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Intersectoral Labour Mobility in Europe as a Driver of Resilience and Innovation: Evidence from Granularity and Spatio-Temporal Modelling

Author

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  • Cristina Lincaru

    (National Scientific Research Institute for Labor and Social Protection, Povernei Street 6, 010643 Bucharest, Romania)

  • Camelia Speranta Pirciog

    (National Scientific Research Institute for Labor and Social Protection, Povernei Street 6, 010643 Bucharest, Romania)

  • Adriana Grigorescu

    (National Scientific Research Institute for Labor and Social Protection, Povernei Street 6, 010643 Bucharest, Romania
    Department of Public Management, Faculty of Public Administration, National University of Political Studies and Public Administration, Expozitiei Boulevard, 30A, 012104 Bucharest, Romania
    Academy of Romanian Scientists, Ilfov Street 3, 050094 Bucharest, Romania
    National Institute for Economic Research “Costin C. Kiritescu”, Romanian Academy, Casa Academiei Române, Calea 13 Septembrie nr. 13, 050711 Bucharest, Romania)

  • Luise Mladen-Macovei

    (National Scientific Research Institute for Labor and Social Protection, Povernei Street 6, 010643 Bucharest, Romania)

Abstract

Intersectoral labour mobility is a key driver of economic resilience and innovation in Europe. The redistribution of workers across sectors and regions enables economies to adapt to shocks, create flexibility and increase the rate of structural change. However, the dynamics of mobility have not been adequately investigated across varying scales of sectoral granularity and spatio-temporal dimensions. This paper applies the Intersectoral Mobility Index (MI) to all European NUTS-2 areas from 2008 to 2020, utilising Eurostat Structural Business Statistics. Two levels of sectoral aggregation (NACE Rev. 2, 1-digit and 2-digit) are employed to compute MI, capturing both broad and fine-grained reallocations. Classical indices of structural change (NAV, Krugman, Shorrocks) are combined with spatio-temporal modelling in ArcGIS Pro, employing Space–Time Cubes, time-series exponential smoothing forecasts, time-series clustering and emerging hot spot analysis. Results indicate that MI distributions are positively skewed and heavy-tailed, with peaks coinciding with systemic crises (2009–2011, 2020). At the 2-digit level, MI values are significantly higher, revealing intra-sectoral changes obscured in aggregated data. A statistically significant downward trend in mobility suggests an increasing structural rigidity following the global financial crisis. Regional clustering highlights heterogeneity: a small number of regions, such as Bremen, Madeira and the Southern Great Plain, have sustained high or unstable mobility, while most exhibit convergent mobility and low reallocation. This paper contributes to the conceptualisation of MI as a dual measure of resilience and innovation preparedness. It underscores the importance of multi-scalar and spatio-temporal methods in monitoring labour market flexibility. The findings have policy implications, including the design of targeted reskilling programmes, proactive labour market policies and just transition plans to maintain regional resilience during the EU’s green and digital transitions.

Suggested Citation

  • Cristina Lincaru & Camelia Speranta Pirciog & Adriana Grigorescu & Luise Mladen-Macovei, 2025. "Intersectoral Labour Mobility in Europe as a Driver of Resilience and Innovation: Evidence from Granularity and Spatio-Temporal Modelling," Sustainability, MDPI, vol. 17(22), pages 1-35, November.
  • Handle: RePEc:gam:jsusta:v:17:y:2025:i:22:p:10333-:d:1797609
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