Investing.com -- Federal Reserve Bank of New York President John Williams said Thursday that understanding structural economic change as it happens remains one of the most fundamental challenges for economic policymakers, with shifts in productivity growth particularly difficult to identify in real time.

Speaking at the Reykjavík Economic Conference in Iceland, Williams focused on how economies respond to changes in productivity growth rates and the implications for monetary policy. He noted the question becomes especially relevant amid current attention on artificial intelligence and its potential economic effects.

Williams pointed to historical examples, including the productivity slowdown of the 1970s following a quarter century of postwar growth, an acceleration beginning in the mid-1990s, and a subsequent slowdown in the mid-2000s. The 1970s productivity slowdown contributed to stagflation, while the late 1990s and early 2000s boom was a contributing factor to that decade’s economic prosperity with low inflation, he said.

The New York Fed president highlighted what he termed the recognition problem, noting that while shifts in trend productivity growth may appear clear in hindsight, it often takes years to distinguish them from normal data fluctuations. Year-over-year productivity growth swings from minus 2% to 7%, compared to a long-run average of just over 2%, according to data Williams cited.

During the 1970s, estimates of trend productivity growth from the Council of Economic Advisers declined gradually through most of the decade, then dropped sharply in 1979, many years after the slowdown had begun, Williams said. This pattern repeated in the mid-1990s and mid-2000s.

Williams said the macroeconomic implications of gradual recognition are profound. Standard economic theories predict that an increase in trend productivity growth drives up real interest rates and causes an economic downturn, with hours worked, investment and output declining. These predictions contradict real-world experience where periods of high productivity growth are associated with a strong economy and elevated investment, he noted.

Model simulations using the New York Fed’s dynamic stochastic general equilibrium model show that incorporating gradual recognition dramatically alters predictions. When trend productivity accelerates but agents only gradually recognize this, they initially interpret the rise in productivity growth as primarily a one-time shift not to be repeated, Williams said.

An increase in productivity growth also reduces costs that businesses face, contributing to downward pressure on inflation until prices and wages fully adjust, Williams said. The size and duration of this effect depend on how quickly businesses and households recognize the shift in productivity growth.

Williams emphasized that real-time identification of structural change is extraordinarily difficult, and expectations of future growth tend to adjust gradually to changes in underlying productivity growth. He said shifts in productivity growth are relatively infrequent and inherently highly uncertain, with large confidence bands around any estimates.