Working Paper: NBER ID: w31007
Authors: Stephen Hansen; Peter John Lambert; Nicholas Bloom; Steven J. Davis; Raffaella Sadun; Bledi Taska
Abstract: The pandemic catalyzed an enduring shift to remote work. To measure and characterize this shift, we examine more than 250 million job vacancy postings across five English-speaking countries. Our measurements rely on a state-of-the-art language-processing framework that we fit, test, and refine using 30,000 human classifications. We achieve 99% accuracy in flagging job postings that advertise hybrid or fully remote work, greatly outperforming dictionary methods and also outperforming other machine-learning methods. From 2019 to early 2023, the share of postings that say new employees can work remotely one or more days per week rose more than three-fold in the U.S and by a factor of five or more in Australia, Canada, New Zealand and the U.K. These developments are highly non-uniform across and within cities, industries, occupations, and companies. Even when zooming in on employers in the same industry competing for talent in the same occupations, we find large differences in the share of job postings that explicitly offer remote work.
Keywords: Remote Work; Job Vacancies; Labor Market; COVID-19; Machine Learning
JEL Codes: C55; E24; M54; O33; R3
Edges that are evidenced by causal inference methods are in orange, and the rest are in light blue.
| Cause | Effect |
|---|---|
| Employer choices (M51) | Variation in remote work offerings (J29) |
| Labor market conditions (J29) | Variation in remote work offerings (J29) |
| Increase in remote work postings (J62) | Change in actual employment practices (J79) |
| Pre-pandemic shares (N21) | Variation in remote work shares across occupations (J29) |
| Remote work share of postings (J60) | Share of employment (J21) |
| Pandemic (H12) | Increase in remote work postings (J62) |