The lost race against the machine: Automation, education, and inequality in an R&D-based growth model
Klaus Prettner () and
Holger Strulik ()
No 329, University of Göttingen Working Papers in Economics from University of Goettingen, Department of Economics
We analyze the effects of automation and education on economic growth and inequality in an R&D-based growth model with two types of labor: high-skilled labor that is complementary to machines and low-skilled labor that is a substitute for machines. The model predicts that innovation-driven growth leads to increasing automation, an increasing skill premium, an increasing population share of college graduates, increasing income and wealth inequality, and a declining labor share. In contrast to conventional wisdom, our theory predicts that faster economic growth promotes inequality. Because education and technology are endogenous, redistribution to low-skilled individuals may actually not improve disposable low-skilled income, irrespective of whether it is financed by taxes on labor income or machine input in production. We extend the model by fair wage concerns and show how automation implies involuntary low-skilled unemployment.
Keywords: Automation; R&D-Based Growth; Inequality; Wealth Concentration; Unemployment; Redistribution (search for similar items in EconPapers)
JEL-codes: E23 E25 O31 O33 O40 (search for similar items in EconPapers)
New Economics Papers: this item is included in nep-gro, nep-ino and nep-mac
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Working Paper: The lost race against the machine: Automation, education and inequality in an R&D-based growth model (2017)
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Persistent link: https://EconPapers.repec.org/RePEc:zbw:cegedp:329
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