Digital transformation and labor market indicators in the EU: Evidence from the COVID-19 shock using difference-in-differences

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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).

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    • Figure 1. Test of the parallel trends assumption
    • Figure 2. Visualization of DiD effects for three indicators
    • Figure 3. Comparison of actual DiD and placebo tests (employment)
    • Table 1. Classification of economic activities by digitalization potential
    • Table 2. Descriptive statistics of key variables by sector group (2018–2024)
    • Table 3. Difference-in-differences estimates of digitalization effects on labor market outcomes
    • Table 4. Sectoral employment dynamics across periods (thousand persons)
    • Table 5. Placebo tests for DiD validity (employment, thousand persons)
    • Table 6. Heterogeneity of the DiD effect across EU countries
    • Table 7. SDG-related labor market indicators by sector digitalization
    • Conceptualization
      Nataliia Bieliaieva, Oleksandr Rozhko, Iuliia Padafet, Svitlana Cherkasova, Semen Blahun, Tetyana Kharchenko, Dmytro Poroshyn
    • Supervision
      Nataliia Bieliaieva
    • Writing – original draft
      Nataliia Bieliaieva, Oleksandr Rozhko, Iuliia Padafet, Svitlana Cherkasova, Semen Blahun, Tetyana Kharchenko, Dmytro Poroshyn
    • Writing – review & editing
      Nataliia Bieliaieva, Oleksandr Rozhko, Iuliia Padafet, Svitlana Cherkasova, Semen Blahun, Tetyana Kharchenko, Dmytro Poroshyn
    • Project administration
      Oleksandr Rozhko
    • Funding acquisition
      Iuliia Padafet
    • Resources
      Iuliia Padafet
    • Visualization
      Svitlana Cherkasova
    • Validation
      Semen Blahun, Dmytro Poroshyn
    • Software
      Tetyana Kharchenko
    • Data curation
      Dmytro Poroshyn
    • Formal Analysis
      Dmytro Poroshyn
    • Investigation
      Dmytro Poroshyn
    • Methodology
      Dmytro Poroshyn