NY Fed Macro Model: AI Investment Boom Explains Growth Surprises, but Medium-Term Outlook Stays Pessimistic
In their September 2026 structural model forecast update, New York Fed researchers attribute recent GDP outperformance primarily to AI-related investment shocks and looser financial conditions, rather than broad productivity gains. Consequently, the model lowers medium-term growth forecasts while expecting inflation to revert to target more slowly than previously projected.
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A September 2026 update to the Federal Reserve Bank of New York's structural macroeconomic model offers a specific causal explanation for the U.S. economy's recent resilience. The model decomposes the economy into interacting households, firms, and policy authorities. Its central finding is that current growth exceeding June expectations is not driven by widespread productivity improvements, but rather by two key factors: more buoyant financial conditions than anticipated and positive growth effects from the artificial intelligence-related boom in investment, captured as marginal efficiency of investment shocks.
Specifically, the Philadelphia Fed Survey of Professional Forecasters projects that annualized GDP growth in the third quarter of 2026 will be more than 1 percent higher than what the model expected in June. The authors note that, assuming the SPF projection is correct, the model attributes this likely forecast miss to these AI-driven investment effects and loose financial conditions. However, this sector-specific capital expenditure surge has not altered the model's pessimistic view of long-term fundamentals. Due to downward revisions in total factor productivity growth expectations, the model forecasts slower GDP growth for future years: 0.1 percent in 2027, 0.5 percent in 2028, and 1.2 percent in 2029, all lower than the June projections of 0.2, 0.7, and 1.5 percent respectively.