The expansion of work-from-home (WFH) arrangements following the COVID-19 pandemic represents one of the most profound and persistent shifts in labor markets in recent decades. This structural change has spurred a growing literature examining WFH as a job amenity negotiated between firms and workers, with implications for productivity, firm organization, and worker welfare. However, there is still limited causal evidence on how the widespread availability of WFH has reshaped workers’ career paths, job mobility, and long-term earnings dynamics.
This dashboard analyzes the career effects of WFH by focusing on access to teleworking opportunities. The working hypothesis is that access to WFH potentially expands workers’ choice sets by widening the relevant labor market, allowing them to search for, and transition to, better-matched jobs.
The analysis combines administrative matched employer–employee data with repeated cross-section survey information on WFH take-up for the Netherlands, the European country with the highest incidence of remote work. A key feature of the data is the availability of detailed occupational classifications, which is mapped into a measure of teleworkability using the index developed by Dingel and Neiman (2020). This classification captures the feasibility of working from home based on occupational tasks and required technologies and is fixed prior to the pandemic. The analysis further leverages the sudden adoption of WFH technologies induced by the COVID-19 pandemic as a source of variation in the availability of teleworking opportunities. This shock disproportionately benefits occupations that were already more amenable to remote work before the pandemic. This heterogeneity is then exploited to identify the causal effects of expanded WFH availability across occupations in a difference-in-differences setting.
As in the following dashboard, occupations classified as teleworkable experienced (Teleworkability and Hybrid Teleworking) a large and persistent increase in WFH rates after 2019, particularly in hybrid arrangements combining on-site and remote work. Compared to non-teleworkable occupations, WFH rates in teleworkable jobs rose by roughly 15 percentage points in 2020, with only limited reversion over time. Conversely, the incidence of full work-from-home (Teleworkability and Full Teleworking) has been less persistent, although effects are detectable even three years after the pandemic.
The main analysis presents matched difference-in-differences models that compare workers employed in teleworkable occupations in 2019 to otherwise similar workers in non-teleworkable occupations. The results reveal sizeable and persistent earnings gains for workers in teleworkable occupations. The following dashboard shows that four years after the pandemic, “treated” workers earn almost 7 log points more than their matched counterparts in non-teleworkable jobs (Teleworkability and Log Wage). These gains are primarily driven by an increase in hours worked (Teleworkability and Log Hours), but there are also meaningful and statistically significant improvements in hourly wages (Teleworkability and Log Hourly Wage). As a result, earnings increase by around 3 thousand euros four years after the pandemic (Teleworkability and Earnings)
The results emerging from this deliverable have several important policy implications. First, they suggest that WFH should be viewed not only as a workplace flexibility or work–life balance tool, but also as a labor market infrastructure that affects mobility, matching efficiency, and long-term earnings growth. Policies that support the diffusion of remote work technologies—such as investments in digital infrastructure, broadband access, and remote collaboration tools—may yield productivity and welfare gains by enhancing workers’ ability to access better job matched.
Overall, this report provides new causal evidence that the post-pandemic expansion of WFH has reshaped workers’ careers primarily by increasing job mobility and improving labor market matching, with important consequences for earnings dynamics.
You may find additional information regarding the data and the methodology used in this report.