The productivity and unemployment effects of the digital transformation: an empirical and modelling assessment
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The productivity and unemployment effects of the digital transformation: an empirical and modelling assessment Filippo Bertani1 · Marco Raberto1
· Andrea Teglio2
Accepted: 28 September 2020 © The Author(s) 2020
Abstract For the last 30 years, the economy has been undergoing a massive digital transformation. Intangible digital assets, like software solutions, Web services, and more recently deep learning algorithms, artificial intelligence, and digital platforms, have been increasingly adopted thanks to the diffusion and advancements of information and communication technologies. Various observers argue that we could rapidly approach a technological singularity leading to explosive economic growth. The contribution of this paper is on the empirical and the modelling sides. On the empirical side, we present a cross-country empirical analysis assessing the correlation between the growth rate of both tangible and intangible investments and different measures of productivity growth. Results show a significant correlation between intangible investments and both labor and total factor productivity in the period after the 2008 financial crisis. Similarly, both measures of productivity growth are correlated with a combination of both tangible and intangible investments which include information and communication technologies and software and database. These results are used to inform the enrichment of the agent-based macro-model Eurace that we employ to assess the long-term impact on unemployment of digital investments. Computational experiments show the emergence of technological unemployment in the long run with a high pace of intangible digital investments. Keywords Intangible assets · Digital transformation · Total factor productivity · Technological unemployment · Agent-based economics JEL Classification C63 Computational Techniques · Simulation Modeling; O33 Technological Change: Choices and Consequences
Filippo Bertani
[email protected]
Extended author information available on the last page of the article.
F. Bertani et al.
1 Introduction In his 1930 lecture “Economic possibilities for our grandchildren,” John Maynard Keynes predicted that in 100 years from then, i.e., around 2030, the production problem would be solved and there would be enough for everyone but machines would cause “technological unemployment.” McKinsey Global Institute in a recent report1 stated that the increasing adoption of automation technologies, including artificial intelligence and robotics, will generate significant benefits for the economy, raising productivity and economic growth, but with a far-reaching impact on the global workforce. In particular, according to the study, around half of current work activities are subject to be technically automatable by adapting current available technologies and, by 2030, 75 million to 375 million workers will be displaced by automation with the need to change occupation to avoid unemployment. Brian Arthur, one of the pioneers in studying the economics of the digital age, recently
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