By the last business day of September 2024, there were about 7.44 million job openings in the United States. This is a decrease from the previous month, when there were 7.86 million job openings. The data are seasonally adjusted. Seasonal adjustment is a statistical method for removing the seasonal component of a time series that is used when analyzing non-seasonal trends.

In the United States, there were about eight million job openings on the last business day of September 2024. The job openings rate was 4.5 percent that month. The data are seasonally adjusted. Seasonal adjustment is a statistical method for removing the seasonal component of a time series that is used when analyzing non-seasonal trends.

Europe: Social Related Job Trends in the Insurance Sector (April 2022 - July 2022)

Global: ESG Related Job Trends in the Insurance Sector (April 2022 - July 2022)

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.

According to Cognitive Market Research, the global Outplacement Services market was USD 3.1 billion in 2022 and will grow at a compound annual growth rate (CAGR) of 18.1% from 2023 to 2030. How are the Key Drivers Affecting the Outplacement Services Market?

Increasing Penetration of Analytical Solutions and Connected Devices Applications Drive the Outplacement Services Market

The rising adoption of analytical solutions and connected device applications propels the Outplacement Services Market. These technologies enable deeper insights into job markets, skill demands, and career trends, enhancing the effectiveness of outplacement services.

Visier, Inc. introduced a novel Platform as a Service (PaaS) named Alpine Visier. These fresh services expand the company's portfolio, offering a comprehensive solution that appeals to potential customers and speeds up revenue growth.

(Source:www.visier.com/blog/alpine-platform/)

Data-driven analytics assist in personalized coaching and job matching, while connected devices provide seamless virtual access to resources and support. This digital transformation optimizes service delivery, aligning with the evolving needs of job seekers and employers, thus driving the market's growth.

Wide ranging Advantages to Organization to Decipher the Market Share

The Factors Restraining the Growth of the Outplacement Services Market

Changing Workforce Dynamics is Challenging the Growth of the Outplacement Services Market

Changing workforce dynamics challenge the Outplacement Services Market by introducing varied skill requirements. Rapid technological advancements and automation reshape job roles, leading to a diverse range of displaced employees with differing skill sets. Providing relevant and effective support tailored to these evolving skill demands becomes more complex. Outplacement service providers must continually adapt their offerings to address the dynamic needs of individuals facing job transitions in a rapidly changing job landscape.

Impact of Covid-19 on Outplacement Services Market

The COVID-19 pandemic disrupted the Outplacement Services Market by causing widespread economic uncertainties, job losses and organizational restructuring. High unemployment rates and remote work challenges shifted the demand for outplacement services. The remote nature of work transitions and limited in-person interactions presented difficulties in delivering personalized support. Despite the increased need for career transition assistance, budget constraints among companies during the pandemic further affected the accessibility and utilization of outplacement services. Introduction of Outplacement Services

The Outplacement Services Market is growing due to changing workforce dynamics and corporate restructuring. Organizations increasingly focus on supporting laid-off employees with career transition assistance and maintaining positive employer branding. With advancements in technology, personalized coaching, skill development, and job search support are offered, driving demand for outplacement services. A greater emphasis on employee well-being and a competitive job market also influences growth.

These developments empower businesses to offer better-tailored solutions and services, which, in turn, contribute to the growth of the Outplacement Services industry.

In the upcoming years, the Metaverse is expected to play a large role in people's lives, according to a recent press release from Gartner, a renowned research and advising company. According to Gartner, 25% of individuals will spend at least one hour per day in the Metaverse by 2026. This virtual environment has the power to change how we communicate, connect with one another, and do business.

(Source:www.linkedin.com/pulse/gartner-predicts-25-people-spend-least-one-hour-per-chintan/)

VITAL SIGNS INDICATOR
Jobs by Industry (EC1)

FULL MEASURE NAME
Employment by place of work by industry sector

LAST UPDATED
December 2022

DESCRIPTION
Jobs by industry refers to both the change in employment levels by industry and the proportional mix of jobs by economic sector. This measure reflects the changing industry trends that affect our region’s workers.

DATA SOURCE
Bureau of Labor Statistics, Quarterly Census of Employment and Wages (QCEW) - https://www.bls.gov/cew/downloadable-data-files.htm
1990-2021

CONTACT INFORMATION
vitalsigns.info@bayareametro.gov

METHODOLOGY NOTES (across all datasets for this indicator)
Quarterly Census of Employment and Wages (QCEW) employment data is reported by the place of work and represent the number of covered workers who worked during, or received pay for, the pay period that included the 12th day of the month. Covered employees in the private-sector and in the state and local government include most corporate officials, all executives, all supervisory personnel, all professionals, all clerical workers, many farmworkers, all wage earners, all piece workers and all part-time workers. Workers on paid sick leave, paid holiday, paid vacation and the like are also covered.

Besides excluding the aforementioned national security agencies, QCEW excludes proprietors, the unincorporated self-employed, unpaid family members, certain farm and domestic workers exempted from having to report employment data and railroad workers covered by the railroad unemployment insurance system. Excluded as well are workers who earned no wages during the entire applicable pay period because of work stoppages, temporary layoffs, illness or unpaid vacations.

The location quotient (LQ) is used to evaluate level of concentration or clustering of an industry within the Bay Area and within each county of the region. A location quotient greater than 1 means there is a strong concentration for of jobs in an industry sector. For the Bay Area, the LQ is calculated as the share of the region’s employment in a particular sector divided by the share of California's employment in that same sector. For each county, the LQ is calculated as the share of the county’s employment in a particular sector divided by the share of the region’s employment in that same sector.

Data is mainly pulled from aggregation level 73, which is county-level summarized at the North American Industry Classification System (NAICS) supersector level (12 sectors). This aggregation level exhibits the least loss due to data suppression, in the magnitude of 1-2 percent for regional employment, and is therefore preferred. However, the supersectors group together NAICS 11 Agriculture, Forestry, Fishing and Hunting; NAICS 21 Mining and NAICS 23 Construction. To provide a separate tally of Agriculture, Forestry, Fishing and Hunting, the aggregation level 74 data was used for NAICS codes 11, 21 and 23.

QCEW reports on employment in Public Administration as NAICS 92. However, many government activities are reported with an industry specific code - such as transportation or utilities even if those may be public governmental entities. In 2021 for the Bay Area, the largest industry groupings under public ownership are Education and health services (58%); Public administration (29%) and Trade, transportation, and utilities (29%). With the exception of Education and health services, all other public activities were coded as government/public administration, regardless of industry group.

For the county data there were some industries that reported 0 jobs or did not report jobs at the desired aggregation/NAICS level for the following counties/years:

Farm:
(aggregation level: 74, NAICS code: 11) - Contra Costa: 2008-2010 - Marin: 1990-2006, 2008-2010, 2014-2020 - Napa: 1990-2004, 2013-2021 - San Francisco: 2019-2020 - San Mateo: 2013

Information:
(aggregation level: 73, NAICS code: 51) - Solano: 2001

Financial Activities:
(aggregation level: 73, NAICS codes: 52, 53) - Solano: 2001

Unclassified:
(aggregation level: 73, NAICS code: 99) - All nine Bay Area counties: 1990-2000 - Marin, Napa, San Mateo, and Solano: 2020 - Napa: 2019 - Solano: 2001

The net job and business growth indicator measures the annual change in both the number of firms and the number of employees between 1978 and 2022. The data is categorized by the size of the firm: those with 1-19 employees, those with between 20 and 499 employees, and those with more than 500 employees.

This data contributes to the big picture of economic conditions in Champaign County. More firms and larger employment numbers are generally positive economic indicators, but any strictly economic indicator should be considered in the context of other factors.

The number of firms and number of employees show very different trends.

Historically, there have been significantly more firms with 1-19 employees than firms in the larger two size categories. The number of firms with 1-19 employees has also been relatively consistent until 2021: there were 95 fewer such firms in 2021 than 1978, and the largest year-to-year change in that 43-year period of analysis was a -3.2% decrease between 1979 and 1980. However, there were 437 fewer such firms in 2022 than 1978. There was a decrease in these firms of 12.5% from 2021 to 2022, the only double-digit year-to-year change and the largest year-to-year change over 44 years.

The larger two size categories have shown an increasing trend over the period of analysis. There were 43 more firms with 20-499 employees in 2022 than 1978, a total increase of 9%. The number of firms with more than 500 employees almost doubled, increasing by 206 firms from 212 in 1978 to 418 in 2022, a total increase of 97.2%.

The trends of employment also vary based on firm size. Firms with 1-19 employees have consistently, and unsurprisingly, accounted for less of the total employment than the larger two categories. Employment in firms with 1-19 employees has also remained relatively consistent over the period of analysis. Employment in firms with more than 500 employees saw an overall trend of growth, interrupted by brief and intermittent decreases, between 1978 and 2022. Employment in the middle category (firms with between 20 and 499 employees) was also greater in 2022 than in 1978.

This data is from the U.S. Census Bureau’s Business Dynamics Statistics Data Tables. This data is at the geographic scale of the Champaign-Urbana Metropolitan Statistical Area (MSA), which is comprised of Champaign and Piatt Counties, or a larger area than the cities or Champaign County.

Source: U.S. Census Bureau; 2022 Business Dynamics Statistics Data Tables; "BDSFSIZE - Business Dynamics Statistics: Firm Size: 1978-2022"; retrieved 21 October 2024.

According to learning and development and HR professionals, challenging and impactful work was the most important factor when considering a new job position for those age 50 and older. The most important factor for the 18 to 34 demographic was career growth.

EN The Job advertisements are in text formats and in their original language. The SUF data files are available in English in SPSS, Stata and R data formats.

DE Die Stellenanzeigen liegen in Textformaten vor und sind in der jeweiligen Originalsprache abgedruckt. Die SUF-Datendateien liegen in Englisch im SPSS-, Stata- und RData Format vor.

FR Les offres d'emploi sont dans un format texte et dans leur langue d'origine. Les fichiers de données SUF sont disponibles en anglais pour SPSS, Stata et R.

According to Cognitive Market Research, the global Recruitment & Staffing market size is USD 519848.5 million in 2024. It will expand at a compound annual growth rate (CAGR) of 9.90% from 2024 to 2031.

North America held the major market share for more than 40% of the global revenue with a market size of USD 207939.40 million in 2024 and will grow at a compound annual growth rate (CAGR) of 8.1% from 2024 to 2031.
Europe accounted for a market share of over 30% of the global revenue with a market size of USD 155954.55 million.
Asia Pacific held a market share of around 23% of the global revenue with a market size of USD 119565.16 million in 2024 and will grow at a compound annual growth rate (CAGR) of 11.9% from 2024 to 2031.
Latin America had a market share for more than 5% of the global revenue with a market size of USD 25992.43 million in 2024 and will grow at a compound annual growth rate (CAGR) of 9.3% from 2024 to 2031.
Middle East and Africa had a market share of around 2% of the global revenue and was estimated at a market size of USD 10396.97 million in 2024 and will grow at a compound annual growth rate (CAGR) of 9.6% from 2024 to 2031.
Recruiting held the domiant position in the Recruitment & Staffing market

Market Dynamics of Recruitment & Staffing Market

Key Drivers for Recruitment & Staffing Market

Huge job opportunities in the BFSI and IT sectors drive staffing and recruitment market growth

IT hiring and recruitment sector is rapidly expanding. According to research from the online hiring site Monster, the banking, financial services, and insurance (BFSI) industry in India will see a 27% increase in job posts year over year in February 2023. According to Monster data, finance-related employment will account for around 8% of all jobs posted on the site by 2023. Furthermore, India is seeing a significant increase in job prospects as a result of digitization, payment innovations, and expanded financial inclusion, as well as the forthcoming 5G deployment. According to the Monster Employment Index, hiring in the BFSI industry increased by 25% in August 2022, after experiencing a 21% increase in July 2022.

Rising young populations

The presence of young workers in the job market and the desire of recruitment agencies for budget-friendly approaches are significantly impacting the expansion of the Recruitment & Staffing Market. Recruitment helps connect skilled and capable young individuals with organizations that are seeking employees, ensuring companies find the right candidates for their needs. Similarly, the focus on expenses has led companies to choose recruitment solutions that are both efficient and cost-effective. These elements contribute to the expansion of the Recruitment & Staffing Market by meeting the demand for cost-effective and effective recruitment services, enabling businesses to acquire the appropriate talent.

Restraint Factor for the Recruitment & Staffing Market

Rising Costs and Margin Pressure

The Recruitment & Staffing Market is restrained by increasing cost and margin pressure. As the operational cost increases in the industry (for eg technology investment, talent acquisition cost etc.), it leads to margin pressure for the recruitment agencies, as every business tries to maintain the profit margin, which directly impact the competitive pricing for the services offered. The rising operational cost may also affect the smaller agencies to invest in cutting edge technologies, training programs etc., which directly impact their competitiveness in the market. Hence the increasing cost in the industry will definitely be a challenge and how efficiently businesses manage this cost pressure will define their sustained growth and profitability.

Impact of Covid-19 on the Recruitment & Staffing Market

The Covid-19 pandemic changed the Recruitment & Staffing market dynamically with its impact across the entire global market. As a result of the COVID-19 pandemic that led to some shutdowns, economic instability and business disruption, many organizations were compelled to freeze or even downsize their employee intake, hence reducing the demand for recruitment services. Nevertheless, as the economis slowly turns into improvement there is observed the shift in the focus on remote work and virtual hiring what accelerates the employment of digital recruitment solutions and platforms. Temporary and contract st...

China City Labor Market: Supply data was reported at 3,579.000 Person th in Sep 2022. This records an increase from the previous number of 3,282.000 Person th for Jun 2022. China City Labor Market: Supply data is updated quarterly, averaging 4,256.227 Person th from Mar 2001 (Median) to Sep 2022, with 86 observations. The data reached an all-time high of 6,766.367 Person th in Sep 2010 and a record low of 1,322.845 Person th in Mar 2001. China City Labor Market: Supply data remains active status in CEIC and is reported by Ministry of Human Resources and Social Security. The data is categorized under China Premium Database’s Labour Market – Table CN.GJ: City Labor Market: Supply of Labour.

Employment placement agencies in Europe’s revenue is anticipated to contract at a compound annual rate of 3.2% over the five years through 2024 to €47.8 billion. The COVID-19 outbreak tanked business confidence and expansion plans because of economic uncertainty after months of global lockdowns, forcing hiring freezes in a tricky time for employment agencies. 2022 marked a resurgence for agencies. According to Eurostat data, employment in the EU reached a record peak of 74.6% in 2022, with unemployment falling month-on-month to 5.9% in August 2023. Companies enjoyed a post-COVID-19 boom in hiring, as the economy reopened and company’s began to look to expand thanks to improved business confidence which kept employment agencies busy. The labour market has proved resilient against the economic background of rising interest rates and high inflation but remains tight with several unfilled vacancies. Vacancies remain well above pre-pandemic levels but have steadily dipped from the sharp rise post-COVID-19 as companies unfroze hiring decisions, indicating a skills mismatch between job seekers and roles that agencies are struggling to negotiate. Several countries attempt to address long-standing labour shortages to ameliorate professional mobility and offer training courses for in-demand skills through agencies. France, for example, is addressing youth unemployment through upskilling training programmes. Public sector hiring in Germany and Spain in health and education also pushes revenue growth for agencies compared to stunted private sector demand. Revenue is expected to slump by 1.3% in 2024 amid job cuts in the technology sector. Revenue is projected to swell at a compound annual rate of 4.3% over the five years through 2029 to reach €58.9 billion. Agencies will continue to target revenue growth by elevating their online presence, specialising their services towards more niche sectors and targeting executives and upper management positions. Technological developments remain a threat to recruiters, with HR AI systems like Paradox able to scan networking platforms such as LinkedIn for candidates. Companies’ in-house HR teams are expanding too. The sustainability sector looks to be a hot property job market to target, but potential shortages in both high and low-skilled occupations driven by employment growth in STEM professions and healthcare will create hurdles in the hiring process in other sectors.

About this dataset

Context

The dataset presents median income data over a decade or more for males and females categorized by Total, Full-Time Year-Round (FT), and Part-Time (PT) employment in New Market. It showcases annual income, providing insights into gender-specific income distributions and the disparities between full-time and part-time work. The dataset can be utilized to gain insights into gender-based pay disparity trends and explore the variations in income for male and female individuals.

Key observations: Insights from 2021

Based on our analysis ACS 2017-2021 5-Year Estimates, we present the following observations: - All workers, aged 15 years and older: In New Market, the median income for all workers aged 15 years and older, regardless of work hours, was $33,634 for males and $20,929 for females.

These income figures highlight a substantial gender-based income gap in New Market. Women, regardless of work hours, earn 62 cents for each dollar earned by men. This significant gender pay gap, approximately 38%, underscores concerning gender-based income inequality in the town of New Market.

- Full-time workers, aged 15 years and older: In New Market, among full-time, year-round workers aged 15 years and older, males earned a median income of $38,116, while females earned $47,290

Surprisingly, within the subset of full-time workers, women earn a higher income than men, earning 1.24 dollars for every dollar earned by men. This suggests that within full-time roles, womens median incomes significantly surpass mens, contrary to broader workforce trends.

https://i.neilsberg.com/ch/new-market-va-income-by-gender.jpeg" alt="New Market, VA gender based income disparity">

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2017-2021 5-Year Estimates. All incomes have been adjusting for inflation and are presented in 2022-inflation-adjusted dollars.

Gender classifications include:

• Male
• Female

Employment type classifications include:

• Full-time, year-round: A full-time, year-round worker is a person who worked full time (35 or more hours per week) and 50 or more weeks during the previous calendar year.
• Part-time: A part-time worker is a person who worked less than 35 hours per week during the previous calendar year.

Variables / Data Columns

• Year: This column presents the data year. Expected values are 2010 to 2022
• Male Total Income: Annual median income, for males regardless of work hours
• Male FT Income: Annual median income, for males working full time, year-round
• Male PT Income: Annual median income, for males working part time
• Female Total Income: Annual median income, for females regardless of work hours
• Female FT Income: Annual median income, for females working full time, year-round
• Female PT Income: Annual median income, for females working part time

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for New Market median household income by gender. You can refer the same here

About this dataset

Context

The dataset presents median income data over a decade or more for males and females categorized by Total, Full-Time Year-Round (FT), and Part-Time (PT) employment in New Market. It showcases annual income, providing insights into gender-specific income distributions and the disparities between full-time and part-time work. The dataset can be utilized to gain insights into gender-based pay disparity trends and explore the variations in income for male and female individuals.

Key observations: Insights from 2021

Based on our analysis ACS 2017-2021 5-Year Estimates, we present the following observations: - All workers, aged 15 years and older: In New Market, the median income for all workers aged 15 years and older, regardless of work hours, was $42,398 for males and $19,332 for females.

These income figures highlight a substantial gender-based income gap in New Market. Women, regardless of work hours, earn 46 cents for each dollar earned by men. This significant gender pay gap, approximately 54%, underscores concerning gender-based income inequality in the town of New Market.

- Full-time workers, aged 15 years and older: In New Market, among full-time, year-round workers aged 15 years and older, males earned a median income of $51,343, while females earned $39,762, leading to a 23% gender pay gap among full-time workers. This illustrates that women earn 77 cents for each dollar earned by men in full-time roles. This analysis indicates a widening gender pay gap, showing a substantial income disparity where women, despite working full-time, face a more significant wage discrepancy compared to men in the same roles.

Surprisingly, the gender pay gap percentage was higher across all roles, including non-full-time employment, for women compared to men. This suggests that full-time employment offers a more equitable income scenario for women compared to other employment patterns in New Market.

https://i.neilsberg.com/ch/new-market-in-income-by-gender.jpeg" alt="New Market, IN gender based income disparity">

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2017-2021 5-Year Estimates. All incomes have been adjusting for inflation and are presented in 2022-inflation-adjusted dollars.

Gender classifications include:

• Male
• Female

Employment type classifications include:

• Full-time, year-round: A full-time, year-round worker is a person who worked full time (35 or more hours per week) and 50 or more weeks during the previous calendar year.
• Part-time: A part-time worker is a person who worked less than 35 hours per week during the previous calendar year.

Variables / Data Columns

• Year: This column presents the data year. Expected values are 2010 to 2022
• Male Total Income: Annual median income, for males regardless of work hours
• Male FT Income: Annual median income, for males working full time, year-round
• Male PT Income: Annual median income, for males working part time
• Female Total Income: Annual median income, for females regardless of work hours
• Female FT Income: Annual median income, for females working full time, year-round
• Female PT Income: Annual median income, for females working part time

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for New Market median household income by gender. You can refer the same here

By 2032, it is projected that the the number of registered nurses working in the U.S., will increase by about 177,400 compared to the number of employed registered nurses in 2022. Home health and personal care aide employment is expected to increase by over 804,100, more than any other occupation in the same timespan.

This 6MB download is a zip file containing 5 pdf documents and 2 xlsx spreadsheets. Presentation on COVID-19 and the potential impacts on employment

May 2020Waka Kotahi wants to better understand the potential implications of the COVID-19 downturn on the land transport system, particularly the potential impacts on regional economies and communities.

To do this, in May 2020 Waka Kotahi commissioned Martin Jenkins and Infometrics to consider the potential impacts of COVID-19 on New Zealand’s economy and demographics, as these are two key drivers of transport demand. In addition to providing a scan of national and international COVID-19 trends, the research involved modelling the economic impacts of three of the Treasury’s COVID-19 scenarios, to a regional scale, to help us understand where the impacts might be greatest.

Waka Kotahi studied this modelling by comparing the percentage difference in employment forecasts from the Treasury’s three COVID-19 scenarios compared to the business as usual scenario.

The source tables from the modelling (Tables 1-40), and the percentage difference in employment forecasts (Tables 41-43), are available as spreadsheets.

Arataki - potential impacts of COVID-19 Final Report

Employment modelling - interactive dashboard

The modelling produced employment forecasts for each region and district over three time periods – 2021, 2025 and 2031. In May 2020, the forecasts for 2021 carried greater certainty as they reflected the impacts of current events, such as border restrictions, reduction in international visitors and students etc. The 2025 and 2031 forecasts were less certain because of the potential for significant shifts in the socio-economic situation over the intervening years. While these later forecasts were useful in helping to understand the relative scale and duration of potential COVID-19 related impacts around the country, they needed to be treated with care recognising the higher levels of uncertainty.

The May 2020 research suggested that the ‘slow recovery scenario’ (Treasury’s scenario 5) was the most likely due to continuing high levels of uncertainty regarding global efforts to manage the pandemic (and the duration and scale of the resulting economic downturn).

The updates to Arataki V2 were framed around the ‘Slower Recovery Scenario’, as that scenario remained the most closely aligned with the unfolding impacts of COVID-19 in New Zealand and globally at that time.

Find out more about Arataki, our 10-year plan for the land transport system

May 2021The May 2021 update to employment modelling used to inform Arataki Version 2 is now available. Employment modelling dashboard - updated 2021Arataki used the May 2020 information to compare how various regions and industries might be impacted by COVID-19. Almost a year later, it is clear that New Zealand fared better than forecast in May 2020.Waka Kotahi therefore commissioned an update to the projections through a high-level review of:the original projections for 2020/21 against performancethe implications of the most recent global (eg International monetary fund world economic Outlook) and national economic forecasts (eg Treasury half year economic and fiscal update)The treasury updated its scenarios in its December half year fiscal and economic update (HYEFU) and these new scenarios have been used for the revised projections.Considerable uncertainty remains about the potential scale and duration of the COVID-19 downturn, for example with regards to the duration of border restrictions, update of immunisation programmes. The updated analysis provides us with additional information regarding which sectors and parts of the country are likely to be most impacted. We continue to monitor the situation and keep up to date with other cross-Government scenario development and COVID-19 related work. The updated modelling has produced employment forecasts for each region and district over three time periods - 2022, 2025, 2031.The 2022 forecasts carry greater certainty as they reflect the impacts of current events. The 2025 and 2031 forecasts are less certain because of the potential for significant shifts over that time.

Data reuse caveats: as per license.

Additionally, please read / use this data in conjunction with the Infometrics and Martin Jenkins reports, to understand the uncertainties and assumptions involved in modelling the potential impacts of COVID-19.

COVID-19’s effect on industry and regional economic outcomes for NZ Transport Agency [PDF 620 KB]

Data quality statement: while the modelling undertaken is high quality, it represents two point-in-time analyses undertaken during a period of considerable uncertainty. This uncertainty comes from several factors relating to the COVID-19 pandemic, including:

a lack of clarity about the size of the global downturn and how quickly the international economy might recover differing views about the ability of the New Zealand economy to bounce back from the significant job losses that are occurring and how much of a structural change in the economy is required the possibility of a further wave of COVID-19 cases within New Zealand that might require a return to Alert Levels 3 or 4.

While high levels of uncertainty remain around the scale of impacts from the pandemic, particularly in coming years, the modelling is useful in indicating the direction of travel and the relative scale of impacts in different parts of the country.

Data quality caveats: as noted above, there is considerable uncertainty about the potential scale and duration of the COVID-19 downturn. Please treat the specific results of the modelling carefully, particularly in the forecasts to later years (2025, 2031), given the potential for significant shifts in New Zealand's socio-economic situation before then.

As such, please use the modelling results as a guide to the potential scale of the impacts of the downturn in different locations, rather than as a precise assessment of impacts over the coming decade.

Australia Employment: Trend: Manufacturing data was reported at 884.697 Person th in Nov 2024. This records a decrease from the previous number of 890.853 Person th for Aug 2024. Australia Employment: Trend: Manufacturing data is updated quarterly, averaging 1,026.291 Person th from Nov 1984 (Median) to Nov 2024, with 161 observations. The data reached an all-time high of 1,169.755 Person th in Aug 1989 and a record low of 847.536 Person th in May 2022. Australia Employment: Trend: Manufacturing data remains active status in CEIC and is reported by Australian Bureau of Statistics. The data is categorized under Global Database’s Australia – Table AU.G021: Employment: by Industry.

Arellano-Bover, Jaime, (2022) “The Effect of Labor Market Conditions at Entry on Workers' Long-Term Skills.” Review of Economics and Statistics 104:5, 1028–1045.

Employment Rate in El Salvador increased to 47.34 percent in 2022 from 46.36 percent in 2021. This dataset provides - El Salvador Employment Rate- actual values, historical data, forecast, chart, statistics, economic calendar and news.