Svitlana Cherkasova

Type of the article: Research Article

Abstract
Digital transformation has emerged as a key driver of structural change in labor markets worldwide, especially in the aftermath of the COVID-19 shock. In the European Union, the pandemic particularly accelerated the adoption of digital technologies and remote work across economic activities. This study estimates the causal effect of the digitalization potential of economic activity (proxied by a binary classification into highly and less digitalized groups based on telework feasibility and digital intensity) on three labor market indicators: employment, hourly wages, and remote work. Using the COVID-19 shock as a quasi-natural experiment within a difference-in-differences (DiD) framework, the empirical analysis draws on quarterly panel data for a consistent sample of 27 EU Member States (excluding the United Kingdom) over 2018–2024 (N = 36,685). The results indicate that higher sectoral digitalization potential (telework feasibility and digital intensity) does not significantly affect aggregate employment levels, as evidenced by a near-zero DiD coefficient (0.06, p ≈ 0.98). In contrast, it has a statistically significant positive effect on wages, with a DiD coefficient of 0.52 €/hour (p < 0.001), corresponding to an increase of approximately 4.6% in the wage gap between highly and less digitalized activities. The strongest effect is found for remote work: the DiD estimate is 40.74 percentage points (p < 0.001). Remote work rose from 17.6% to 82.1% in highly digitalized sectors, compared with only 1.3% to 6.6% in less digitalized economic activities.

Acknowledgment
This article was prepared within the framework of the research project “Modelling the impact of economic digitalisation on public health in Ukraine in the context of preserving human capital” (State Registration No. 0126U001085).

Type of the article: Research Article

Digital skills anchor human-capital policy in the European knowledge economy, yet which dimension of digitalization moves lifelong learning remains unsettled, as connectivity, specialist, and training targets are pursued in parallel. The paper aims to quantify the association between the workforce’s digital-skills composition and adult participation in learning across 31 European economies, using an unbalanced annual 2015–2023 panel supplemented by DigComp 2.0 waves for 2021–2025, and to draw implications for human-capital policy. Both are estimated with two-way fixed-effects models, lagged regressors, country-clustered standard errors, and an audit of survey redesigns. The lagged employment share of ICT specialists is positively associated with adult learning: a one-percentage-point increase corresponds to a 1.38-point gain (β = 1.379, p = 0.034; wild-cluster bootstrap p = 0.077). Diffusion-type measures – daily internet use and online health-information seeking – show no such link (β = 0.021 and 0.025), although the specialist coefficient is not statistically distinguishable from theirs. The coefficient stays positive across estimators and samples (0.44–1.76) and significant in the pre-break 2015–2020 window (β = 1.536, p = 0.024); a formal test does not reject constancy across the 2021 EU-LFS redesign. Direct skills measures point the same way but stay insignificant (β = 0.042–0.121); unemployment is counter-cyclical (β = 0.583–0.694). The evidence is consistent with rebalancing policy from connectivity targets towards workforce skills composition – a margin unmeasured in Ukraine, Kazakhstan, and Armenia – with specialist pipelines as the instrument most directly supported and enterprise ICT training as a possible, not yet established, channel.

Acknowledgment
Vladyslav Smiianov contributed to this article within the framework of the research project “Modelling the impact of economic digitalization on public health in Ukraine in the context of preserving human capital”, funded by the Ministry of Education and Science of Ukraine (State Registration No. 0126U001085).