S11-S2 The regional socio-economic impact of the 4th industrial revolution
Tracks
Special Session
| Wednesday, August 28, 2019 |
| 4:30 PM - 6:00 PM |
| UdL_Room 104 |
Details
Convenor(s): Camilla Lenzi, Roberta Capello / Chair: Camilla Lenzi
Speaker
Dr. Massimiliano Nuccio
Senior Researcher
Ca' Foscari University of Venice
Patterns of specialization and robots adoption: A regional perspective in Italy and UK
Author(s) - Presenters are indicated with (p)
Massimiliano Nuccio (p), Marco Guerzoni, Aldo Geuna, Riccardo Cappelli
Discussant for this paper
Patrizio Lecca
Abstract
Most of the recent literature on the development of robotics has studied the relationship between robots adoption and employment at the country level and only in a recent report OECD (2018) has examined the issue at the regional level. This paper focuses on the regional antecedents of robots adoption investigating those features of industrial structure, which favour the shift to advanced automation.
The paper provides also methodological contribution as it applies an innovative unsupervised algorithm (SOM) to classify regions based on their industrial structure; comparing our results with the more traditional measures of related and unrelated variety we highlight the limitations of the latter constructs.
The analysis relies on NACE industrial re-classification of employment data for 137 NUTS2 regions in the five largest European economies (Germany, France, UK, Italy and Spain) and data on acquisitions of industrial robots provided by the IFR (2017) and rescaled at the regional level. We consider the two periods of growth in between the crisis: 2001-2007 and 2013-2015. After selecting and outlining the 9 industrial patterns generated by the SOM algorithm, we provide new evidence on the relationship between industrial structure and robot penetration, considering the 2008 financial crisis as either an opportunity for firms to change and move into Industry 4.0 or a threat to survival.
Key words: Industrial structure, industrial specialization, robotics, innovation
JEL classifications: E32, R11, R12
The paper provides also methodological contribution as it applies an innovative unsupervised algorithm (SOM) to classify regions based on their industrial structure; comparing our results with the more traditional measures of related and unrelated variety we highlight the limitations of the latter constructs.
The analysis relies on NACE industrial re-classification of employment data for 137 NUTS2 regions in the five largest European economies (Germany, France, UK, Italy and Spain) and data on acquisitions of industrial robots provided by the IFR (2017) and rescaled at the regional level. We consider the two periods of growth in between the crisis: 2001-2007 and 2013-2015. After selecting and outlining the 9 industrial patterns generated by the SOM algorithm, we provide new evidence on the relationship between industrial structure and robot penetration, considering the 2008 financial crisis as either an opportunity for firms to change and move into Industry 4.0 or a threat to survival.
Key words: Industrial structure, industrial specialization, robotics, innovation
JEL classifications: E32, R11, R12
Dr. Patrizio Lecca
Associate Professor
Icade, Universidad Pontificia Comillas
The Impact of Automation at Regional Level
Author(s) - Presenters are indicated with (p)
Patrizio Lecca (p), Damiaan Persyn, Stelios Sakkas, Simone Salotti, Conte Andrea
Discussant for this paper
Camilla Lenzi
Abstract
see extended abstract
Prof. Camilla Lenzi
Full Professor
Politecnico di Milano - DABC
The regional socio-economic impact of the 4th industrial revolution
Author(s) - Presenters are indicated with (p)
Roberta Capello , Camilla Lenzi (p)
Discussant for this paper
Massimiliano Nuccio
Abstract
The regional socio-economic impact of the 4th industrial revolution
The so-called 4th industrial revolution (or Industry 4.0) is expected to lead societies and economies to adapt and to undertake pervasive, if not disruptive, transformations. These transformations, however, raise imperative alarms about the substitution effect of the new technologies with respect to labour and the risks of the so-called technological unemployment because of “functions – and tasks within functions – at risk of automation” (Goos et al., 2014; Nedelkoska and Quintini, 2018).
Differently from previous technological revolutions, however, the present one implies an increasing automation not only of routine tasks but also of non-routine ones, having thus the potential of transformative, if not, disruptive effects on the economy and the society through the impact on whole sets of sectors and occupations (Frey and Osborne, 2017).
The pervasiveness of such effects, therefore, requires a deep understanding of the mechanisms enabling to take advantage of the opportunities opened by the new technologies (i.e. the maximization of the economic benefits in terms of productivity and growth,) while minimizing the social costs that may arise in terms of restructuring of the labor market, possible unemployment growth and widening social and spatial inequalities.
The present paper offers a conceptual reflection on the territorial dimension of such processes, which has only recently received some attention (Autor and Dorn, 2013; OECD, 2018). By empirically reviewing the advancement of the penetration of technological transformations in European regions, the paper will discuss the territorial mechanisms favouring the emergence of the new technologies in specific places and will identify the territorial assets favouring the creation and diffusion of these technologies. These reflections will help framing the scientific and policy debate about the potential impact of the current technological revolution on jobs and productivity.
References
Autor D. and Dorn D. (2013) “The growth of low-skill service jobs and the polarization of the US labor market” American Economic Review 103(5): 1153-1597
Frey C.B. and Osborne M.A. (2017) “The future of employment: How susceptible are jobs to computerisation?”, Technological Forecasting and Social Change, 114(C), 254-280
Goos M., Manning A., Salomons A. “Explaining job polarization: Routine-biased technological change and offshoring”, American Economic Review, 104(8): 2509-2526
Nedelkoska L. and Quintini G. (2018) “Automation, skills use and training” OECD Social, Employment and Migration WP N 202
OECD (2018) Job creation and local economic development: Preparing for the future of work, OECD Publishing, Paris
The so-called 4th industrial revolution (or Industry 4.0) is expected to lead societies and economies to adapt and to undertake pervasive, if not disruptive, transformations. These transformations, however, raise imperative alarms about the substitution effect of the new technologies with respect to labour and the risks of the so-called technological unemployment because of “functions – and tasks within functions – at risk of automation” (Goos et al., 2014; Nedelkoska and Quintini, 2018).
Differently from previous technological revolutions, however, the present one implies an increasing automation not only of routine tasks but also of non-routine ones, having thus the potential of transformative, if not, disruptive effects on the economy and the society through the impact on whole sets of sectors and occupations (Frey and Osborne, 2017).
The pervasiveness of such effects, therefore, requires a deep understanding of the mechanisms enabling to take advantage of the opportunities opened by the new technologies (i.e. the maximization of the economic benefits in terms of productivity and growth,) while minimizing the social costs that may arise in terms of restructuring of the labor market, possible unemployment growth and widening social and spatial inequalities.
The present paper offers a conceptual reflection on the territorial dimension of such processes, which has only recently received some attention (Autor and Dorn, 2013; OECD, 2018). By empirically reviewing the advancement of the penetration of technological transformations in European regions, the paper will discuss the territorial mechanisms favouring the emergence of the new technologies in specific places and will identify the territorial assets favouring the creation and diffusion of these technologies. These reflections will help framing the scientific and policy debate about the potential impact of the current technological revolution on jobs and productivity.
References
Autor D. and Dorn D. (2013) “The growth of low-skill service jobs and the polarization of the US labor market” American Economic Review 103(5): 1153-1597
Frey C.B. and Osborne M.A. (2017) “The future of employment: How susceptible are jobs to computerisation?”, Technological Forecasting and Social Change, 114(C), 254-280
Goos M., Manning A., Salomons A. “Explaining job polarization: Routine-biased technological change and offshoring”, American Economic Review, 104(8): 2509-2526
Nedelkoska L. and Quintini G. (2018) “Automation, skills use and training” OECD Social, Employment and Migration WP N 202
OECD (2018) Job creation and local economic development: Preparing for the future of work, OECD Publishing, Paris
