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AI subsidies as a tool for redistribution
[Subventions à l’IA comme outil de redistribution]

Author

Listed:
  • Lucas Parmentier

    (CEMOI - Centre d'Économie et de Management de l'Océan Indien - UR - Université de La Réunion)

Abstract

I study the optimal taxation of artificial intelligence (AI). My analysis highlights a wage-compression effect that provides a rationale for subsidizing AI, as AI adoption may reduce rather than increase wage inequality. When this effect outweighs AI's social costs, AI should be subsidized instead of taxed. I treat AI as a productive input distinct from robots, as the two technologies perform different ranges of tasks. Using numerical simulations, I demonstrate that the optimal policy for AI may differ sharply from that for robots. Under the benchmark calibration, AI is subsidized, whereas robots are taxed. Therefore, the case for taxing AI is weaker than is commonly assumed. When AI lowers the skill premium, fiscal policy may need to encourage, rather than slow, adoption.

Suggested Citation

  • Lucas Parmentier, 2026. "AI subsidies as a tool for redistribution [Subventions à l’IA comme outil de redistribution]," Post-Print hal-05748060, HAL.
    • Handle: RePEc:hal:journl:hal-05748060
    DOI: 10.1016/j.econmod.2026.107817
    Note: View the original document on HAL open archive server: https://hal.science/hal-05748060v1
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    JEL classification:

    • D31 - Microeconomics - - Distribution - - - Personal Income and Wealth Distribution
    • H21 - Public Economics - - Taxation, Subsidies, and Revenue - - - Efficiency; Optimal Taxation
    • J31 - Labor and Demographic Economics - - Wages, Compensation, and Labor Costs - - - Wage Level and Structure; Wage Differentials
    • O33 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Technological Change: Choices and Consequences; Diffusion Processes

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