The Bank of Canada COVID‑19 stringency index: measuring policy response across provinces Staff analytical note 2021-1 Calista Cheung, Jerome Lyons, Bethany Madsen, Sarah Miller, Saarah Sheikh We construct an index that systematically measures and tracks the stringency of government policy responses to the COVID-19 pandemic across Canadian provinces. Researchers can use this stringency index to analyze how the pandemic is affecting the economy. Content Type(s): Staff research, Staff analytical notes JEL Code(s): E, E2, E20, H, H7, I, I1, I18, R, R1 Research Theme(s): Models and tools, Econometric, statistical and computational methods, Monetary policy, Real economy and forecasting
COVID-19 Crisis: Lessons Learned for Future Policy Research Staff discussion paper 2021-2 Jean-Sébastien Fontaine, Corey Garriott, Jesse Johal, Jessica Lee, Andreas Uthemann 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. Content Type(s): Staff research, Staff discussion papers JEL Code(s): D, D4, D47, E, E4, E41, E5, G, G0, G01, G1, G14, G2, G20, G21, G23 Research Theme(s): Financial markets and funds management, Market functioning, Financial system, Financial institutions and intermediation, Financial stability and systemic risk, Monetary policy, Monetary policy tools and implementation
Distributional Effects of Payment Card Pricing and Merchant Cost Pass-through in Canada and the United States Staff working paper 2021-8 Marie-Hélène Felt, Fumiko Hayashi, Joanna Stavins, Angelika Welte Although credit cards are more expensive for merchants to accept than cash or debit cards, merchants typically pass through their costs evenly to all customers. Along with consumer card rewards and banking fees, this creates cross-subsidies between payment methods. Because higher-income individuals tend to use credit cards more than those with lower incomes, our results indicate that these cross-subsidies might lead to regressive distributional effects. Content Type(s): Staff research, Staff working papers JEL Code(s): D, D1, D12, D2, D23, D3, D31, E, E4, E42, G, G2, G21, L, L8, L81 Research Theme(s): Financial markets and funds management, Market structure, Money and payments, Retail payments
Estimating Policy Functions in Payments Systems Using Reinforcement Learning Staff working paper 2021-7 Pablo S. Castro, Ajit Desai, Han Du, Rodney J. Garratt, Francisco Rivadeneyra 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. Content Type(s): Staff research, Staff working papers JEL Code(s): A, A1, A12, C, C7, D, D8, D83, E, E4, E42, E5, E58 Research Theme(s): Models and tools, Econometric, statistical and computational methods, Money and payments, Digital assets and fintech, Payment and financial market infrastructures
Eggs in One Basket: Security and Convenience of Digital Currencies Staff working paper 2021-6 Charles M. Kahn, Francisco Rivadeneyra, Tsz-Nga Wong 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. Content Type(s): Staff research, Staff working papers JEL Code(s): E, E4, E42, E5, E51, E58 Research Theme(s): Financial system, Financial stability and systemic risk, Money and payments, Digital assets and fintech, Payment and financial market infrastructures
(Optimal) Monetary Policy with and without Debt Staff working paper 2021-5 Boris Chafwehé, Rigas Oikonomou, Romanos Priftis, Lukas Vogel 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. Content Type(s): Staff research, Staff working papers JEL Code(s): C, C1, C11, E, E3, E31, E5, E52, E58, E6, E62 Research Theme(s): Models and tools, Economic models, Monetary policy, Monetary policy framework and transmission, Monetary policy tools and implementation, Real economy and forecasting
Networking the Yield Curve: Implications for Monetary Policy Staff working paper 2021-4 Tatjana Dahlhaus, Julia Schaumburg, Tatevik Sekhposyan 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. Content Type(s): Staff research, Staff working papers JEL Code(s): C, C1, C18, C2, C21, C5, C53, E, E4, E43, E44, E5, E52 Research Theme(s): Models and tools, Econometric, statistical and computational methods, Monetary policy, Monetary policy framework and transmission, Monetary policy tools and implementation
Chinese Monetary Policy and Text Analytics: Connecting Words and Deeds Staff working paper 2021-3 Jeannine Bailliu, Xinfen Han, Barbara Sadaba, Mark Kruger What are the main drivers behind the monetary policy reaction function of the People’s Bank of China? Content Type(s): Staff research, Staff working papers JEL Code(s): C, C6, C63, E, E5, E52, E58 Research Theme(s): Models and tools, Econometric, statistical and computational methods, Monetary policy, Monetary policy framework and transmission
Qualitative Field Research in Monetary Policy Making Staff discussion paper 2021-1 Chris D'Souza, Jane Voll 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. Content Type(s): Staff research, Staff discussion papers JEL Code(s): C, C8, C83, E, E3, E37, E5, E52 Research Theme(s): Models and tools, Econometric, statistical and computational methods, Economic models, Monetary policy, Monetary policy framework and transmission, Real economy and forecasting
Using Payments Data to Nowcast Macroeconomic Variables During the Onset of COVID-19 Staff working paper 2021-2 James Chapman, Ajit Desai 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. Content Type(s): Staff research, Staff working papers JEL Code(s): C, C5, C53, C55, E, E3, E37, E4, E42, E5, E52 Research Theme(s): Models and tools, Econometric, statistical and computational methods, Monetary policy, Real economy and forecasting, Money and payments, Retail payments