Digital Transformation, Remote Work and Migration in the European Union: Implications for Sustainable Labour Markets

This study examines the conditional correlates of usual working from home and the net population migration rate across the 27 European Union Member States. Separate balanced panels cover 2014–2025 for working from home (324 observations) and 2015–2024 for migration (270 observations). Country and year fixed-effects models are estimated, with inference compared across White cross-section, country-clustered and Driscoll–Kraay covariance estimators. In the working-from-home model, regular Internet use has a negative coefficient and GDP per capita a positive coefficient; both remain significant under country-clustered inference. Unemployment has a positive baseline coefficient but loses significance under country-clustered inference. In the migration model, R&D expenditure intensity and GDP per capita have positive baseline coefficients, but neither remains significant at the 5% level with country-clustered standard errors. Knowledge-intensive employment is non-significant in both models, and its exclusion leaves the remaining coefficients almost unchanged. Adding unemployment to the migration model removes the baseline significance of R&D intensity. Country and recent-year exclusions preserve positive R&D-intensity and GDP-per-capita coefficients, while significance remains sensitive to inference, conditioning and period coverage. The estimates describe conditional within-country associations without identifying causal mechanisms or a relationship between the two outcomes. Labour-market sustainability provides a conceptual context rather than an empirically evaluated outcome.