This page contains selected figures, as well as a portal for researchers to access the data used in our research paper: “Remote Work across Jobs, Companies, and Space” (Hansen, Lambert, Bloom, Davis, Sadun & Taska, 2023).
The below figures are interactive and data are available to download
Figure 1: Share of new job vacancies advertising remote work rose dramatically
Note: This figure shows the share of vacancy postings that say the job allows one or more remote workdays per week. We compute these monthly, country-level shares as the weighted mean of the own-country occupation-level shares, with weights given by the U.S. vacancy distribution in 2019. Our occupation-level granularity is roughly equivalent to six-digit SOC codes. Figures depicts the 3-month moving average. Full screen. Access data.
Figure 2: Advertised remote work shows substantial divergence across US cities
Note: This figure shows the share of new vacancy postings across selected US cities that say the job allows one or more remote workdays per week. Full screen. Access data.
Figure 3: Advertised remote work in 2022 is very uneven across occupations
Note: This figure shows the share of new vacancy postings across occupations (using USA data) that say the job allows one or more remote workdays per week. Each bar is an ONET code (scroll over the top to find out which one!). We display the top ten occupations (by count of postings) in each selected group. Full screen. Access data.
How we measure advertised remote work…
Our team of researchers joined forces with Lightcast, a labour-market analytics firm, and developed a text algorithm capable of measuring offers of remote work (i.e. one or more days per week at home) directly from the raw text of online job vacancy postings.
Our data span the near-universe of new online job vacancy postings, and currently contains over 250 million documents.
Our approach to measurement has a number of distinct benefits (and some drawbacks). For example:
- Our dataset is huge, covering five countries, thousands of cities and employers, and hundreds of occupations
- New vacancies are posted daily, allowing us to measure advertised remote work in near-realtime. We plan to update the data regularly.
- The algorithm we developed achieves a 99% accuracy at identifying remote work job ads
- We measure explicit offers of remote work in new job ads, not the number of employees who work-from-home (for this, see survey measures available at wfhresearch.com)
These data may be used by researchers and other interested parties. For any specific data requests, media comments, or technical issues, please contact us.