Estimating the Demand for Settlement Balances in the Canadian Large Value Transfer System
This paper applies a static model of an interest rate corridor to the Canadian data, and estimates the aggregate demand for central-bank settlement balances in the Large Value Transfer System (LVTS). The empirical specification controls for various calendar effects that have been shown to cause fluctuations in LVTS payment flows. The analysis takes into account the downward divergence of the overnight interest rate from the target rate, which has been persistent since 2005. The results suggest that a target of $3 billion for LVTS settlement balances does not seem excessive during the time period when Canadian monetary policy was operating at the effective lower bound (ELB). Specifically, the model projects that, if the consistent downward divergence of overnight interest rate is taken into account, then on average $2.405 billion of LVTS settlement balances would probably have been sufficient to achieve the goal of keeping the overnight interest rate at or very close to the lower bound of the corridor. However, by targeting a slightly higher level, the Bank of Canada could be 95% certain that the overnight interest rate would on average not exceed its policy rate at the lower bound of the corridor. In addition, the estimation shows that the point elasticity of overnight interest rate is around 0.17 when the daily level of settlement balances is targeted at $3 billion under the ELB framework.
|Date of creation:||2012|
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- James H. Stock & Motohiro Yogo, 2002. "Testing for Weak Instruments in Linear IV Regression," NBER Technical Working Papers 0284, National Bureau of Economic Research, Inc.
- David Bowman & Etienne Gagnon & Mike Leahy, 2010. "Interest on excess reserves as a monetary policy instrument: the experience of foreign central banks," International Finance Discussion Papers 996, Board of Governors of the Federal Reserve System (U.S.).
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- Stock, James H & Wright, Jonathan H & Yogo, Motohiro, 2002. "A Survey of Weak Instruments and Weak Identification in Generalized Method of Moments," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(4), pages 518-29, October.
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