ABSTRACT
Understanding the linkages between monetary policy surprises and long-term interest rates is of immense interest to policymakers and researchers worldwide. In this paper, we investigate this relationship for a large sample of 29 economies and attempt to unravel the possible reasons for rotated linkages between these two variables in a long time-period, i.e., 1979–2019. We provide empirical evidence on exogenous shifts in the preferences of central banks in terms of weightage of inflation to output, altering the behaviour of long-term interest rates. We examine this phenomenon using financial crisis, and positive inflation deviations which may cause such exogenous shifts, and find both to be responsible for rotated linkages. On comparison, we find that the linkages get rotated the most during systemic crisis, followed by banking crisis, and currency crisis in that order. In terms of policy prescriptions, we confirm that central banks can ensure effective monetary transmission to long-term interest rates by having a robust monetary policy framework which encompasses the three pillars of independence and accountability, policy and operational strategy, and communications.
Disclosure statement
No potential conflict of interest was reported by the author(s).
Notes
1 This term was coined by Alan Greenspan in 2005 in a Congressional testimony and was based on the observation that while Fed’s tightening of policy from 1% to 5.25%, starting in June 2004, led to an expected response of the short-term interest rates, the long-term interest rates moved in the opposite direction from 6.5% in July 2004 to 5.2% in February 2005.
2 We use mean inflation instead of target inflation because majority of our sample economies are not inflation targeting. Hence, to maintain consistency, we have taken mean inflation as a proxy for inflation target for all the sample economies.
3 Australia, Austria, Belgium, Brazil, Canada, Chile, China, Finland, France, Germany, India, Italy, Japan, Korea, Malaysia, Mexico, Netherlands, New Zealand, Norway, Peru, South Africa, Singapore, Spain, Sweden, Switzerland, Thailand, Turkey, UK, USA.
4 Other variables may also hold importance in the investigation we attempt to carry forward. However, this would have meant focusing on a quite shorter time-period, because of the unavailability of data for the EMEs for longer periods.
5 The data provides coverage till 2016 only.
6 We also use deviations from median and get qualitatively similar results.
7 = 1 divided by total number of quarters in the study period for an economy.
8 to capture the dynamics of one year in line with the extant literature.
9 The lag lengths for these dynamic time-series models have been identified using Schwarz Information Criteria (SBC).