A dataset containing statistics on work-life balance, employee burnout, flexible work policies, productivity, and job satisfaction, based on surveys and reports.

In 2025, there were estimated to be approximately 3.6 billion people employed worldwide, compared to 2.23 billion people in 1991 - an increase of around 1.4 billion people. There was a noticeable fall in global employment between 2019 and 2020, when the number of employed people fell from due to the sudden economic shock caused by the COVID-19 pandemic. Formal vs. Informal employment globally Worldwide, there is a large gap between the informally and formally employed. Most informally employed workers reside in the Global South, especially Africa and Southeast Asia. Moreover, men are slightly more likely to be informally employed than women. The majority of informal work, nearly 90 percent, is within the agricultural sector, with domestic work and construction following behind. Women’s employment As the number of employees has risen globally, so has the number of employed women. Overall, care roles such as nursing and midwifery have the highest shares of female employees globally. Moreover, while the gender pay gap has shrunk over time, it still exists. As of 2024, the uncontrolled gender pay gap was 0.83, meaning women made, on average, 83 cents per every dollar earned by men.

In 2024, the U.S. employment rate stood at 60.1 percent. Employed persons consist of: persons who did any work for pay or profit during the survey reference week; persons who did at least 15 hours of unpaid work in a family-operated enterprise; and persons who were temporarily absent from their regular jobs because of illness, vacation, bad weather, industrial dispute, or various personal reasons. The employment-population ratio represents the proportion of the civilian non-institutional population that is employed. The monthly unemployment rate for the United States can be found here.

Dataset shows an individual’s statistical area 2 (SA2) of usual residence and the SA2 of their workplace address, for the employed census usually resident population count aged 15 years and over, by main means of travel to work from the 2018 and 2023 Censuses.

The main means of travel to work categories are:

• Work at home
• Drive a private car, truck, or van
• Drive a company car, truck, or van
• Passenger in a car, truck, van, or company bus
• Public bus
• Train
• Bicycle
• Walk or jog
• Ferry
• Other.

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Main means of travel to work is the usual method which an employed person aged 15 years and over used to travel the longest distance to their place of work.

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Workplace address refers to where someone usually works in their main job, that is the job in which they worked the most hours. For people who work at home, this is the same address as their usual residence address. For people who do not work at home, this could be the address of the business they work for or another address, such as a building site.

Workplace address is coded to the most detailed geography possible from the available information. This dataset only includes travel to work information for individuals whose workplace address is available at SA2 level. The sum of the counts for each region in this dataset may not equal the total employed census usually resident population count aged 15 years and over for that region. Workplace address – 2023 Census: Information by concept has more information.

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This dataset can be used in conjunction with the following spatial files by joining on the SA2 code values:

• Statistical area 2 2023 (generalised)
• Statistical area 2 2023 (Centroid Inside)

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Download data table using the instructions in the Koordinates help guide.

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Footnotes

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Geographical boundaries

Statistical standard for geographic areas 2023 (updated December 2023) has information about geographic boundaries as of 1 January 2023. Address data from 2013 and 2018 Censuses was updated to be consistent with the 2023 areas. Due to the changes in area boundaries and coding methodologies, 2013 and 2018 counts published in 2023 may be slightly different to those published in 2013 or 2018.

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Subnational census usually resident population

The census usually resident population count of an area (subnational count) is a count of all people who usually live in that area and were present in New Zealand on census night. It excludes visitors from overseas, visitors from elsewhere in New Zealand, and residents temporarily overseas on census night. For example, a person who usually lives in Christchurch city and is visiting Wellington city on census night will be included in the census usually resident population count of Christchurch city. 

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Population counts

Stats NZ publishes a number of different population counts, each using a different definition and methodology. Population statistics – user guide has more information about different counts. 

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Caution using time series

Time series data should be interpreted with care due to changes in census methodology and differences in response rates between censuses. The 2023 and 2018 Censuses used a combined census methodology (using census responses and administrative data).

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Workplace address time series

Workplace address time series data should be interpreted with care at lower geographic levels, such as statistical area 2 (SA2). Methodological improvements in 2023 Census resulted in greater data accuracy, including a greater proportion of people being counted at lower geographic areas compared to the 2018 Census. Workplace address – 2023 Census: Information by concept has more information.

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Working at home

In the census, working at home captures both remote work, and people whose business is at their home address (e.g. farmers or small business owners operating from their home). The census asks respondents whether they ‘mostly’ work at home or away from home. It does not capture whether someone does both, or how frequently they do one or the other.

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Rows excluded from the dataset

Rows show SA2 of usual residence by SA2 of workplace address. Rows with a total population count of less than six have been removed to reduce the size of the dataset, given only a small proportion of SA2-SA2 combinations have commuter flows.

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About the 2023 Census dataset

For information on the 2023 dataset see Using a combined census model for the 2023 Census. We combined data from the census forms with administrative data to create the 2023 Census dataset, which meets Stats NZ's quality criteria for population structure information. We added real data about real people to the dataset where we were confident the people who hadn’t completed a census form (which is known as admin enumeration) will be counted. We also used data from the 2018 and 2013 Censuses, administrative data sources, and statistical imputation methods to fill in some missing characteristics of people and dwellings.

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Data quality

The quality of data in the 2023 Census is assessed using the quality rating scale and the quality assurance framework to determine whether data is fit for purpose and suitable for release. Data quality assurance in the 2023 Census has more information.

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Quality rating of a variable

The quality rating of a variable provides an overall evaluation of data quality for that variable, usually at the highest levels of classification. The quality ratings shown are for the 2023 Census unless stated. There is variability in the quality of data at smaller geographies. Data quality may also vary between censuses, for subpopulations, or when cross tabulated with other variables or at lower levels of the classification. Data quality ratings for 2023 Census variables has more information on quality ratings by variable.

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Main means of travel to work quality rating

Main means of travel to work is rated as moderate quality.

Main means of travel to work – 2023 Census: Information by concept has more information, for example, definitions and data quality.

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Workplace address quality rating

Workplace address is rated as moderate quality.

Workplace address – 2023 Census: Information by concept has more information, for example, definitions and data quality.

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Using data for good

Stats NZ expects that, when working with census data, it is done so with a positive purpose, as outlined in the Māori Data Governance Model (Data Iwi Leaders Group, 2023). This model states that "data should support transformative outcomes and should uplift and strengthen our relationships with each other and with our environments. The avoidance of harm is the minimum expectation for data use. Māori data should also contribute to iwi and hapū tino rangatiratanga”.

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Confidentiality

The 2023 Census confidentiality rules have been applied to 2013, 2018, and 2023 data. These rules protect the confidentiality of individuals, families, households, dwellings, and undertakings in 2023 Census data. Counts are calculated using fixed random rounding to base 3 (FRR3) and suppression of ‘sensitive’ counts less than six, where tables report multiple geographic variables and/or small populations. Individual figures may not always sum to stated totals. Applying confidentiality rules to 2023 Census data and summary of changes since 2018 and 2013 Censuses has more information about 2023 Census confidentiality rules.

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Percentages

To calculate percentages, divide the figure for the category of interest by the figure for ‘Total stated’ where this applies.

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Symbol

-999 Confidential

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Inconsistencies in definitions

Please note that there may be differences in definitions between census classifications and those used for other data collections.

Historical Employment Statistics 1990 - current. The Current Employment Statistics (CES) more information program provides the most current estimates of nonfarm employment, hours, and earnings data by industry (place of work) for the nation as a whole, all states, and most major metropolitan areas. The CES survey is a federal-state cooperative endeavor in which states develop state and sub-state data using concepts, definitions, and technical procedures prescribed by the Bureau of Labor Statistics (BLS). Estimates produced by the CES program include both full- and part-time jobs. Excluded are self-employment, as well as agricultural and domestic positions. In Connecticut, more than 4,000 employers are surveyed each month to determine the number of the jobs in the State. For more information please visit us at http://www1.ctdol.state.ct.us/lmi/ces/default.asp.

In 2024, the employment rate of the workforce of 55 years and older decreased to 37.3 percent. Employment rate among young adults (age 16-24) was at 50.9 percent in 2024. For monthly updates on employment in the United States visit the annual national employment rate here.

Introduction

Remote Work Statistics: The traditional office-based work model has undergone a significant transformation in recent years, with remote work becoming increasingly prevalent. As of 2024, approximately 30% of the global workforce engages in remote work at least part-time. In the United States, 12.7% of full-time employees work entirely from home, while 28.2% follow a hybrid model combining home and office work.

Productivity has seen notable improvements among remote workers. Studies indicate that remote employees are 35–40% more productive than their in-office counterparts, often working 1.4 additional days per month. Moreover, 77% of remote workers report higher productivity levels when working from home.

Financial benefits are also significant. Employers can save up to USD 11,000 per remote employee annually due to reduced overhead costs. Employees, on average, save approximately USD 4,000 per year on commuting and related expenses.

Employee well-being has improved with remote work. About 82% of remote workers report lower stress levels, and 78% experience better work-life balance. Additionally, companies offering remote work options see a 25% reduction in employee turnover.

These statistics highlight the evolving landscape of work, emphasizing the productivity gains, cost savings, and enhanced employee satisfaction associated with remote work arrangements. Let's examine some statistics to gain a better understanding of the current state of remote work.

Graph and download economic data for Multiple Jobholders as a Percent of Employed (LNS12026620) from Jan 1994 to Jun 2025 about multiple jobholders, 16 years +, percent, household survey, employment, and USA.

Current Employment by Industry (CES) data reflect jobs by "place of work." It does not include the self-employed, unpaid family workers, and private household employees. Jobs located in the county or the metropolitan area that pay wages and salaries are counted although workers may live outside the area. Jobs are counted regardless of the number of hours worked. Individuals who hold more than one job (i.e. multiple job holders) may be counted more than once. The employment figure is an estimate of the number of jobs in the area (regardless of the place of residence of the workers) rather than a count of jobs held by the residents of the area.

This dataset contains annual average CES data for California statewide and areas from 1990 to 2023.

The Current Employment Statistics (CES) program is a Federal-State cooperative effort in which monthly surveys are conducted to provide estimates of employment, hours, and earnings based on payroll records of business establishments. The CES survey is based on approximately 119,000 businesses and government agencies representing approximately 629,000 individual worksites throughout the United States.

CES data reflect the number of nonfarm, payroll jobs. It includes the total number of persons on establishment payrolls, employed full- or part-time, who received pay (whether they worked or not) for any part of the pay period that includes the 12th day of the month. Temporary and intermittent employees are included, as are any employees who are on paid sick leave or on paid holiday. Persons on the payroll of more than one establishment are counted in each establishment. CES data excludes proprietors, self-employed, unpaid family or volunteer workers, farm workers, and household workers. Government employment covers only civilian employees; it excludes uniformed members of the armed services.

The Bureau of Labor Statistics (BLS) of the U.S. Department of Labor is responsible for the concepts, definitions, technical procedures, validation, and publication of the estimates that State workforce agencies prepare under agreement with BLS.

Graph and download economic data for Infra-Annual Labor Statistics: Employment Total: From 15 to 64 Years for United States (LFEM64TTUSQ647S) from Q1 1970 to Q1 2025 about 15 to 64 years, employment, and USA.

Labour Force Survey (LFS) estimates of the number of people out of work who either returned to employment or remained out of employment in three-month periods, broken down by a range of personal characteristics.

The 2018 Census commuter view dataset contains the employed census usually resident population count aged 15 years and over by statistical area 2 for the main means of travel to work variable from the 2018 Census. The geography corresponds to 2018 boundaries.

This dataset is the base data for the ‘There and back again: our daily commute’ competition.

This 2018 Census commuter view dataset is displayed by statistical area 2 geography and contains from-to (journey) information on an individual's usual residence and workplace address* by main means of travel to work.

* Workplace address is coded from information supplied by respondents about their workplaces. Where respondents do not supply sufficient information, their responses are coded to ‘not further defined’. The 2018 Census commuter view datasets excludes these ‘not further defined’ areas, as such the sum of the counts for each region in this dataset may not be equal to the total employed census usually resident population count aged 15 years and over for that region.

It is recommended that this dataset be downloaded as either a CSV or a file geodatabase.

This dataset can be used in conjunction with the following spatial files by joining on the statistical area 2 code values:

· Statistical Area 2 2018 (generalised)

· Statistical Area 2 2018 (Centroid Inside)

The data uses fixed random rounding to protect confidentiality. Counts of less than 6 are suppressed according to 2018 confidentiality rules. Values of -999 indicate suppressed data.

Data quality ratings for 2018 Census variables, summarising the quality rating and priority levels for 2018 Census variables, are available.

For information on the statistical area 2 geography please refer to the Statistical standard for geographic areas 2018.

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About this Dataset

This dataset combines automation probability data with a breakdown of the number of jobs and salary in each occupation by state within the USA. Automation probability was acquired from the work of Carl Benedikt Freyand Michael A. Osborne; State employment data is from the Bureau of Labor Statistics. Note that for simplicity of analysis, all jobs where data was not available or there were less than 10 employees were marked as zero.

How to Cite this Dataset

If you use this dataset in your research, please credit the authors.

Salary Data

@misc{u.s. bureau of labor statistics, title={Occupational Employment Statistics}, url={https://www.bls.gov/oes/current/oes_nat.htm}, journal={U.S. BUREAU OF LABOR STATISTICS}}

Automation Data

@article{frey_osborne_2017, title={The future of employment: How susceptible are jobs to computerisation?}, volume={114}, DOI={10.1016/j.techfore.2016.08.019}, journal={Technological Forecasting and Social Change}, author={Frey, Carl Benedikt and Osborne, Michael A.}, year={2017}, pages={254–280}}

License

License was not specified at the source.

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Labour statistics consistent with the System of National Accounts (SNA), by economic regions, job category and work schedule.

AHE: sa: PW: EH: Residential Intellect & Dev'l Disability Facilities data was reported at 21.850 USD in Mar 2025. This records an increase from the previous number of 21.760 USD for Feb 2025. AHE: sa: PW: EH: Residential Intellect & Dev'l Disability Facilities data is updated monthly, averaging 11.690 USD from Jan 1990 (Median) to Mar 2025, with 423 observations. The data reached an all-time high of 21.850 USD in Mar 2025 and a record low of 6.740 USD in Jan 1990. AHE: sa: PW: EH: Residential Intellect & Dev'l Disability Facilities data remains active status in CEIC and is reported by U.S. Bureau of Labor Statistics. The data is categorized under Global Database’s United States – Table US.G: Current Employment Statistics: Average Hourly Earnings: Production Workers: Seasonally Adjusted.

In the aftermath of the Coronavirus pandemic, the working hours lost in the second quarter of 2020 amounted to the equivalent of *** million full-time jobs, when compared with the fourth quarter of 2019. Since that quarter, the situation has improved, with the estimated number of working hours lost in ** 2022 closer to pre-COVID levels, at approximately ***** million full-time equivalent jobs.

Graph and download economic data for All Employees, Federal (CES9091000001) from Jan 1939 to Jun 2025 about establishment survey, federal, government, employment, and USA.

Full Time Employment in the United States increased to 135277 Thousand in June from 134840 Thousand in May of 2025. This dataset provides - United States Full Time Employment- actual values, historical data, forecast, chart, statistics, economic calendar and news.

Introduction

Career Change Statistics: If you've been thinking about leaving your job to focus more than focusing on your work, you're not the only one. Since the pandemic, nearly half of us have thought about changing careers. The idea that there's something better out there is growing quickly, with over 60% of workers planning to switch jobs this year. The days of staying in one job forever are gone.

Whether it's because of burnout or feeling stuck, the numbers don't lie – it's a big shift in how we think about our careers, and you might be the next one to break free from the corporate routine. We shall shed more light on the Career Change Statistics through this article.