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The Impact of Industrial Robots on EU Employment and Wages

Verantwortlicher Autor: Carlo Marino Rome/Brussels, 23.04.2018, 14:04 Uhr
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Rome/Brussels [ENA] An interesting Working Paper - The Impact of Industrial Robots on EU Employment and Wages: A Local Labour Market Approach- has been recently published by the European think tank specializing in economics and established in 2005: Bruegel. It is an independent and non-doctrinal think tank. The authors of this working paper Francesco Chiacchio, Georgios Petropoulos and David Pichler

studied the impact of industrial robots on employment and wages in six European Union countries, which make up 85.5 percent of the EU industrial robots market. Since the start of the Industrial Revolution about 200 years ago, technological development has significantly redesigned life and work. Revolutionary innovations allow easy communication and travel within and between countries, use less energy to do the housework and offer instant access to any kind of information. However, machines and software can radically outsmart workers in many tasks, leaving workers at risk of substitution.

Technological expansion, and especially, digitalization has major implications for labour markets. The assessment of the impact of digitalization on employment is very important for getting specific policy recommendations that can lead to the efficient functioning of the labour market for the benefit of workers, employers and society as a whole. In theory, robots can completely supplant workers from performing specific tasks (displacement effect). But they can also expand labour demand through the efficiencies they bring to industrial production (productivity effect). The research adopts the local labour market equilibrium approach developed by Acemoglu and Restrepo (2017) to assess which of the two labour market effects dominates.

Studying additional dimensions of the impact of robots, the authors found that the displacement effect is mainly prominent for workers of middle education, for young cohorts and for men. The estimates, however, did not point to significant results for wage growth, even after accounting for possible counterbalancing effects across different population or sectoral groups. In fact, there are three methods to assessing the impact of automation on employment. A first approach is to analyze previous industrial revolutions and explore the impact of technological advances on labour and associated industries: the introduction of automobiles in daily life led to a waning in horse-related jobs, for instance.

On the other side, new industries developed resulting in a positive impact on employment. It was not only that the automobile industry itself grew rapidly, increasing the available jobs in the sector. Jobs were also created in different sectors because of the growing number of vehicles on the roads. New jobs were created in the motel and fast-food industries that arose to serve motorists and truck drivers. That means a significant displacement effect. The displacement effect is particularly manifest for workers of middle education and for young cohorts, while men are more affected than women. As noted by Acemoglu and Restrepo (2017), technological innovations can affect employment in two main ways:

by directly displacing workers from tasks they were previously performing (displacement effect) or by increasing the demand for labour in industries or jobs that are the result of technological progress (productivity effect). Consequently, in order to analyze holistically the impact of artificial intelligence systems on industrial production, the question then becomes: which of the two effects – displacement or productivity – dominate in the artificial intelligence (AI) era?

The authors took into account the impact of one automated technology – industrial robots – on employment and wages in six EU countries: Finland, France, Germany, Italy, Spain and Sweden, which account for 85.5 percent of the EU robots market in 2007. By adopting this approach, it has been possible to exploit exogenous changes at the local level and control for detailed demographic variables and study the impact of robots on sector and occupational-level variables. In general, past industrial revolutions imply that in the short run the displacement effect might dominate. But in the longer run, the productivity effect can dominate and lead to a positive impact on employment.

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