The paper investigates whether the penetration of advanced manufacturing technologies can be better explained at the regional or national level. If regional effects prevail, policy actions would focus on local investments, while if country effects make regional covariates redundant, they should be redirected to more structural reform of the national systems of innovation. In this respect, the contribution is 2-fold. First, data on acquisitions of industrial robots in the five largest European economies are rescaled at regional levels to draw a clear picture of winners and losers in the robotics race after the 2008 financial crisis. Second, we explain differential of growth rates in robot adoption with (1) traditional measures of industrial variety, (2) an unsupervised machine learning approach classifying a region’s industry profile (3) usual determinants of innovation and, thereafter test the robustness of the results when country effects are added. As the main result, we highlight a process of regional convergence in which country-fixed effects hold greater explanatory power, although related variety and the number of skilled people are statistically significant regional explanatory factors. We do not discover a specific industry mix associated with the rise of adoption, but we highlight the one associated with its decline.

The diffusion of industrial robots in Europe: regional or country effect?

Massimiliano Nuccio;
2024-01-01

Abstract

The paper investigates whether the penetration of advanced manufacturing technologies can be better explained at the regional or national level. If regional effects prevail, policy actions would focus on local investments, while if country effects make regional covariates redundant, they should be redirected to more structural reform of the national systems of innovation. In this respect, the contribution is 2-fold. First, data on acquisitions of industrial robots in the five largest European economies are rescaled at regional levels to draw a clear picture of winners and losers in the robotics race after the 2008 financial crisis. Second, we explain differential of growth rates in robot adoption with (1) traditional measures of industrial variety, (2) an unsupervised machine learning approach classifying a region’s industry profile (3) usual determinants of innovation and, thereafter test the robustness of the results when country effects are added. As the main result, we highlight a process of regional convergence in which country-fixed effects hold greater explanatory power, although related variety and the number of skilled people are statistically significant regional explanatory factors. We do not discover a specific industry mix associated with the rise of adoption, but we highlight the one associated with its decline.
2024
TBC
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10278/5083404
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