MSTest: An R-Package for Testing Markov Switching Models Staff working paper 2026-7 Gabriel Rodriguez Rondon, Jean-Marie Dufour We present the R package MSTest, which implements hypothesis testing procedures to determine the number of regimes in Markov switching models. The package provides several testing frameworks, including Monte Carlo likelihood ratio tests, moment-based tests, parameter stability tests, and classical likelihood ratio procedures. Content Type(s): Staff research, Staff working papers JEL Code(s): C, C1, C12, C15, C18, C6, C63, C8, C87 Research Theme(s): Models and tools, Econometric, statistical and computational methods, Economic models, Monetary policy, Real economy and forecasting
I Am So Tired! I Don’t Know What to Do! Survey Fatigue and Financial Literacy: Results from a Randomized Experiment Staff working paper 2026-5 Anna Chernesky, Kim Huynh, Marcel Voia We use a randomization of question placement in surveys to estimate the causal effect on financial literacy results. We find that financial literacy questions placed at the end of a survey lead to a drop in financial literacy of 5%–15%. This research suggests a measure of financial literacy adapted for survey length. Content Type(s): Staff research, Staff working papers JEL Code(s): C, C8, C81, C83, D, D1, D12, G, G5, G53 Research Theme(s): Models and tools, Econometric, statistical and computational methods, Money and payments, Cash and bank notes, Digital assets and fintech, Payment and financial market infrastructures, Retail payments
Inflation Expectations in Action: Exploring Agents’ Behaviour in a Period of High Inflation Staff discussion paper 2025-18 Naveen Rai, Hayley Touchburn, Matt West Inflation expectations are important to monetary policy decision-makers. Using survey evidence, we examine how firms and consumers react to their inflation expectations during the post-pandemic period of high inflation. Content Type(s): Staff research, Staff discussion papers JEL Code(s): C, C8, C83, D, D8, D84, E, E3, E31 Research Theme(s): Monetary policy, Inflation dynamics and pressures
Do Firms’ Sales Expectations Hit the Mark? Evidence from the Business Leaders’ Pulse Staff discussion paper 2025-15 Owen Gaboury, Farrukh Suvankulov, Mathieu Utting We analyze Canadian data from the Bank of Canada’s Business Leaders’ Pulse, examining firms’ sales growth expectations. We find that expected growth predicts outcomes, uncertainty influences forecast errors and revisions, and firms with weak past performance anticipate and experience weaker future growth. These results highlight the survey’s value for understanding business expectations. Content Type(s): Staff research, Staff discussion papers JEL Code(s): C, C8, C83, D, D2, D22 Research Theme(s): Monetary policy, Monetary policy framework and transmission, Real economy and forecasting
Correcting Selection Bias in a Non-Probability Two-Phase Payment Survey Staff working paper 2025-17 Heng Chen, John Tsang We develop statistical inferences for a non-probability two-phase survey sample when relevant auxiliary information is available from a probability survey sample. The proposed method is assessed by simulation studies and used to analyze a non-probability two phase payment survey. Content Type(s): Staff research, Staff working papers JEL Code(s): C, C8, C83 Research Theme(s): Models and tools, Econometric, statistical and computational methods, Money and payments, Retail payments
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
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
Bouncing Back: How Mothballing Curbs Prices Staff working paper 2024-51 Thibaut Duprey, Artur Kotlicki, Daniel E. Rigobon, Philip Schnattinger We investigate the macroeconomic impacts of mothballed businesses—those that closed temporarily—on sectoral equilibrium prices after a negative demand shock. Our results suggest that pandemic fiscal support for temporary closures may have eased inflationary pressures. Content Type(s): Staff research, Staff working papers JEL Code(s): C, C5, C55, C8, C81, D, D2, D22, E, E3, E32 Research Theme(s): Models and tools, Economic models, Monetary policy, Inflation dynamics and pressures, Real economy and forecasting
Familiarity with Crypto and Financial Concepts: Cryptoasset Owners, Non-Owners, and Gender Differences Staff working paper 2024-48 Daniela Balutel, Walter Engert, Christopher Henry, Kim Huynh, Doina Rusu, Marcel Voia Measuring cryptoasset knowledge alongside financial knowledge enhances our understanding of individuals' decisions to purchase cryptoassets. This paper uses microdata from the Bank of Canada’s Bitcoin Omnibus Survey to examine gender differences and the interrelationship between crypto and financial knowledge through an empirical joint analysis. Content Type(s): Staff research, Staff working papers JEL Code(s): C, C8, C81, D, D1, D14, D9, D91, G, G5, G53, O, O5, O51 Research Theme(s): Models and tools, Econometric, statistical and computational methods, Money and payments, Digital assets and fintech
Seasonal Adjustment of Weekly Data Staff discussion paper 2024-17 Jeffrey Mollins, Rachit Lumb The industry standard for seasonally adjusting data, X-13ARIMA-SEATS, is not suitable for high-frequency data. We summarize and assess several of the most popular seasonal adjustment methods for weekly data given the increased availability and promise of non-traditional data at higher frequencies. Content Type(s): Staff research, Staff discussion papers JEL Code(s): C, C1, C4, C5, C52, C8, E, E0, E01, E2, E21 Research Theme(s): Models and tools, Econometric, statistical and computational methods, Monetary policy, Real economy and forecasting