AI, Automation, and Taxation

Spencer Bastani and Daniel Waldenström ()
Additional contact information
Daniel Waldenström: Research Institute of Industrial Economics (IFN), Postal: Research Institute of Industrial Economics, Box 55665, SE-102 15 Stockholm, Sweden, https://www.ifn.se/en/researchers/ifn-researcher/daniel-waldenstrom/

No 1501, Working Paper Series from Research Institute of Industrial Economics

Abstract: This chapter examines the implications of Artificial Intelligence (AI) and automation for the taxation of labor and capital in advanced economies. It synthesizes empirical evidence on worker displacement, productivity, and income inequality, as well as theoretical frameworks for optimal taxation. Implications for tax policy are discussed, focusing on the level of capital taxes and the progressivity of labor taxes. While there may be a need to adjust the level of capital taxes and the structure of labor income taxation, there are potential drawbacks of overly progressive taxation and universal basic income schemes that could undermine work incentives, economic growth, and long-term household welfare.

Keywords: AI; Automation; Inequality; Labor Share; Optimal Taxation; Tax Progressivity (search for similar items in EconPapers)
JEL-codes: H20 H21 (search for similar items in EconPapers)
Pages: 19 pages
Date: 2024-10-03
New Economics Papers: this item is included in nep-ain, nep-ltv, nep-pbe and nep-tid
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Citations: View citations in EconPapers (2)

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Related works:
Chapter: AI, automation and taxation (2024)
Working Paper: AI, Automation and Taxation (2024)
Working Paper: AI, Automation and Taxation (2024)
Working Paper: AI, Automation and Taxation (2024)
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