Estimates of the Natural Rate of Interest Consistent with a Supply-Side Structure and a Monetary Policy Rule for the U.S. Economy

We estimate the natural rate of interest (r*) using a semi-structural model of the U.S. economy that jointly characterizes the trend and cyclical factors of key macroeconomic variables such as output, the unemployment rate, inflation, and short- and long-term interest rates. We specify a monetary policy rule and a 10-year Treasury yield equation to exploit the information provided by both interest rates to infer r*. However, the use of a monetary policy rule with a sample that spans the Great Recession and its aftermath poses a challenge because of the effective lower bound. We devise a Bayesian estimation technique that incorporates a Tobit-like specification to deal with the censoring problem. We compare and validate our model specifications using pseudo out-of-sample forecasting exercises. Our results show that the smoothed value of r* declined sharply around the Great Recession, eventually falling below zero, and remained negative through early 2020. Our results also indicate that obviating the censoring would imply higher estimates of r* than otherwise. We also extend our results to the COVID-19 pandemic period, introducing stochastic volatility in the model and dealing with the massive swings in the data, to find that r* would be close to 1% in early 2023.