Bitte verwenden Sie diesen Link, um diese Publikation zu zitieren, oder auf sie als Internetquelle zu verweisen: http://hdl.handle.net/10419/191983
Autoren: 
Prettner, Klaus
Strulik, Holger
Datum: 
2019
Reihe/Nr.: 
GLO Discussion Paper 320
Zusammenfassung: 
We analyze the effects of R&D-driven automation on economic growth, education, and inequality when high-skilled workers are complements to machines and low-skilled workers are substitutes for machines. The model predicts that innovation-driven growth leads to an increasing population share of college graduates, increasing income and wealth inequality, and a declining labor share. We use the model to analyze the effects of redistribution. We show that it is difficult to improve income of low-skilled individuals as long as both technology and education are endogenous. This is true irrespective of whether redistribution is financed by progressive wage taxation or by a robot tax. Only when higher education is stationary, redistribution unambiguously benefits the poor. We show that education subsidies affect the economy differently depending on their mode of funding and that they may actually reduce education. Finally, we extend the model by fair wage concerns and show how automation could induce involuntary low-skilled unemployment.
Schlagwörter: 
Automation
Innovation-Driven Growth
Inequality
Wealth Concentration
Unemployment
Policy Responses
JEL: 
E23
E25
O31
O33
O40
Dokumentart: 
Working Paper
Nennungen in sozialen Medien:

Datei(en):
Datei
Größe
398.54 kB





Publikationen in EconStor sind urheberrechtlich geschützt.