with increasing adoption across diverse sectors and geographies.

Revenue in the Temporary Employment Agency industry is anticipated to drop at a compound annual rate of 4% in the five years through 2024 to €236.5 billion. The COVID-19 outbreak meant key employers of temporary workers in the hospitality and tourist sector shut their doors, and companies froze hiring due to economic uncertainty - a sizeable blow to revenue in the three years through 2022. Workers on temporary contracts represented a significant chuck of employment losses in all quarters of 2020. According to Eurostat data, temporary employment declined across Europe in the four years from 2017 to 2020, dipping from 13.8% to 11.9%. Since COVID-19 has slowed, companies have resumed hiring as confidence levels have been restored and vacancy levels have soared. An increasingly tight labour market encourages employers to rely on temporary employment placement agencies to fight in an increasingly competitive market. Several countries rank highly in terms of temporary workers with a large short-term job market. In 2022, the Netherlands and Spain have more than 15% of employed people under temporary contracts, according to Eurostat. Industry revenue is expected to shrink by 1.6% in 2024. Revenue is expected to grow at an annual rate of 4.5% in the five years through 2029 to €295.4 billion. With the labour market is likely to remain tight in many countries due to skill mismatches, employers will keep turning to placement agencies for their databases to track and identify the right candidates. Companies will lean on temporary hires as the economic outlook remains unclear and inflation keeps squeezing budgets. The automation of more routine jobs will be a threat to some long-standing temporary jobs. Across Europe, countries that traditionally rely on a strong network of short-term workers are implanting policies that may disrupt or expand services. Spain has already introduced reforms that are taking effect to increase permanent positions and remove temporary contracts, while Italy is expanding its voucher scheme to encourage temporary hires.

The Global Employment Platforms (GEP) Software market is experiencing robust growth, driven by the increasing adoption of remote work models, globalization of businesses, and the need for streamlined HR processes. The market, estimated at $15 billion in 2025, is projected to exhibit a Compound Annual Growth Rate (CAGR) of 15% from 2025 to 2033, reaching approximately $45 billion by 2033. This expansion is fueled by several key factors. Firstly, the rising demand for flexible and scalable workforce solutions enables businesses to easily manage international teams and contractors. Secondly, advancements in technology, such as AI-powered recruitment and payroll automation, are enhancing efficiency and reducing administrative burdens. Thirdly, regulatory changes and compliance requirements in various regions are pushing organizations towards employing GEP software to ensure legal adherence and mitigate risks. Finally, the growing preference for cloud-based solutions offers enhanced accessibility and cost-effectiveness, further fueling market growth. Competitive dynamics within the market are shaped by a blend of established players like ADP TotalSource and TriNet, and innovative startups such as Deel and Remote, each offering a unique suite of features and targeting specific niches. This competitive landscape fosters continuous innovation and drives down costs, benefiting businesses seeking effective workforce management solutions. The segmentation of the GEP market is crucial for understanding its nuances. While specific segment breakdowns are unavailable, we can reasonably infer key divisions based on industry best practices. These are likely to include small and medium-sized businesses (SMBs) versus large enterprises, based on company size and feature requirements. Further segmentation may also include industry verticals (e.g., tech, finance, healthcare), geographic regions, and the specific services offered (e.g., payroll, recruitment, compliance). Regional variations in market penetration and growth rates are anticipated, with North America and Europe likely leading the market initially, followed by a surge in adoption from Asia-Pacific and other emerging regions as global workforce strategies evolve. Constraints to growth might include data security concerns, integration challenges with existing HR systems, and the need for robust customer support to address the complexities of global employment regulations.

Revenue in the Temporary Employment Agency industry is anticipated to drop at a compound annual rate of 4% in the five years through 2024 to €236.5 billion. The COVID-19 outbreak meant key employers of temporary workers in the hospitality and tourist sector shut their doors, and companies froze hiring due to economic uncertainty - a sizeable blow to revenue in the three years through 2022. Workers on temporary contracts represented a significant chuck of employment losses in all quarters of 2020. According to Eurostat data, temporary employment declined across Europe in the four years from 2017 to 2020, dipping from 13.8% to 11.9%. Since COVID-19 has slowed, companies have resumed hiring as confidence levels have been restored and vacancy levels have soared. An increasingly tight labour market encourages employers to rely on temporary employment placement agencies to fight in an increasingly competitive market. Several countries rank highly in terms of temporary workers with a large short-term job market. In 2022, the Netherlands and Spain have more than 15% of employed people under temporary contracts, according to Eurostat. Industry revenue is expected to shrink by 1.6% in 2024. Revenue is expected to grow at an annual rate of 4.5% in the five years through 2029 to €295.4 billion. With the labour market is likely to remain tight in many countries due to skill mismatches, employers will keep turning to placement agencies for their databases to track and identify the right candidates. Companies will lean on temporary hires as the economic outlook remains unclear and inflation keeps squeezing budgets. The automation of more routine jobs will be a threat to some long-standing temporary jobs. Across Europe, countries that traditionally rely on a strong network of short-term workers are implanting policies that may disrupt or expand services. Spain has already introduced reforms that are taking effect to increase permanent positions and remove temporary contracts, while Italy is expanding its voucher scheme to encourage temporary hires.

The gig economy, encompassing freelance work and on-demand services, is experiencing robust growth, driven by technological advancements, evolving work preferences, and a desire for flexible employment options. The market, estimated at $300 billion in 2025, is projected to achieve a Compound Annual Growth Rate (CAGR) of 15% from 2025 to 2033, reaching approximately $1 trillion by 2033. This expansion is fueled by several key factors: the increasing adoption of digital platforms connecting businesses with independent contractors; a growing preference among workers for flexible schedules and autonomy; and the scalability these platforms offer businesses needing temporary or project-based assistance. Furthermore, the gig economy's diverse sectors, including transportation (DoorDash, Favor Delivery, Turo), home services (TaskRabbit, BellHops), professional services (Guru.com, Upwork, Fiverr), and pet care (Rover), contribute to its overall market strength.
However, challenges remain. Regulatory uncertainties surrounding worker classification and employment benefits pose significant hurdles. Competition among gig platforms is fierce, requiring constant innovation and adaptation to maintain market share. Fluctuations in the broader economy can also impact demand for gig services. Despite these restraints, the overall trajectory suggests a continued expansion of the gig economy, driven by ongoing technological advancements, evolving workforce demographics, and the increasing reliance of businesses on flexible talent pools. The major players, including TaskRabbit, Upwork, and Fiverr, are well-positioned to capitalize on this growth, provided they navigate the regulatory and competitive landscapes effectively. Successful strategies will likely involve investments in technology, focus on user experience, and proactive engagement with regulatory bodies.

The global market for behavioral tests in recruitment is experiencing robust growth, driven by a rising demand for objective and data-driven hiring processes. Organizations are increasingly recognizing the limitations of traditional interview methods and are turning to behavioral assessments to identify candidates with the personality traits, cognitive abilities, and behavioral patterns most likely to succeed in specific roles. This shift is fueled by a growing awareness of the high costs associated with poor hiring decisions and the need to improve employee retention. The market is segmented by various assessment types (e.g., personality tests, situational judgment tests), deployment methods (online, in-person), and industry verticals. Key players are constantly innovating, incorporating AI and machine learning to enhance accuracy, efficiency, and candidate experience. The integration of these technologies allows for more sophisticated analysis of candidate data, enabling better prediction of job performance and reducing bias in the hiring process. While the market faces challenges such as concerns about data privacy and the potential for misuse of assessment data, the overall trend points towards significant expansion. A conservative estimate for the market size in 2025 might be $2 billion, projecting a Compound Annual Growth Rate (CAGR) of 15% over the forecast period (2025-2033), driven by continuous technological advancements and growing adoption across diverse industries. This growth is further supported by the increasing adoption of cloud-based solutions, which offer scalability, cost-effectiveness, and ease of access. Furthermore, the expanding global talent pool and the intensifying competition for skilled workers necessitate efficient and effective recruitment strategies, thereby bolstering the demand for behavioral assessments. However, challenges such as the need for robust validation studies to ensure the fairness and accuracy of assessments, along with the potential for candidate resistance to these tools, need to be addressed. The market's future trajectory is likely to be shaped by the development of more sophisticated and ethically sound assessment methodologies, tailored to specific industry needs and cultural contexts, alongside greater transparency and candidate control over data usage. The competitive landscape is populated by established players alongside innovative startups, driving innovation and competition in the space.

Revenue in the Temporary Employment Agency industry is anticipated to drop at a compound annual rate of 4% in the five years through 2024 to €236.5 billion. The COVID-19 outbreak meant key employers of temporary workers in the hospitality and tourist sector shut their doors, and companies froze hiring due to economic uncertainty - a sizeable blow to revenue in the three years through 2022. Workers on temporary contracts represented a significant chuck of employment losses in all quarters of 2020. According to Eurostat data, temporary employment declined across Europe in the four years from 2017 to 2020, dipping from 13.8% to 11.9%. Since COVID-19 has slowed, companies have resumed hiring as confidence levels have been restored and vacancy levels have soared. An increasingly tight labour market encourages employers to rely on temporary employment placement agencies to fight in an increasingly competitive market. Several countries rank highly in terms of temporary workers with a large short-term job market. In 2022, the Netherlands and Spain have more than 15% of employed people under temporary contracts, according to Eurostat. Industry revenue is expected to shrink by 1.6% in 2024. Revenue is expected to grow at an annual rate of 4.5% in the five years through 2029 to €295.4 billion. With the labour market is likely to remain tight in many countries due to skill mismatches, employers will keep turning to placement agencies for their databases to track and identify the right candidates. Companies will lean on temporary hires as the economic outlook remains unclear and inflation keeps squeezing budgets. The automation of more routine jobs will be a threat to some long-standing temporary jobs. Across Europe, countries that traditionally rely on a strong network of short-term workers are implanting policies that may disrupt or expand services. Spain has already introduced reforms that are taking effect to increase permanent positions and remove temporary contracts, while Italy is expanding its voucher scheme to encourage temporary hires.

Revenue in the Temporary Employment Agency industry is anticipated to drop at a compound annual rate of 4% in the five years through 2024 to €236.5 billion. The COVID-19 outbreak meant key employers of temporary workers in the hospitality and tourist sector shut their doors, and companies froze hiring due to economic uncertainty - a sizeable blow to revenue in the three years through 2022. Workers on temporary contracts represented a significant chuck of employment losses in all quarters of 2020. According to Eurostat data, temporary employment declined across Europe in the four years from 2017 to 2020, dipping from 13.8% to 11.9%. Since COVID-19 has slowed, companies have resumed hiring as confidence levels have been restored and vacancy levels have soared. An increasingly tight labour market encourages employers to rely on temporary employment placement agencies to fight in an increasingly competitive market. Several countries rank highly in terms of temporary workers with a large short-term job market. In 2022, the Netherlands and Spain have more than 15% of employed people under temporary contracts, according to Eurostat. Industry revenue is expected to shrink by 1.6% in 2024. Revenue is expected to grow at an annual rate of 4.5% in the five years through 2029 to €295.4 billion. With the labour market is likely to remain tight in many countries due to skill mismatches, employers will keep turning to placement agencies for their databases to track and identify the right candidates. Companies will lean on temporary hires as the economic outlook remains unclear and inflation keeps squeezing budgets. The automation of more routine jobs will be a threat to some long-standing temporary jobs. Across Europe, countries that traditionally rely on a strong network of short-term workers are implanting policies that may disrupt or expand services. Spain has already introduced reforms that are taking effect to increase permanent positions and remove temporary contracts, while Italy is expanding its voucher scheme to encourage temporary hires.