Low Response Rate from Merchants? Sample and Ask Consumers! An Application of Indirect Sampling Under a Consumer-Merchant Bipartite Network Technical report No. 126 Heng Chen, Joy Wu Under the consumer-merchant bipartite network, we apply the indirect sampling approach to estimate merchant payment acceptance through a consumer payment diary. Content Type(s): Staff research, Technical reports JEL Code(s): C, C8, C80, C83, E, E5 Research Theme(s): Models and tools, Econometric, statistical and computational methods, Money and payments, Retail payments
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
Canadian Bitcoin Ownership in 2023: Key Takeaways Staff discussion paper 2025-4 Daniela Balutel, Marie-Hélène Felt, Doina Rusu The Bitcoin Omnibus Survey is an important tool for monitoring Canadians’ awareness and ownership of bitcoin and other cryptoassets over time. In this paper, we present data highlights from the 2023 survey. Content Type(s): Staff research, Staff discussion papers JEL Code(s): C, C8, C81, E, E4, O, O5, O51 Research Theme(s): Models and tools, Econometric, statistical and computational methods, Money and payments, Digital assets and fintech
Estimating the inflation risk premium Staff analytical note 2025-9 Bruno Feunou, Gitanjali Kumar Is there a risk of de-anchoring of inflation expectations in the near term? We estimate the inflation risk premium using traditional asset pricing models to answer this question. The risk of de-anchoring is elevated compared with the period before the COVID-19 pandemic and is higher in the United States than in Canada. Content Type(s): Staff research, Staff analytical notes JEL Code(s): C, C2, C22, C5, C58, G, G1, G12 Research Theme(s): Financial markets and funds management, Market functioning, Models and tools, Econometric, statistical and computational methods, Economic models, Monetary policy, Inflation dynamics and pressures
Crisis facilities as a source of public information Staff analytical note 2025-7 Lerby Ergun During the COVID-19 financial market crisis, central banks introduced programs to support liquidity in important core funding markets. As well as acting as a backstop to market prices, these programs produce useful trading data on prevailing market conditions. When summary information from this data is shared publicly, it can help market participants understand current conditions and aid the recovery of market functioning. Content Type(s): Staff research, Staff analytical notes JEL Code(s): C, C5, C58, D, D5, D53, D8, D83, G, G1, G12, G14 Research Theme(s): Financial markets and funds management, Market functioning, Financial system, Financial institutions and intermediation
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
Exploring the drivers of the real term premium in Canada Staff analytical note 2025-3 Zabi Tarshi, Gitanjali Kumar Changes in the term premium can reflect uncertainty about inflation, growth and monetary policy. Understanding the key factors that influence the term premium is important when central banks make decisions about monetary policy. In this paper, we derive the real term premium from the nominal term premium in Canada. Content Type(s): Staff research, Staff analytical notes JEL Code(s): C, C5, C58, E, E4, E43, E47, G, G1, G12 Research Theme(s): Financial markets and funds management, Market functioning, Monetary policy, Monetary policy framework and transmission
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
Tech Reluctance: Fostering Empathy for Canadians Facing Challenges with Digital Systems Staff discussion paper 2025-2 Sebastian Hernandez, Helena Wang, Badr Omrane, Vera Roberts, David Pereyra We find that individuals who require help performing banking tasks or who are reluctant to adopt technology avoid digital payment systems they expect to lack usability. Addressing these issues through standard accessibility practices, live assistance and thoughtful interface design can enhance user interaction and trust. Content Type(s): Staff research, Staff discussion papers JEL Code(s): A, A1, A14, C, C9, C90, D, D8, D83, O, O3, O33, Y, Y8, Y80 Research Theme(s): Money and payments, Cash and bank notes, Digital assets and fintech, Retail payments, Structural challenges, Digitalization and productivity
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