Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/210446
Authors: 
Blanas, Sotiris
Gancia, Gino Alessandro
Lee, Sang Yoon
Year of Publication: 
2019
Series/Report no.: 
Working Paper No. 889
Abstract: 
We study how various types of machines, namely, information and communication technologies, software, and especially industrial robots, affect the demand for workers of different education, age, and gender. We do so by exploiting differences in the composition of workers across countries, industries and time. Our dataset comprises 10 high-income countries and 30 industries, which span roughly their entire economies, with annual observations over the period 1982-2005. The results suggest that software and robots reduced the demand for low and medium-skill workers, the young, and womenspecially in manufacturing industries; but raised the demand for high-skill workers, older workers and menspecially in service industries. These findings are consistent with the hypothesis that automation technologies, contrary to other types of capital, replace humans performing routine tasks. We also find evidence for some types of workers, especially women, having shifted away from such tasks.
Subjects: 
Automation
Robots
Employment
Labor Demand
Labor Income Share
JEL: 
J21
J23
O33
Document Type: 
Working Paper

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