Many central banks are considering issuing a central bank digital currency (CBDC). This would introduce a new policy tool—interest on CBDC. We investigate how this new tool would interact with traditional monetary policy tools, such as the interest on central bank reserves.
One year later, we review the events that took place in Canadian fixed-income markets at the beginning of the COVID-19 crisis and propose potential policy research questions for future work.
We demonstrate the ability of reinforcement learning techniques to estimate the best-response functions of banks participating in high-value payments systems—a real-world strategic game of incomplete information.
Digital currencies store balances in anonymous electronic addresses. This paper analyzes the trade-offs between the safety and convenience of aggregating balances in addresses, electronic wallets and banks.
How should policy be designed at high debt levels, when fiscal authorities have little room to adjust taxes? Assigning the monetary authority a role in achieving debt sustainability makes it less effective in stabilizing inflation and output.
We study how different monetary policies affect the yield curve and interact. Our study highlights the importance of the spillover structure across the yield curve for policy-making.
Central banks conduct research involving in-depth interviews with external parties—but little is known about how this information affects monetary policy. We address this gap by analyzing open-ended interviews with senior central bank economic and policy staff who work closely with policy decision-makers.
We use retail payment data in conjunction with machine learning techniques to predict the effects of COVID-19 on the Canadian economy in near-real time. Our model yields a significant increase in macroeconomic prediction accuracy over a linear benchmark model.