The trend of working remotely has been slowly increasing globally since 2015, with a *** to ***** percent annual increase rate. However, the COVID-19 pandemic in 2020 upended the world economy and global markets. Employment trends were no exception to this, with the share of employees working remotely increasing to some ** percent in 2022 from just ** percent two years prior. The industry with the highest share of remote workers globally in 2023 was by far the technology sector, with over ** percent of tech employees worldwide working fully or mostly remotely. How are employers dealing with remote work? Many employers around the world have already adopted some remote work policies. According to IT industry leaders, reasons for remote work adoption ranged from a desire to broaden a company’s talent pool, increase productivity, and reduce costs from office equipment or real estate investments. Nonetheless, employers worldwide grappled with various concerns related to hybrid work. Among tech leaders, leading concerns included enabling effective collaboration and preserving organizational culture in hybrid work environments. Consequently, it’s unsurprising that maintaining organizational culture, fostering collaboration, and real estate investments emerged as key drivers for return-to-office mandates globally. However, these efforts were not without challenges. Notably, ** percent of employers faced employee resistance to returning to the office, prompting a review of their remote work policies.

Before the coronavirus (COVID-19) pandemic, 17 percent of U.S. employees worked from home 5 days or more per week, a share that increased to 44 percent during the pandemic. The outbreak of the COVID-19 pandemic accelerated the remote working trend, as quarantines and lockdowns made commuting and working in an office close to impossible for millions around the world. Remote work, also called telework or working from home (WFH), provided a solution, with employees performing their roles away from the office supported by specialized technology, eliminating the commute to an office to remain connected with colleagues and clients. What enables working from home?

To enable remote work, employees rely on a remote work arrangements that enable hybrid work and make it safe during the COVID-19 pandemic. Technology supporting remote work including laptops saw a surge in demand, video conferencing companies such as Zoom jumped in value, and employers had to consider new communication techniques and resources. Is remote work the future of work?

The response to COVID-19 has demonstrated that hybrid work models are not necessarily an impediment to productivity. For this reason, there is a general consensus that different remote work models will persist post-COVID-19. Many employers see benefits to flexible working arrangements, including positive results on employee wellness surveys, and potentially reducing office space. Many employees also plan on working from home more often, with 25 percent of respondents to a recent survey expecting remote work as a benefit of employment. As a result, it is of utmost importance to acknowledge any issues that may arise in this context to empower a hybrid workforce and ensure a smooth transition to more flexible work models.

Introduction

Work From Home Statistics: Since the COVID-19 pandemic, a major shift in work culture has taken place globally. Remote work, often referred to as work from home, has become a permanent option for many employees. According to data from Owl Labs and Global Workplace Analytics, about 30 percent of employees in the United States now work remotely full-time as of 2024. Meanwhile, 65 percent of employees prefer remote work over traditional office roles. In Europe, approximately 22 percent of workers were working from home regularly by the end of 2023. Remote work opportunities have also expanded, with LinkedIn reporting a 20 percent rise in remote job postings compared to pre-pandemic levels.

In terms of cost savings, employees who work from home can save an average of USD 6,000 annually on commuting and daily expenses. Additionally, businesses are seeing benefits, as employers can save around USD 11,000 per year for every remote employee. However, not all regions have fully embraced this trend; for instance, in countries like Japan, less than 10 percent of employees work remotely as companies encourage a return to traditional office environments.

As stated in Work from Home Statistics 2025, employees are resigning from their positions to get a remote job if they are called back to the office. Remote work is peace of mind, with which work-life balance is handled.

In 2021, ** percent of respondents currently working at least partially outside the office indicated that their company has a 100 percent remote policy. This is a slight increase from the previous year. Only ** percent of respondents stated that remote work in their company is allowed but not the norm, down from ** percent in 2020. Global shift to new work in 2020 In 2020, the outbreak of the global COVID-19 pandemic led to a shift from work in the office to work from home, to keep the workforce and the community safe. While this created some struggles in the beginning, many organizations and employees have since adapted and are thriving. Many employees appreciate the benefits of working remotely. Accordingly, one in two individuals indicate that the ability to work remotely is an important decision factor for future employment. Companies experiment with hybrid work models As a result, many companies worldwide are updating their policies to accommodate this new way of working. These include a combination of both flexibility on work location and productive in-person and digital collaboration opportunities. For this reason, organizations are not only actively monitoring both employee well-being and productivity but are also evolving operations to support a hybrid workforce.

Experimental estimates from the Annual Population Survey for homeworking in the UK, including breakdowns by sex, full-time or part-time, ethnicity, occupation, industry, qualifications, hours worked, pay and sickness absence among others. Includes regression outputs on the different outcomes for homeworkers.

Employed persons working from home as a percentage of the total employment, by sex, age and professional status (%)

Percentage of workforce teleworking or working remotely prior to February 1, 2020, on March 31, 2020, and percentage of workforce able to carry out a majority of their duties during the COVID-19 pandemic, by North American Industry Classification System (NAICS) code, business employment size, type of business and majority ownership.

In 2023, the largest share of employees who preferred to work-from-home in the United States were those between 26 and 41 years old and totaled 41 percent of those surveyed within this age group. The age group with the least desire to work from home were between 18 and 25 years old.

Analysis of how working from home has affected individuals’ spending and how this differs by characteristics, Great Britain.

A survey of 1,500 NSW workers during August and September 2020 (2020 Remote Working Survey) and March and April 2021 (2021 Remote Working Survey), commissioned to understand workers' experiences of and attitudes to remote and hybrid working. To be eligible, respondents had to be employed NSW residents with experience of remote working in their current job. After accounting for unemployed people and those whose jobs cannot be done remotely—for example, dentists, cashiers and cleaners—the sample represents around 59 per cent of NSW workers. Workers answered questions on: • their attitudes to remote working • the amount of time they spent working remotely • their employers’ policies, practices, and attitudes • how they spent their time when working remotely • how barriers to remote working have changed • the barriers they faced to hybrid working • their expectations for future remote working

These figures are experimental estimates of online job adverts provided by Adzuna, an online job search engine. The number of job adverts over time is an indicator of the demand for labour. To identify these adverts we have applied text-matching to find job adverts which contain key phrases associated with homeworking such as “remote working”, “work from home”, “home-based” and “telework”. The data do not separately identify job adverts which exclusively offer homeworking from those which offer flexible homeworking, such as one day a week from home.

In 2022, around ** percent of respondents stated that their biggest struggle when working remotely was staying at home too often because there they don't have reason to leave. Moreover many people who work from home do not necessarily have a designated workspace, they experience a conflation between their living area and workplace. Most notably, around ** percent of respondents reported loneliness as their biggest struggle with working remotely. As a result, remotely working employees emphasize the importance of finding strategies to balance their private lives with their professional routines. On the other hand, employees also state having less difficulties with collaboration and communication in 2021. This is likely due to the quick cultivation of skills during the 2020 pandemic that allow them to effectively communicate and collaborate with others when working from different locations. Challenges inherent in new work set-ups As employees work from different locations, companies are confronted with the urgency to ease some of the challenges inherent in novel hybrid work solutions. Strategies developed to support remote work include training for employees or expanding information technology infrastructure to ensure that employees can collaborate efficiently from different locations. The future of work Certainly, it is important to take the challenges experienced by employees seriously as the current telework trend is likely to continue and become a common way of working in the future. Addressing challenges head-on in the present will ensure better working conditions in the future.

Data on working patterns and location of work of adults in Great Britain, including costs and benefits of homeworking and future expectations. Survey data from the Opinions and Lifestyle Survey (OPN).

The percentage of the working population that does not commute to work. Source: U.S. Census Bureau, American Community Survey Years Available: 2018-2022, 2019-2023

A 2022 survey found that ** million Americans have been offered the option to work remotely either full- or party-time. During the COVID-19 pandemic, many workers across the U.S. began working remotely for the first time. The popularity of remote work has continued as pandemic restrictions have relaxed.

The percentage of the working population that does not commute to work. Source: U.S. Census Bureau, American Community SurveyYears Available: 2018-2022, 2019-2023Please note: We do not recommend comparing overlapping years of data due to the nature of this dataset. For more information, please visit: https://www.census.gov/programs-surveys/acs/guidance/comparing-acs-data.html

Data are provided on the labor force activity for the week prior to the survey. Comprehensive data are available on the employment status, occupation, and industry of persons aged 15 and older. Also shown are personal characteristics such as age, sex, race, marital status, veteran status, household relationship, educational background, and Hispanic origin. The Work Schedules and Work at Home Supplement questions were asked of all eligible persons aged 15 and older. The file contains information on temporary work done without expecting continuing employment from the employer. Also included is information about each worker's expectation of continuing employment, satisfaction with their current employment arrangement, current job history, transition into the current employment arrangement, search for other employment, employee benefits, and earnings. (Source: downloaded from ICPSR 7/13/10)

Please Note: This dataset is part of the historical CISER Data Archive Collection and is also available at ICPSR at https://doi.org/10.3886/ICPSR03663.v2. We highly recommend using the ICPSR version as they have made this dataset available in multiple data formats.

Average percentage of workforce anticipated to work on-site or remotely over the next three months, by average percentage, North American Industry Classification System (NAICS), business employment size, type of business, business activity and majority ownership, second quarter of 2022.

The paper uses data from the BIBB/BAuA Employment Survey of the Working Population on Qualification and Working Conditions in Germany 2018, doi: 10.7803/501.18.1.1.10. The Survey was conducted by the Federal Institute for Vocational Education and Training (BIBB), and the Federal Institute for Occupational Safety and Health (BAuA). For further details, see https://www.bibb.de/de/65740.php and the BIBB-FDZ Data and methodological Report at https://www.bibb.de/veroeffentlichungen/de/publication/show/16563.

The data access was provided via a Scientific-Use-File (called ZA7574_v1-0-0.dta) of the Data Research Centre at the Federal Institute for Vocational Training and Education (BIBB-FDZ). The data are confidential, but not exclusive. To apply for data access, please follow the instructions at https://www.bibb.de/de/120401.php.

To replicate the results reported in the paper, access to this data set must be obtained from the data provider.

The STATA do-file “ik_replication.do” (also available as txt-file “ik_replication.txt”) is replicating all results presented in the paper. It first makes use of the BIBB-BAuA source file “ZA7574_v1-0-0.dta” (see above) to generate and label all relevant variables, specifies the sample, and finally generates a working data set. In a second step, this working data is used to generate the results. Thereby, the analysis makes use of several auxiliary data sets, which can be merged to the working data. These auxiliary data sets have been obtained and constructed from alternative data sources (which we make available as part of the replication package).

A. Google mobility report https://www.gstatic.com/covid19/mobility/2020-03-29_DE_Mobility_Report_en.pdf Google prepared this report to provide information on the responses to social distancing guidance related to COVID-19. We use information for the first weeks of the shutdown on mobility trend changes for places of work on March 29, 2020, relative to a baseline value. The respective numbers are already included in the do-file to replicate the results in the paper and the pdf-file is part of the replication folder (see Source Files/2020-03-29_DE_Mobility_Report_en.pdf).

B. Unemployment across occupations – Data files ba_jul.dta / ba_jul.txt We use information from the report ”Arbeitsmarkt nach Berufen” from July 2020 provided by the Federal Employment Agency (BA) to obtain yearly changes in unemployment for occupations at the three digit level according to the occupation classification KldB 2010. The original file is part of the replication folder (see Source Files/berufe-heft-kldb2010-d-0-202007-xlsx). We use information from sheet 1.1 for number of unemployed persons in July 2020 and 2019 and the respective difference. This information is merged to the working data using the data file “ba_jul.dta” (or “ba_jul.txt”). It contains the following variables: - kldb2010_3d: 3-digit KldB 2010 occupation code (also available in working data) - jul_2020: number of unemployed persons in July 2020 - jul_2019: number of unemployed persons in July 2020 - delta_abs_jul: difference between 2020 and 2019   C. Fadinger and Schymik (2020) – Data files wfh_sch.dta / wfh_sch.txt To generate Figure A.9 in the Appendix, we rely on estimates provided in recent work by Fadinger and Schymik (2020) , who use an alternative measure for the WFH potential at the NUTS2 level. This information is merged to the working data using the data file “wfh_sch.dta” (or “wfh_sch.txt”). It contains the following variables: - GEO: Name of NUTS2 region - shr_homewk_pssb: Estimates on WFH share from Fadinger and Schymik (2020) - region: NUTS2 number (also available in working data)

D. Spatial Autocorrelation – Data files geo_data.dta / geo_data.txt To check for spatial autocorrelation across the 38 NUTS2 regions in Germany, we compute Moran’s I statistic which requires information on the longitude and latitude of NUTS2 regions. This information can be merged to the working data using the data file “geo_data.dta” (or “geo_data.txt”). It contains the following variables: - nuts_id: NUTS2 code - region: NUTS2 number (also available in working data) - longitude: Longitude position - latitude: Latitude position

A survey conducted in 2022 found that members of Generation Z were the least likely to say they were just as productive when working from home versus working in the office. In contrast, nearly ***** times the number of Baby Boomers said they were just as productive working from home versus the office.