Extraordinary Forward Guidance in Canada During the Pandemic Staff analytical paper 2026-1 Christopher S. Sutherland We consider two trade-offs inherent to extraordinary forward guidance (EFG): potency versus flexibility, and the credibility of forward guidance versus the credibility of inflation targeting. We argue that the form of EFG used by the Bank of Canada during the COVID‑19 pandemic balanced both trade-offs relatively well. Content Type(s): Staff research, Staff analytical paper JEL Code(s): D, D3, D8, D83, D84, E, E3, E37, E5, E52, E58 Research Theme(s): Monetary policy, Monetary policy tools and implementation
Estimating the impacts on GDP of natural disasters in Canada Staff analytical note 2025-5 Tatjana Dahlhaus, Thibaut Duprey, Craig Johnston Extreme weather events contribute to increased volatility in both economic activity and prices, interfering with the assessment of the true underlying trends of the economy. With this in mind, we conduct a timely assessment of the impact of natural disasters on Canadian gross domestic product (GDP). Content Type(s): Staff research, Staff analytical notes JEL Code(s): B, B2, B23, C, C1, C13, C2, C23, E, E1, E17, E3, E37, E6, E62, H, H6 Research Theme(s): Monetary policy, Real economy and forecasting, Structural challenges, Climate change
Quantile VARs and Macroeconomic Risk Forecasting Staff working paper 2025-4 Stéphane Surprenant This paper provides an extensive evaluation of the performance of quantile vector autoregression (QVAR) to forecast macroeconomic risk. Generally, QVAR outperforms standard benchmark models. Moreover, QVAR and QVAR augmented with factors perform equally well. Both are adequate for modeling macroeconomic risks. Content Type(s): Staff research, Staff working papers JEL Code(s): C, C5, C53, C55, E, E3, E37 Research Theme(s): Models and tools, Econometric, statistical and computational methods, Monetary policy, Real economy and forecasting
Differentiable, Filter Free Bayesian Estimation of DSGE Models Using Mixture Density Networks Staff working paper 2025-3 Chris Naubert I develop a method for Bayesian estimation of globally solved, non-linear macroeconomic models. The method uses a mixture density network to approximate the initial state distribution. The mixture density network results in more reliable posterior inference compared with the case when the initial states are set to their steady-state values. Content Type(s): Staff research, Staff working papers JEL Code(s): C, C6, C61, C63, E, E3, E37, E4, E47 Research Theme(s): Models and tools, Econometric, statistical and computational methods, Economic models
Interaction of Macroprudential and Monetary Policies: Practice Ahead of Theory Staff discussion paper 2024-18 Thibaut Duprey, Yaz Terajima, Jing Yang We draw on the Canadian experience to examine how monetary and macroprudential policies interact and possibly complement each other in achieving their respective price and financial stability objectives. Content Type(s): Staff research, Staff discussion papers JEL Code(s): E, E3, E37, E5, E52, E58, E6, E61, G, G0, G01, G2, G21, G28 Research Theme(s): Financial system, Financial stability and systemic risk, Household and business credit, Monetary policy, Monetary policy framework and transmission
Monetary Policy Transmission to Small Business Loan Performance: Evidence from Loan-Level Data Staff working paper 2024-41 Rodrigo Sekkel, Tamon Takamura, Yaz Terajima We analyze the dynamic and heterogeneous responses of small-business loan performance to a monetary-policy shock using loan-level data in Canada. We find evidence of monetary policy transmission through the cash-flow channel and the aggregate demand channel as well as some, though limited, impact of collateral to discipline loan repayment. Content Type(s): Staff research, Staff working papers JEL Code(s): C, C3, C32, E, E1, E17, E3, E37, E5, E52 Research Theme(s): Financial system, Household and business credit, Monetary policy, Monetary policy framework and transmission
Sources of pandemic-era inflation in Canada: An application of the Bernanke and Blanchard model Staff analytical note 2024-13 Fares Bounajm, Jean Garry Junior Roc, Yang Zhang We explore the drivers of the surge in inflation in Canada during the COVID-19 pandemic. This work is part of a joint effort by 11 central banks using the model developed by Bernanke and Blanchard (2023) to identify similarities and differences across economies. Content Type(s): Staff research, Staff analytical notes JEL Code(s): E, E2, E24, E3, E31, E37, E5, E52, E6 Research Theme(s): Models and tools, Economic models, Monetary policy, Inflation dynamics and pressures, Real economy and forecasting
Making It Real: Bringing Research Models into Central Bank Projections Staff discussion paper 2023-29 Marc-André Gosselin, Sharon Kozicki Macroeconomic projections and risk analyses play an important role in guiding monetary policy decisions. Models are integral to this process. This paper discusses how the Bank of Canada brings research models and lessons learned from those models into the central bank projection environment. Content Type(s): Staff research, Staff discussion papers JEL Code(s): C, C3, C32, C5, C51, E, E3, E37, E4, E47, E5, E52 Research Theme(s): Models and tools, Economic models, Monetary policy, Monetary policy framework and transmission, Real economy and forecasting
Combining Large Numbers of Density Predictions with Bayesian Predictive Synthesis Staff working paper 2023-45 Tony Chernis I show how to combine large numbers of forecasts using several approaches within the framework of a Bayesian predictive synthesis. I find techniques that choose and combine a handful of forecasts, known as global-local shrinkage priors, perform best. Content Type(s): Staff research, Staff working papers JEL Code(s): C, C1, C11, C5, C52, C53, E, E3, E37 Research Theme(s): Models and tools, Econometric, statistical and computational methods, Monetary policy, Real economy and forecasting
Turning Words into Numbers: Measuring News Media Coverage of Shortages Staff discussion paper 2023-8 Lin Chen, Stéphanie Houle We develop high-frequency, news-based indicators using natural language processing methods to analyze news media texts. Our indicators track both supply (raw, intermediate and final goods) and labour shortages over time. They also provide weekly time-varying topic narratives about various types of shortages. Content Type(s): Staff research, Staff discussion papers JEL Code(s): C, C5, C55, C8, C82, E, E3, E37 Research Theme(s): Models and tools, Econometric, statistical and computational methods, Monetary policy, Inflation dynamics and pressures, Real economy and forecasting