Understanding the impact of AI on global economies is imperative as it continues to dominate. While much attention has been given to the direct effects of AI in the U.S., the broader spillover effects to foreign markets remain underexplored. The challenge is to quantify and analyse spillover effects, particularly the interaction between tax policies and AI investments, and to understand the long-term implications for productivity and economic growth.

The research employs a three-step empirical approach. First, it estimates the time-lagged effects of AI investments on subsidiary-level outcomes, such as employment and asset growth, using a local projection methodology. This approach incorporates fixed effects for country-year and industry-year to account for local economic trends. Second, it examines how European host countries’ tax regimes mediate the spillover effects of AI investments, focusing on measures like effective tax rates and R&D tax incentives. Third, it uses a Bartikstyle shift-share instrument to link country-industry exposure to U.S. AI investments with host country tax policies. This analysis combines aggregate and administrative data on employment, innovation, and productivity to assess how tax policies influence the timing and strength of economic growth driven by AI investments.

This research has the potential to reshape understanding of the global economic impact of AI, particularly by shedding light on the crucial role of tax policy in amplifying these effects. This research provides novel insights into the global economic impact of AI investments, highlighting the role of tax policy in shaping these outcomes. By connecting corporate innovation to taxation and local market growth, the findings will inform policy debates on industrial strategy and the taxation of multinational firms’ profits.