A new analysis from the Federal Reserve Bank of Chicago finds that whether the central bank should raise or cut interest rates in response to productivity growth depends entirely on whether people see it coming. When productivity surges are fully anticipated, rates should climb about 50 basis points for a 1 percentage point annual increase over ten years. But when the same growth arrives as a surprise, rates should drop roughly 75 basis points. The research, published in Chicago Fed Letter 528 in 2026, uses a standard economic model to show why expectations about artificial intelligence and other productivity-boosting technologies matter as much for monetary policy as the gains themselves.
The report notes that nonfarm private business labor productivity has been growing at about 2.5% per year since the pandemic recovery, compared with a pre-pandemic average of 1.1%. The acceleration began soon after ChatGPT's public debut in late 2022. The analysis simulates a ten-year productivity surge of 1 percentage point per year above the baseline. When that surge is unanticipated—meaning people expect growth to return to normal each period—inflation falls and the natural rate of interest stays flat. When the same surge is fully expected, inflation still declines by about the same amount, but the natural rate of interest rises because consumers try to spend more now in anticipation of higher future income.
Chicago Fed President Austan Goolsbee laid out the framework in a May 2026 speech at Stanford's Hoover Institution, drawing parallels to the 1990s productivity boom. The report explains that in the mid-1990s, Fed Chairman Alan Greenspan argued against rate hikes because he suspected productivity was rising even though the data hadn't confirmed it yet. By the late 1990s, once productivity gains were widely expected, the Federal Reserve raised rates six times in less than a year to prevent the economy from overheating. The authors write that if the central bank waits to act until inflation and output gaps appear rather than tracking the natural rate of interest in real time, it ends up with much higher inflation and has to raise rates even more aggressively later.
Why does timing matter so much? When people know extra productivity growth is on the way, they anticipate higher lifetime income and try to boost consumption immediately—but most of the productivity gains haven't materialized yet, so capacity hasn't expanded. That mismatch threatens to overheat the economy, forcing the central bank to raise the return on saving and cool demand. The natural rate of interest climbs because of anticipated consumption growth, and a Taylor rule that tracks it calls for higher nominal rates. When productivity gains arrive unexpectedly, there's no reason to pull spending forward. Costs and inflation drop as wages lag the productivity jump, and the Taylor rule responds to lower inflation by cutting rates. Federal Reserve Governor Chris Waller suggested the wealth effects might be smaller in practice if consumers exhibit habit persistence or if many households are unable to borrow against future income, but the authors tested both scenarios and found the qualitative results hold even with realistic adjustments.
The bottom line: productivity growth benefits the economy, but the report concludes that its implications for interest rates hinge on expectations. If a surge happens without warning, central bankers following a Taylor rule that tracks the natural rate should probably cut nominal rates. But the more that productivity growth is expected to arrive in the future, the more it pulls economic activity into the present—and the more necessary it becomes to push rates up now to prevent overheating. With surveys showing economists, tech leaders, and the public all expecting significant AI-driven productivity gains over the next decade, the research suggests the Federal Reserve may need to tighten policy preemptively rather than wait for the gains to show up in the data.