The Usage of Security Lending Facilities under Unconventional Monetary Policy: Evidence from Sweden Staff working paper 2026-9 Marianna Blix Grimaldi, Fabienne Schneider, David Vestin This paper examines the interaction between quantitative easing (QE) and the securities lending facility (SLF) using a detailed dataset on Riksbank QE purchases, Swedish DMO SLF transactions and OTC repo deals. A theoretical model further shows how excess demand for assets and search frictions shift the SLF from a backstop to a first-resort tool. Content Type(s): Staff research, Staff working papers JEL Code(s): E, E5, E52, E58, G, G2, G21 Research Theme(s): Financial markets and funds management, Market functioning, Market structure, Financial system, Financial institutions and intermediation, Monetary policy, Monetary policy tools and implementation
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
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
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
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
Did the Renewable Fuel Standard Shift Market Expectations of the Price of Ethanol? Staff working paper 2017-35 Christiane Baumeister, Reinhard Ellwanger, Lutz Kilian It is commonly believed that the response of the price of corn ethanol (and hence of the price of corn) to shifts in biofuel policies operates in part through market expectations and shifts in storage demand, yet to date it has proved difficult to measure these expectations and to empirically evaluate this view. Content Type(s): Staff research, Staff working papers JEL Code(s): Q, Q1, Q18, Q2, Q28, Q4, Q42, Q5, Q58 Research Theme(s): Financial markets and funds management, Market functioning, Models and tools, Econometric, statistical and computational methods, Monetary policy, Inflation dynamics and pressures
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
The Mutable Geography of Firms’ International Trade Staff working paper 2025-11 Lu Han Exporters frequently change their market destinations. This paper introduces a new approach to identifying the drivers of these decisions over time. Analysis of customs data from China and the UK shows most changes are driven by demand rather than supply-related shocks. Content Type(s): Staff research, Staff working papers JEL Code(s): F, F1, F12, F14, L, L1, L11 Research Theme(s): Models and tools, Economic models, Structural challenges, International trade, finance and competitiveness
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
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