U.S. legislators have a radical plan for the Federal Reserve, one of the world’s most powerful policy-making institutions: They want to remove human judgment from its decisions on where to set interest rates. It’s a terrible idea that could endanger the entire global economy.

The Fed’s monetary policy has long been set by the Federal Open Market Committee, which consists of the governors of the Federal Reserve Board, the president of the New York Fed and four regional Fed presidents on a rotating basis. Now, some legislators led by Jeb Hensarling, chairman of the House Financial Services Committee, want to replace this group of people with a fixed mechanical rule.





Known as the Taylor rule — after its inventor, Stanford University economist John Taylor — the rule crunches numbers such as inflation, output and potential growth, then spits out an interest rate that in theory should set the economy on the right course. Economists use the rule as a simple way to represent central bank policy-making in models, and for teaching students about monetary policy. Studies have shown that the rule is not a bad approximation of what many central banks do, particularly during normal times.

The past eight years, though, have not been normal times — demonstrating just how dangerous it would be to apply an academic simplification such as the Taylor rule to the real world. No fixed rule can ever substitute for human judgment in monetary policy, for three main reasons.

First, economies are not like physical systems with immutable laws. The state of the economy determines what policies we need, but the policies also shape the state of the economy. Back in the 1970s, when the British government was unsuccessfully trying to control inflation with a fixed rule focused on the quantity of money, the economist Charles Goodhart noted that “any observed statistical regularity will tend to collapse once pressure is placed on it for control purposes.” This became known as Goodhart’s law and has deterred central bankers ever since from relying too heavily on rigid rules.

A related point is that the structure of economies changes over time, sometimes quite abruptly. New technologies appear, business models evolve. The economy we have today is not just a bigger version of the economy we had in 1960 — it is different. One of us (Hendry) has shown in academic work that in such a shifting environment, no fixed rule could ever be a reliable guide to policy.

Second, the Taylor rule and others like it rely on imperfect inputs. For example, the potential output of the economy is an unknowable and evolving quantity that can only be roughly estimated. Even numbers like gross domestic product and inflation are available only after a delay and subject to later revision. Formulas also ignore useful qualitative information, such as discussions with people in business. There is much nuance and judgment in the Fed’s interpretation of the available data, all of which would be lost in a formulaic approach.

Third, the Taylor rule ignores many of the most important risks that the Fed must consider. The Fed’s big mistake in the 2000s was not paying enough attention to excesses building up in the subprime mortgage market. The next threat could come from cyberterrorism, problems in China or something completely unexpected. One of the biggest challenges the Fed currently faces is balancing its monetary policy with the goal of financial stability. The Taylor rule is silent on this.

The Fed isn’t perfect. No human institution can be. There are legitimate debates to be had about the Fed’s actions. Indeed, Fed officials have such debates every time they meet, and the 12 members of its policy-making Open Market Committee represent a spectrum of views, from conservative to liberal, from hawkish to dovish. No mathematical formula can substitute for the expertise and leadership that such a group can provide, particularly in a crisis.

Eric Beinhocker is executive director at the Institute for New Economic Thinking, University of Oxford. David Hendry is professor of economics at the University of Oxford.