Price Discounts and Cheapflation During the Post-Pandemic Inflation Surge Staff working paper 2024-31 Alberto Cavallo, Oleksiy Kryvtsov We study how price variation within a store changes with inflation, and whether households exploit these changes to reduce the burden of inflation. We find that price changes from discounts mitigated the inflation burden while cheapflation exacerbated it. Content Type(s): Staff research, Staff working papers JEL Code(s): E, E2, E21, E3, E30, E31, L, L8, L81 Research Theme(s): Financial markets and funds management, Market functioning, Monetary policy, Inflation dynamics and pressures
Is a Cashless Society Problematic? Staff discussion paper 2018-12 Walter Engert, Ben Fung, Scott Hendry The use of bank notes in Canada for payments has declined consistently for some time, and similar trends are evident in other countries. This has led some observers to predict a cashless society in the future. Content Type(s): Staff research, Staff discussion papers JEL Code(s): E, E4, E41, E42, E5 Research Theme(s): Financial system, Financial stability and systemic risk, Money and payments, Cash and bank notes, Digital assets and fintech, Retail payments
Partial Identification of Heteroskedastic Structural Vector Autoregressions: Theory and Bayesian Inference Staff working paper 2025-14 Helmut Lütkepohl, Fei Shang, Luis Uzeda, Tomasz Woźniak We consider structural vector autoregressions that are identified through stochastic volatility. Our analysis focuses on whether a particular structural shock can be identified through heteroskedasticity without imposing any sign or exclusion restrictions. Content Type(s): Staff research, Staff working papers JEL Code(s): C, C1, C11, C12, C3, C32, E, E6, E62 Research Theme(s): Models and tools, Econometric, statistical and computational methods, Economic models, Monetary policy, Real economy and forecasting
An Alternative Estimate of Canadian Potential Output: The Multivariate State-Space Framework Staff discussion paper 2018-14 Lise Pichette, Maria Bernier, Marie-Noëlle Robitaille In this paper, we extend the state-space methodology proposed by Blagrave et al. (2015) and decompose Canadian potential output into trend labour productivity and trend labour input. As in Blagrave et al. (2015), we include output growth and inflation expectations from consensus forecasts to help refine our estimates. Content Type(s): Staff research, Staff discussion papers JEL Code(s): C, C5, E, E0, E5 Research Theme(s): Models and tools, Economic models, Monetary policy, Real economy and forecasting
Survival Analysis of Bank Note Circulation: Fitness, Network Structure and Machine Learning Staff working paper 2020-33 Diego Rojas, Juan Estrada, Kim Huynh, David T. Jacho-Chávez Using the Bank of Canada's Currency Information Management Strategy, we analyze the network structure traced by a bank note’s travel in circulation and find that the denomination of the bank note is important in our potential understanding of the demand and use of cash. Content Type(s): Staff research, Staff working papers JEL Code(s): C, C5, C52, C6, C65, C8, C81, E, E4, E42, E5, E51 Research Theme(s): Models and tools, Econometric, statistical and computational methods, Money and payments, Cash and bank notes
Monetary Policy Transmission with Endogenous Central Bank Responses in TANK Staff working paper 2025-21 Lilia Maliar, Chris Naubert We study how the transmission of monetary policy innovations is affected by the endogenous response of the central bank to macroeconomic aggregates in a two-agent New Keynesian model. We focus on how the stance of monetary policy and the fraction of savers in the economy affect transmission. Content Type(s): Staff research, Staff working papers JEL Code(s): C, C6, C61, C62, C63, E, E3, E31, E5, E52 Research Theme(s): Models and tools, Economic models, Monetary policy, Monetary policy framework and transmission
Dynamic Consumer Cash Inventory Model Staff working paper 2025-22 Kim Huynh, Oleksandr Shcherbakov, André Stenzel We study consumer cash inventory behavior by developing a dynamic model of forward-looking consumers and estimating structural parameters of the model using detailed consumer survey data. Consumers facing holding and withdrawal costs solve a discrete-time continuous-control dynamic programming problem to optimally use cash at the point of sale. Content Type(s): Staff research, Staff working papers JEL Code(s): D, D1, D12, D14, E, E4, E41, E42, G, G2, G21 Research Theme(s): Models and tools, Econometric, statistical and computational methods, Money and payments, Cash and bank notes
On the Evolution of the United Kingdom Price Distributions Staff working paper 2018-25 Ba M. Chu, Kim Huynh, David T. Jacho-Chávez, Oleksiy Kryvtsov We propose a functional principal components method that accounts for stratified random sample weighting and time dependence in the observations to understand the evolution of distributions of monthly micro-level consumer prices for the United Kingdom (UK). Content Type(s): Staff research, Staff working papers JEL Code(s): C, C1, C14, C8, C83, E, E3, E31, E37 Research Theme(s): Models and tools, Econometric, statistical and computational methods, Monetary policy, Inflation dynamics and pressures
Limits to Arbitrage and Deviations from Covered Interest Rate Parity Staff discussion paper 2016-4 James Pinnington, Maral Shamloo We document an increase in deviations from short-term covered interest rate parity (CIP) in the first half of 2015. Since the Swiss National Bank’s (SNB) decision to abandon its minimum exchange rate policy, both the magnitude and volatility of deviations from CIP have increased across several currency pairs. The effect is particularly pronounced for pairs involving the Swiss franc. Content Type(s): Staff research, Staff discussion papers JEL Code(s): F, F3, F31, G, G1, G15 Research Theme(s): Financial markets and funds management, International markets and currencies, Market functioning
Identifying Nascent High-Growth Firms Using Machine Learning Staff working paper 2023-53 Stéphanie Houle, Ryan Macdonald Firms that grow rapidly have the potential to usher in new innovations, products or processes (Kogan et al. 2017), become superstar firms (Haltiwanger et al. 2013) and impact the aggregate labour share (Autor et al. 2020; De Loecker et al. 2020). We explore the use of supervised machine learning techniques to identify a population of nascent high-growth firms using Canadian administrative firm-level data. Content Type(s): Staff research, Staff working papers JEL Code(s): C, C5, C55, C8, C81, L, L2, L25 Research Theme(s): Models and tools, Econometric, statistical and computational methods, Structural challenges, Digitalization and productivity