Monetary Policy in a Low Interest Rate World

Abstract

Nominal interest rates may remain substantially below the averages of the last half century, because central banks' inflation objectives lie below the average level of inflation, and estimates of the real interest rate that are likely to prevail over the long run fall notably short of the average real interest rate experienced during this period. Persistently low nominal interest rates may lead to more frequent and costly episodes at the effective lower bound (ELB) on nominal interest rates. We revisit the frequency and potential costs of such episodes in a world of low interest rates, using both a dynamic stochastic general equilibrium (DSGE) model and the Federal Reserve's largescale econometric model, the FRB/US model. Four main conclusions emerge. First, monetary policy strategies based on traditional, simple policy rules lead to poor economic performance when the equilibrium interest rate is low, with economic activity and inflation more volatile and systematically falling short of desirable levels. Moreover, the frequency and length of ELB episodes under such policy approaches are estimated to be significantly higher than in previous studies. Second, a risk adjustment to a simple rule-whereby monetary policymakers are more accommodative, on average, than prescribed by the rule-ensures that inflation averages its 2 percent objective, and requires that policymakers systematically seek inflation near 3 percent when the ELB is not binding. Third, commitment strategies, whereby monetary accommodation is not removed until either inflation or economic activity overshoots its longrun objective, are very effective in both the DSGE and FRB/US models. And

Endogenous Forecast Switching Near the Zero Lower Bound

“…In contrast, the simulations here deliver a baseline ZLB binding frequency in the switching model of 19.6%, despite allowing for a natural rate of interest as low as 0:39% and further allowing for the possibility of switches to the de ‡ation equilibrium. The much higher ZLB binding frequency obtained by Kiley and Roberts (2017) appears to be partly due to the shock distributions which are based on the more-volatile U.S. data sample going back to 1965. Here, in contrast, the shock distributions are based the more-recent sample period of consistent monetary policy going back to 1988.…”

“…Here, in contrast, the shock distributions are based the more-recent sample period of consistent monetary policy going back to 1988. Moreover, Kiley and Roberts (2017) do not allow for the possibility that the natural rate of interest may drift above 1% in their simulations.…”

“…In addition to the features noted above, Kiley and Roberts (2017) employ a Taylor rule with no interest rate smoothing. This feature of their model would also appear to contribute to a higher ZLB binding frequency.…”

“…This feature of their model would also appear to contribute to a higher ZLB binding frequency. Table 8 Following Kiley and Roberts (2017), I use a simple loss function approach to quantify the various trade-o¤s that are involved in raising the in ‡ation target. The trade-o¤s here include:…”

“…(2010), Chung et al (2012), Coibion, Gorodnichenko, and Wieland (2012), Dennis (2016), and Kiley and Roberts (2017). 5 See, for example, Eggertsson and Woodford (2003), Adam and Billi (2007), Nakov (2008), Nakata (2013), Hamilton, et al (2016), Basu and Bundick (2015), Evans, et al (2015), and Gust, Johannsen, López-Salido (2017).…”