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News article9 April 2019

Assessing the impact of job automation in the regions of the European Union

Job automation
© European Commission

A recently published JRC analysis in the OECD Regional Outlook 2019 provides a quantitative assessment of the impact of job automation on the regional economies of the European Union.

The analysis has been carried out with the spatial dynamic general equilibrium model (RHOMOLO) developed by the Regional Economic Modelling team of JRC Seville in collaboration with DG REGIO (see Lecca et al., 2018). The simulations rely on the assumption that the efficiency of capital is assumed to rise with technological progress in automation, increasing the number of tasks that robots can perform and the quality with which they handle such tasks. This is modelled with an increase in the productivity of capital, which can be thought of a situation in which as robots evolve, the amount of output that can be produced for a given investment in capital will increase.

This positive productivity shock will lead to an increase in output. The improvement in capital efficiency not only translates into direct output gains as the same amount of capital can now produce more output, but it also creates extra gains from increased capital investment. On average, households enjoy this development. Increased efficiency of the capital stock that workers use to produce output increases their productivity and therefore the wages for those in employment increase too. Households also benefit from lower prices given that productive efficiency increases. However, not all workers and regions will benefit the same.

The regional results

The working assumption is that technological change will be complementary to the skills of the highly educated workers, while workers with low or intermediate levels of education can be replaced by both more capital and more high-skilled workers. Consequently, automation creates stronger benefits in regions with a more educated workforce (more developed regions) and those with higher capital intensity, which on the contrary tends to favour less developed regions (the capital share is 45% in less developed regions as opposed to 39% in more developed regions and 38% in transition regions).

The positive effect of having a larger percentage of skilled workers dominates. The total labour income generated in more developed regions increases by about 0.12% for a 5% shock in capital productivity, while less developed and transition regions lose a labour income share by about 0.8% and 0.11%, respectively. Highly educated workers increase their labour share in all three types of regions, by 1% in less developed and transition regions and by more than double that percentage in more developed regions. Workers with low and intermediate levels of education lose income shares in all types of regions, but particularly in less developed regions where their income shares drop by 1.5% and more.

Further information

OECD Regional Outlook 2019


Publication date
9 April 2019