AI investment and green innovation bolster long-run sustainable growth in both the United States and China, with AI delivering larger long-run gains in the US and green-tech driving bigger benefits in China; rising tariffs, however, blunt these gains by hampering trade- and technology-driven efficiency.

Main Finding

AI investment, green innovation, and trade openness are long-run determinants of sustainable economic growth (SEG) in both China and the United States over 2015Q1–2025Q4 under the Trump Tariff 2.0 policy environment. AI investment and green innovation positively affect SEG in both countries (AI's long-run effect is stronger in the U.S.; green innovation's contribution is larger in China). Trade openness boosts SEG in China but has a weaker effect in the U.S., while increased tariff protection harms SEG by reducing trade- and technology-related efficiency gains.

Key Points

• Long-run cointegration exists among AII (AI investment), GI (green innovation), TO (trade openness), and SEG in both countries.
• AI investment (AII)
  • Positive and statistically significant impact on SEG in both China and the U.S.
  • Long-run effect stronger in the United States than in China.
• Green innovation (GI)
  • Promotes SEG in both countries.
  • Relative contribution to SEG is larger in China, consistent with rapid expansion in renewable-energy and environmental-innovation activity.
• Trade openness (TO)
  • Positively influences SEG in China.
  • Exhibits a weaker (less pronounced) positive effect in the United States, indicating heterogeneous trade–growth dynamics across the two economies.
• Tariff protection (Trump Tariff 2.0)
  • Increasing tariff protection reduces SEG by undermining efficiency gains from international trade and slowing technology diffusion.

Data & Methods

• Sample period: quarterly data from 2015Q1 to 2025Q4.
• Countries analyzed: China and the United States.
• Variables: sustainable economic growth (SEG) as dependent variable; AI investment (AII), green innovation (GI), trade openness (TO), and tariff-protection measures (policy environment) as explanatory factors.
• Econometric approach:
  • Country-specific Autoregressive Distributed Lag (ARDL) models to capture both short-run dynamics and long-run relationships.
  • Cointegration testing confirmed long-run relationships among the variables in both economies.
  • Results reported for short-run and long-run effects, with statistical significance noted for main coefficients (AII, GI, TO, tariffs), and cross-country differences examined.

Implications for AI Economics

• Policy and investment
  • Strengthening AI investment is likely to yield sustained gains in SEG; the U.S. appears to capture larger long-run growth benefits per unit of AI investment than China, suggesting possible complementarities with existing technological, institutional, or human-capital endowments.
  • Promoting green innovation remains crucial, especially for China where GI has shown a larger growth payoff—support for renewable-energy R&D and environmental technologies can magnify sustainable growth outcomes.
• Trade and technology diffusion
  • Maintaining open and resilient international trade systems supports SEG by facilitating technology transfer and efficiency gains; protectionist tariffs dampen these channels and reduce growth.
  • The weaker association between trade openness and SEG in the U.S. suggests country-specific factors (e.g., domestic market structure, supply-chain resilience, or absorptive capacity) mediate trade-growth returns—policy should consider these heterogeneities.
• Balanced policy under geopolitical uncertainty
  • Policymakers should balance industrial and trade-policy goals: targeted support for domestic AI and green-innovation capabilities, coupled with measured trade policies that avoid large-scale tariff barriers, will better sustain long-run growth.
• Research directions
  • Investigate the mechanisms behind the stronger U.S. long-run AI–growth effect (e.g., complementarities with human capital, services sector composition, or institutional quality).
  • Examine distributional and sectoral impacts of AI and GI on growth, and the role of supply-chain reconfiguration under tariff regimes.
  • Assess robustness to alternative measures of AI activity, GI, and tariff intensity, and potential nonlinearity or threshold effects in the AII–SEG relationship.