Economic Uncertainty and the Evolution of Monetary Policymaking


All eyes were squarely focused on the Federal Reserve this week, as markets whiplashed between several unknowns. Would recent inflation and payroll data nudge the Fed towards a more hawkish stance? Would the Fed signal that it believes it’s losing its fight to bring inflation towards its target rate of 2%? Are rate cuts still on the table this year?

Jerome Powell, Chairman of the Federal Reserve, tempered these mounting concerns during his address on Wednesday, offering markets some relief as the Fed's tone proved less hawkish than anticipated. However, as the case for Federal Reserve rate cuts has taken on serious water over the past several months, there is increasing uncertainty about what the Fed will do next.

This week, we delve into a condensed transcript from a presentation delivered by Federal Reserve Vice Chair Philip N. Jefferson at the International Research Forum on Monetary Policy on April 16th, 2024. Though the transcript is now two-weeks-old, it serves as a vital window into the mindset prevailing within the hallowed halls of the Federal Reserve, drawing upon a rich tapestry of historical insights and contemporary economic paradigms to illuminate the central bank's current outlook on monetary policy. We believe this is critical to understand as markets are at least semi-permanently focused on the FED, and any structural changes to their thinking is of importance for investors.

The original transcript can be found on the Federal Reserve’s website.

Economic Uncertainty and the Evolution of Monetary Policymaking

I became a member of the Federal Reserve Board just as it was grappling with the economic after-effects of the pandemic, a once-in-a-century disturbance of worldwide significance. As a result, I know from firsthand experience that understanding the main sources of uncertainty and how best to make monetary policy decisions in the presence of uncertainty is crucial to policymaking.

I will take this opportunity to do a couple of things. First, I will review a few historical examples of how economic thinking on monetary policymaking in the presence of uncertainty has evolved. Second, I will consider lessons learned from these examples that could influence how monetary policymakers think about the policy choices the Federal Open Market Committee (FOMC) faces currently.

The 1960s to the 1980s

In the 1960s, during the heyday of Keynesian macroeconomics, researchers widely believed that monetary policymakers faced a long-run tradeoff between inflation and unemployment and that the tradeoff could be calibrated to keep unemployment indefinitely low at an acceptable cost in terms of higher inflation. Improvements in econometric modeling abounded, and the harnessing of optimal-control methods developed in the field of engineering held out the prospect that business cycle fluctuations could be stabilized.

There were contrarians, of course, most notably Milton Friedman, who highlighted the necessity of monetary policymakers to consider what they don't know in their decision-making process (Friedman, 1968). Friedman's statement that monetary policy works with "long and variable lags" was, among other things, an argument against policymakers trying to fine-tune the level of economic activity. In recognition of policymakers' limited knowledge of short-run economic relationships, Friedman advocated the use of simple rules for monetary policy, such as the k-percent money growth rule. He argued that rules that focused on monetary growth and that eschewed direct feedback on macroeconomic variables would work reasonably well, on average, and avoid the hubris of fine-tuning policy in a dynamic and uncertain world.

History proved Friedman right in his take on the importance of uncertainty, even if his prescription of a k-percent money growth rule fared less well.

During roughly the same period when Friedman authored his famous presidential address to the American Economic Association disputing the purported long-run tradeoff between inflation and unemployment, William Brainard published an influential paper on the implications of uncertainty. Brainard (1967) argued that uncertainty about the power of monetary policy implied that policy should respond more cautiously to shocks than would be the case if this uncertainty did not exist. Brainard's attenuation principle is a classic example of what is today known as the Bayesian approach to uncertainty. The Brainard approach to uncertainty consisted of two steps. The first step is to compute the optimal policy for a world without uncertainty: the certainty equivalence case. The second step is to adjust that policy response to account for the particular uncertainty under study. One strand of research followed these steps through the 1970s and beyond. A parallel strand of research that embraced at least part of the message of Friedman was also under way. It bypassed the optimal policy benchmark altogether on the grounds that uncertainty is pervasive and sought instead to find simple rules that performed well across a large class of models and for a large range of conditions.

Brainard's insight was important. There are many circumstances in which the principle of gradualism applies, but as I will discuss later, economic research has also found that there are circumstances in which the presence of uncertainty does not warrant a gradual policy response.

The 1990s and 2000s

Jumping ahead to the 1990s, a "new economy" was emerging. The unemployment rate was below what many analysts at the time judged to be its natural rate, and many FOMC participants and others were forecasting growth above the economy's potential. Chairman Alan Greenspan, however, suspected that technological advances and other forces were fostering a "new economy" of sustained high productivity growth that would allow a period of persistently low unemployment without generating inflationary pressure. In the absence of hard evidence to the contrary, he was able to persuade the FOMC to go along with him by implicitly employing the Bayesian logic of Brainard's attenuation principle with a disarmingly simple suggestion: Let's just wait one more meeting and see. Chairman Greenspan repeated this message as inflation fell from above 2 percent in 1996 to below 2 percent in 1997 and 1998 while the economy added 9.3 million jobs, and the FOMC raised the federal funds rate just once.

Around the same time, there was an explosion of interest in simple policy rules for monetary policy, beginning, in most people's reckoning, with the rule John Taylor (1993) published in the early 1990s. These simple feedback rules, which specify how central banks' policy instruments would respond to the state of the economy, differed from their predecessors by replacing monetary aggregates as the instrument of monetary policy with a short-term policy interest rate. This research embraced the message that restricting feedback to a small number of key macroeconomic variables would result in more robust outcomes than adhering to the prescriptions of, say, optimal-control policies, which in essence-imposed feedback on all aspects of these models. Whether much of the robustness gains of simple rules can be realized when central banks only use such rules as "guides" for monetary policy is a topic worthy of further research.

The claimed robustness of simple rules across a set of fixed models is arguably only part of their appeal. Another part is the notion that their parsimony presumably makes simple rules relatively easy for households, businesses, and financial market participants to learn. One useful finding was that gradualism in policy setting, in the form of a sizable weight on the lagged policy rate in the policy rule, is helpful for facilitating learnability. In any event, the literature on learning in macroeconomics extended the dimension of uncertainty for monetary policymakers from the cross-section of candidate models to the time dimension of any given model.

The bulk of the early literature assumed private-sector decision-makers were knowledgeable, rational agents, while policymakers lacked detailed knowledge of the structure of the economy. The assumed imbalance of information and knowledge was striking. It was usually assumed, sometimes only implicitly, that private agents understood not only the economic environment in which they operated but also the policy regime that was in place. Considering this background, some more recent contributions explored two related departures from the assumption of a fixed model with uncertain parameters: time variation in the true (population) model and private agents learning about the economy.

As I just observed, the rational expectations paradigm presupposes that economic agents have a great deal of knowledge about their environment, but policymakers need to know the true (population) parameters of the models they use. Instead, they must use estimates of those parameters. As Sargent (1993) noted, it makes sense to assume that the decision-makers within the models that policymakers employ are no more sophisticated than the econometricians who estimate them. Doing so means accepting that the true (population) parameters of one's model could be time-varying—the outcome of the interplay between shocks, uncertainty, learning, and policy. That realization changes the way you think about monetary policy.

How might this matter? Let me give you one example. As many of you know, econometricians have found sizable declines in recent decades in the response of inflation to the unemployment rate. Taken at face value, these declines in the slope of the Phillips curve have important implications for the optimal conduct of monetary policy. But what should policymakers take from such econometric results? Some researchers argue that the apparent decline in the response to slack in the Phillips curve could be a manifestation of the central bank's improved control of inflation. That is, policymakers could be "victims of their own success" in the sense that good performance in controlling inflation over the Great Moderation period may have weakened the information content of the data.

Now, take this notion a step further, as a strand of the literature does, and suppose that private agents within our models are themselves skeptical—that is, they have doubts about their methods for formulating expectations and making decisions and that they act accordingly. Economists now have new means of modeling uncertainty both within a given model and across a set of rival models. These methods draw on theories of ambiguity aversion. Under ambiguity aversion, agents are particularly concerned about types of uncertainties that do not lend themselves to being represented in terms of probabilities. Agents' choices are motivated, in part, by an incentive to minimize the adverse consequences of these types of uncertainties. The ambiguity aversion approach to uncertainty suggests that to protect against uncertainty over which a policymaker is unwilling or unable to attach prior probabilities; the appropriate response is often anti-attenuation; that is, policy should apply for stronger monetary medicine than in the certainty equivalence case.

For the reasons I have outlined, there are circumstances when uncertainty might appropriately induce a gradual response and other circumstances when a nongradual response to uncertainty may be justified. Furthermore, under either the Bayesian approach or the ambiguity aversion approach, the best response to uncertainty is context-specific and can vary over time. Sometimes, the context leads to the same conclusion, broadly speaking, regardless of the approach. One case of perennial interest to central bankers is inflation persistence, where the Bayesian approach, the ambiguity aversion approach, and its close cousin, robust control, all tend to lead to policy that is stronger than the certainty equivalent case to forestall the possibility of inflationary forces becoming embedded in inflation expectations. Another case is that of crisis periods.

The Global Financial Crisis

Take, for example, the Global Financial Crisis of 2008. During this period, the tension between caution, on the one hand, and vigorous action, on the other, as a way to conduct monetary policy in the face of uncertainty was evident. In September 2007, the FOMC decided to lower its target for the federal funds rate by 50 basis points to "forestall some of the adverse effects on the broader economy that might otherwise arise from the disruptions in financial markets" and noted that "developments in financial markets since the Committee's last regular meeting have increased the uncertainty surrounding the economic outlook." In subsequent meetings, the FOMC gradually lowered its target for the federal funds rate by 25 basis points and, in January 2008, decided to quicken its pace by lowering the target by 75 basis points in an unscheduled meeting and by 50 basis points, 75 basis points, and 25 basis points in subsequent meetings. Inflation, however, was rising over that period. By June 2008, it was well over 2 percent and still increasing, and the FOMC paused its rate cutting. It was a decision that weighed the upside risks to inflation and inflation expectations with the downside risks to economic growth. In September 2008, the circumstances changed precipitously, as did the FOMC's approach to policy. The Committee quickly cut the federal funds rate effectively to zero and took extraordinary steps to stabilize the financial system and support the economy. The motivation to respond assertively to the emerging crisis and the uncertainty surrounding it was no doubt accentuated by the knowledge that future policy actions might be circumscribed by a lengthy spell of the funds rate at its lower bound, which would magnify losses associated with adverse outcomes. My conclusion, as Chair Powell mentioned in a speech in 2018, is that during crisis periods, words like "we will do whatever it takes" will likely be more effective than "we will take cautious steps."

Lessons Learned

Some clear lessons flow from the history that I have summarized. First, when uncertainty is high, policymakers should sometimes act quickly and should sometimes act cautiously. The right action depends on the circumstances. Second, while simple monetary policy rules are appealing for several reasons, rigid adherence to the prescriptions of simple rules is unwarranted. Historically, policymakers have only used rules as "guides" or benchmarks in setting policy, and there are good reasons for this. It is clearly beneficial to look at the totality of the data to identify changes in the economy in real-time, to embrace the risk-management considerations associated with uncertainty that factor into FOMC decisions, and to adapt policy to the evolution of the economy. Third, in the presence of a high degree of uncertainty, policymakers benefit from a healthy dose of humility. There are limits to what we know about the economy, especially after periods of economic upheaval such as a pandemic.

Current Situation

Reflecting on the situation we are facing today, over the past year, inflation has come down significantly but is still running above the FOMC's 2 percent goal. In March, headline personal consumption expenditures (PCE) inflation was 2.7 percent over the past 12 months based on the Federal Reserve's staff estimates. A year earlier, it was 4.4 percent. Core PCE inflation, which excludes the volatile food and energy components, stood at 2.8 percent; a year ago, it was 4.8 percent. While we have seen considerable progress in lowering inflation, the job of sustainably restoring 2 percent inflation is not yet done.

Real GDP growth in the fourth quarter of 2023 was 3.4 percent, and I expect first-quarter economic growth to slow down but remain solid, as indicated by the solid growth in retail sales in March and February. Recent readings on both job gains and inflation have come in higher than expected. The economy added an average of 276,000 nonfarm jobs per month in the three months through March, a faster pace than we have seen since last March. And the inflation data over the past three months were above the low readings in the second half of last year.

My baseline outlook continues to be that inflation will decline further, with the policy rate held steady at its current level, and that the labor market will remain strong, with labor demand and supply continuing to rebalance. Of course, the outlook is still quite uncertain, and if incoming data suggest that inflation is more persistent than I currently expect it to be, it will be appropriate to hold in place the current restrictive stance of policy for longer. I am fully committed to getting inflation back to 2 percent.


I would like to conclude by saying that in this environment of heightened uncertainty, it is increasingly important to comprehend what is driving uncertainty and how monetary policy might play a role in limiting the negative impact of uncertainty on businesses, households, and financial markets.


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