Debt-Relief Programs and Money Left on the Table: Evidence from Canada's Response to COVID-19 Staff working paper 2021-13 Jason Allen, Robert Clark, Shaoteng Li, Nicolas Vincent During the COVID-19 pandemic, Canadian financial institutions offered debt-relief programs to help borrowers cope with job losses and economic insecurity. We consider the low take-up rates for these programs and suggest that to be effective, such programs must be visible and easy to use. Content Type(s): Staff research, Staff working papers JEL Code(s): G, G3, G31, H, H5 Research Theme(s): Financial system, Financial stability and systemic risk, Household and business credit, Monetary policy, Real economy and forecasting
Competing Currencies in the Laboratory Staff working paper 2017-53 Janet Hua Jiang, Cathy Zhang We investigate competition between two intrinsically worthless currencies as a result of decentralized interactions between human subjects. We design a laboratory experiment based on a simple two-country, two-currency search model to study factors that affect circulation patterns and equilibrium selection. Content Type(s): Staff research, Staff working papers JEL Code(s): C, C9, C92, D, D8, D83, E, E4, E40 Research Theme(s): Financial markets and funds management, International markets and currencies, Models and tools, Economic models, Money and payments, Digital assets and fintech
Assessing tariff pass-through to consumer prices in Canada: Lessons from 2018 Staff analytical note 2025-18 Alexander Lam US trade protectionism is making the economic outlook increasingly uncertain. To assess how consumer prices may respond to tariffs, we examine a tariff episode from 2018 using detailed microdata and the synthetic control method. Content Type(s): Staff research, Staff analytical notes JEL Code(s): E, E3, E30, E31, F, F1, F10, F13, F14 Research Theme(s): Monetary policy, Inflation dynamics and pressures, Structural challenges, International trade, finance and competitiveness
Estimating Discrete Choice Demand Models with Sparse Market-Product Shocks Staff working paper 2025-10 Zhentong Lu, Kenichi Shimizu We propose a novel approach to estimating consumer demand for differentiated products. We eliminate the need for instrumental variables by assuming demand shocks are sparse. Our empirical applications reveal strong evidence of sparsity in real-world datasets. Content Type(s): Staff research, Staff working papers JEL Code(s): C, C1, C3, D, D1, L, L0, L00 Research Theme(s): Financial markets and funds management, Market structure, Models and tools, Econometric, statistical and computational methods
Demand for Payment Services and Consumer Welfare: The Introduction of a Central Bank Digital Currency Staff working paper 2020-7 Kim Huynh, Jozsef Molnar, Oleksandr Shcherbakov, Qinghui Yu Using a two-stage model, we study the determinants of Canadian consumers’ choices of payment method at the point of sale. We estimate consumer preferences and adoption costs for various combinations of payment methods. We analyze how introducing a central bank digital currency would affect the market equilibrium. Content Type(s): Staff research, Staff working papers JEL Code(s): C, C5, C51, E, E4, E42, L, L1, L14, L5, L52 Research Theme(s): Models and tools, Econometric, statistical and computational methods, Economic models, Money and payments, Digital assets and fintech, Retail payments
Potential output in Canada: 2026 assessment Staff analytical paper 2026-19 Alex Chernoff, Christopher Hajzler, Stéphanie Houle, Gabriella Ruggero, Olena Senyuta, Karanbir Sohal, Walter Steingress, Temel Taskin Growth in potential output is expected to drop from 2.3% in 2025 to 1.2% in 2026 given slowing population growth, US tariffs and trade policy uncertainty. It is then estimated to pick up to an average of 1.5% over 2027–29 as strengthening business and government investment supports trend labour productivity (TLP). Gradual adoption of artificial intelligence is also expected to lift TLP growth over the projection horizon. Content Type(s): Staff research, Staff analytical paper JEL Code(s): E, E2, E3, E4, E5 Research Theme(s): Models and tools, Economic models, Monetary policy, Real economy and forecasting, Structural challenges, Demographics and labour supply
An Optimal Macroprudential Policy Mix for Segmented Credit Markets Staff working paper 2021-31 Jelena Zivanovic How can macroprudential policy and monetary policy stabilize segmented credit markets? Is there a trade-off between financial stability and price stability? I use a theoretical model to evaluate the performance of alternative policies and find the optimal mix of macroprudential and monetary policy in response to aggregate shocks. Content Type(s): Staff research, Staff working papers JEL Code(s): E, E3, E30, E4, E44, E5, E50 Research Theme(s): Financial system, Financial stability and systemic risk, Household and business credit, Models and tools, Economic models, Monetary policy, Monetary policy tools and implementation
Cyclicality of Schooling: New Evidence from Unobserved Components Models Staff working paper 2020-38 Barbara Sadaba, Sunčica Vujič, Sofia Maier What is the time-varying impact of economic cycles on decisions to invest in human capital? Content Type(s): Staff research, Staff working papers JEL Code(s): C, C3, C32, E, E3, I, I2, J, J2 Research Theme(s): Models and tools, Econometric, statistical and computational methods, Monetary policy, Real economy and forecasting
The potential effect of a central bank digital currency on deposit funding in Canada Staff analytical note 2020-15 Alejandro García, Bena Lands, Xuezhi Liu, Joshua Slive A retail central bank digital currency denominated in Canadian dollars could, in theory, create competition for bank deposit funding. Content Type(s): Staff research, Staff analytical notes JEL Code(s): E, E4, E41, E44, E5, G, G1, G10, G17, G2, G21, G3, G32, O Research Theme(s): Financial system, Financial institutions and intermediation, Financial stability and systemic risk, Money and payments, Digital assets and fintech
Trading on Long-term Information Staff working paper 2020-20 Corey Garriott, Ryan Riordan Investors who trade based on good research are said to be the backbone of stock markets: They conduct research to discover the value of stocks and, through their trading, guide financial prices to reflect true value. What can make their job difficult is that high-speed, short-term traders could use machine learning and other technologies to infer when informed investors are trading. Content Type(s): Staff research, Staff working papers JEL Code(s): G, G1, G14, G2, G20, L, L1 Research Theme(s): Financial markets and funds management, Market functioning, Market structure, Financial system, Financial institutions and intermediation