Publications - Working Papers IER SAS

Due to automation’s impact on the labour market, publicly funded training programs have gained increased attention. This paper explores a training program provided to job seekers in Slovakia, the OECD country with the highest average automation risk. The scheme allows job seekers to choose their training specialisation. We evaluate the most popular training specializations chosen by job seekers, which were gender-divided, with healthcare workers, beauticians and accountants dominated by females and welders, drivers, and security guards dominated by males. Our findings suggest that job seekers, when allowed to select their specialization, use training to reduce their risk of automation. Female participants showed a preference for specializations targeting occupa-tions with a lower risk of automation. Training participation also reduced the automation risk of male participants, but mainly because they suffered a higher automation risk in their previous oc-cupations. We apply double machine learning to estimate the average treatment effect of training participation under the unconfoundedness assumption. In line with existing empirical studies, our results indicate a negative lock-in effect in the short run and a positive employment effect in the long run. Furthermore, our data allowed us to observe different stories related to particular train-ing specializations. Some training specializations are used as a means to find employment abroad or enter the informal sector. Other training specializations provide opportunities for low-skilled job seekers to obtain within-country employment in occupations with a lower risk of automation.