Automation and the risk of labor market exclusion across Europe

• We analyse the effect of automation on individual odds of labour market exclusion, as measured by long-term unemployment and inactivity, across 27 European countries and the United Kingdom between 2009 and 2019. • We employ repeated cross-sections of individual-level data to compute probabilities of exclusion outcomes due to automation adoption, controlling for several individual, macroeconomic, and region-specific characteristics, and for potential selection mechanisms. • On average, the adoption of new automation technologies is associated with an increase in the probability of exclusion outcomes, although limited inactivity. • Our findings are consistent with the view that automation may exacerbate psychological discouragement and raise detachment from the labor force, increasing the unwillingness to seek jobs. • This relationship is heterogeneous across demographic groups, with younger individuals being relatively more affected. Labor market exclusion represents a major concern in several European economies, particularly affecting highly exposed demographic groups. This paper examines the potential effect of automation technologies on the risk of being locked into protracted unemployment or inactivity, using Labour Force Survey data for the European Union 27 countries and the United Kingdom, between 2009 and 2019. Our study employs repeated cross-sections of individual-level data to compute probabilities of exclusion outcomes due to automation adoption, controlling for several individual, macroeconomic, and region-specific characteristics, and for potential selection mechanisms. Findings highlight that, on average, the adoption of new automation technologies is associated with a higher probability of being inactive. This is consistent with the view that automation may exacerbate job insecurity, psychological discouragement, and detachment from job-seeking. This relationship is heterogeneous across demographic groups, with younger individuals being relatively more affected.