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Innovation, automation, and inequality: Policy challenges in the race against the machine

Klaus Prettner () and Holger Strulik ()

Journal of Monetary Economics, 2020, vol. 116, issue C, 249-265

Abstract: The effects of automation on economic growth, education, and inequality are analyzed using an R&D-driven growth model with endogenous education in which high-skilled workers are complements to machines and low-skilled workers are substitutes for machines. The model predicts that automation leads to an increasing share of college graduates, increasing income and wealth inequality, and a declining labor share. We show that standard policy suggestions for the age of automation can trigger unintended side effects on inequality, growth, and welfare, irrespective of whether they are financed by progressive wage taxation or by a robot tax.

Keywords: Automation; Education; Innovation-Driven growth; Inequality; Policy responses (search for similar items in EconPapers)
JEL-codes: E23 E25 H23 O31 O33 O40 (search for similar items in EconPapers)
Date: 2020
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Working Paper: Innovation, Automation, and Inequality: Policy Challenges in the Race against the Machine (2019) Downloads
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Persistent link: https://EconPapers.repec.org/RePEc:eee:moneco:v:116:y:2020:i:c:p:249-265

DOI: 10.1016/j.jmoneco.2019.10.012

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