In remarks at a conference in Mexico City on August 25, New York Fed President John C. Williams addressed three questions pertaining to the importance, measurement, and use of time-varying unobservable variables at central banks, with a particular focus on the neutral rate of interest, or r-star.
He said:
“[Unobservable variables] play a central role in macroeconomic theory and have important implications for the conduct of monetary policy.”
“Model-based estimates of r-star in many countries exhibited a sizable downtrend over the quarter-century leading up to the COVID-19 pandemic. . . . A variety of factors contributed to this decline in r-star, including fundamental shifts in demographics and productivity growth.”
“The global demographic and productivity growth trends that pushed r-star down have not reversed. . . . [T]he GDP-weighted estimates of r-star for these four economies—Canada, the Euro Area, the United Kingdom, and the United States—are around half of a percent, similar to the comparable real-time estimates from the period prior to the onset of the pandemic. . . . [T]he era of low r-star appears far from over.”
The first question President Williams discussed was why central banks care so much about time-varying variables that cannot be observed or directly measured.
“The star variables provide key benchmarks for the economy and, in the case of r-star, the stance of monetary policy,” he said. He explained that r-star is the real short-term interest rate that is expected to prevail when the economy is at full strength and inflation is stable; y-star is potential GDP; and u-star is the level of unemployment when an economy is at its potential. “When the stars perfectly align, it means the economy has reached an equilibrium where its resources are fully utilized,” he said.
However, there are inherent challenges in measuring star variables, according to President Williams. Given that uncertainty, how do central banks measure r-star?
He noted three approaches that have emerged to infer r-star from data: 1) using a statistical method to extract a longer-run trend, 2) basing it on financial market or survey data, and 3) looking at r-star’s effects on economic data. “Each potentially provides useful information, but each also poses significant challenges,” he said.
President Williams said that univariate statistical methods generally do not provide reliable estimates of r-star, as they can be overly influenced by large macroeconomic disturbances.
Financial market and survey data are more promising sources of information; however, market- and survey-based measures “can give a false sense of precision since the reported values do not convey the uncertainty underlying them,” he said. “In addition, financial market measures of r-star are contaminated by liquidity and risk premiums, making a direct read of ‘what the markets think’ elusive.”
However, President Williams said that over the past quarter century a variety of model-based estimates of r-star have been developed—including the Holston-Laubach-Willams (HLW) model—that are able to infer the likely value of r-star by observing the movements of demand, real interest rates, and other relevant macroeconomic variables.
The final question President Williams addressed was how star variables are used by central banks.
“Estimates of r-star are foundational to considering the potential effects of the effective lower bound and strategies to mitigate its effects,” he said. “In addition to their role in internal analysis, the stars have increasingly become an aspect of central bank transparency and communication.”
However, policymakers “are well advised to avoid placing too great confidence in precise estimates of the stars in making real-world assessments and decisions,” he said.
“In the end, policy decisions must be based on the totality of information and assessments, including those related to risks,” he said.
President Williams concluded by saying that since the star variables are either explicitly or implicitly at the core of any macroeconomic model or framework. “[I]t is important that we do our best to understand the factors that influence the stars and the uncertainties related to them,” he said. “In this way we can attain the best understanding of the forces affecting the evolution of the economy and monetary policy as we carry out our mandates.”
Judy DeHaven is an executive communications specialist at the New York Fed.
The views expressed in this article are those of the contributing authors and do not necessarily reflect the position of the New York Fed or the Federal Reserve System.
