Fiscal policy and human capital in the race against the machine

Daniele Angelini (), Stefan Niemann and Florian Roeser ()
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Florian Roeser: University of Konstanz

No 2024-01, Working Paper Series of the Department of Economics, University of Konstanz from Department of Economics, University of Konstanz

Abstract: We analyze the policy trade-offs facing fiscal policy in a dynamic growth model with au-tomation, education choice, and human capital formation. Although beneficial for economic growth, automation contributes to wage inequality. When human capital formation is affected by government spending, fiscal policy can enhance welfare through a coordinated increase in labor and robot taxes. The composition of taxes financing spending on transfers and educa-tion is key in determining the effects on economic growth and inequality, as the robot tax is the more redistributive instrument. We calibrate our model to the US economy and determine the welfare-maximizing tax policy. Optimality requires an initial reduction in the robot tax to foster automation-driven growth, followed by its gradual increase to address widening inequal-ity. Education subsidies can be welfare-improving if they are financed through the labor tax without compromising higher education spending. Finally, we explore robustness under private contributions to higher education.

Keywords: Automation; Education; Human capital; Innovation-driven growth; Inequality; Policy responses (search for similar items in EconPapers)
JEL-codes: E23 E25 H23 H52 O31 O33 O40 (search for similar items in EconPapers)
Date: 2024-02-01
New Economics Papers: this item is included in nep-dge, nep-gro, nep-pub and nep-tid
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Related works:
Working Paper: Fiscal Policy and Human Capital in the Race Against the Machine (2023)
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