May 16, 2016 Estimating Canada’s Effective Lower Bound Bank of Canada Review - Spring 2016 Jonathan Witmer, Jing Yang Recently, the Bank of Canada has estimated the effective lower bound (ELB) on its policy interest rate to be about -50 basis points. This article outlines the analysis that underpins that estimate by quantifying the costs of storing and using cash in Canada. It also explores how some international markets have adapted to negative interest rates, issues surrounding their implementation, as well as their transmission to other interest rates in the economy. Finally, it discusses theoretical ideas on how the ELB could be reduced further. Content Type(s): Publications, Bank of Canada Review articles JEL Code(s): D, D5, D53, E, E4, E43, E5, E52, E58
Survey Evidence on Firm AI Adoption and its Implications Staff analytical paper 2026-22 Chanya Chawla, Crystal Arnburg This paper analyzes AI adoption among Canadian firms using December 2025 Business Leaders’ Pulse data. It finds that while personal use is widespread, operational adoption remains limited. Firms expect modest positive impacts on capital spending and small net negative effects on employment over the next three years. Content Type(s): Staff research, Staff analytical paper JEL Code(s): E, E0, E2, E22, E24, O, O3, O33 Research Theme(s): Structural challenges, Digitalization and productivity
November 28, 2017 Financial System Review - November 2017 This issue of the Financial System Review reflects the Bank’s judgment that the high level of household indebtedness and housing market imbalances remain the most important vulnerabilities. While these vulnerabilities are still elevated, improving economic conditions and recent changes to housing policy should support an easing of these vulnerabilities over time. A third vulnerability highlighted in the FSR concerns cyber threats and the interconnectedness of the financial system. Content Type(s): Publications, Financial Stability Report
Earnings Dynamics and Intergenerational Transmission of Skill Staff working paper 2020-46 Lance Lochner, Youngmin Park How are your past, current and future earnings related to those of your parents? We explore this by using 37 years of Canadian tax data on two generations. Content Type(s): Staff research, Staff working papers JEL Code(s): C, C3, C33, J, J2, J24, J6, J62 Research Theme(s): Models and tools, Econometric, statistical and computational methods, Structural challenges, Demographics and labour supply
Do Canadian Broker-Dealers Act as Agents or Principals in Bond Trading? Staff analytical note 2017-11 Daniel Hyun, Jesse Johal, Corey Garriott Technology, risk tolerance and regulation may influence dealers to reduce their trading as principals (using their own balance sheets for sales and purchases of securities) in favour of agency trading (matching client trades). Content Type(s): Staff research, Staff analytical notes JEL Code(s): G, G1, G14, G2, G20, L, L1 Research Theme(s): Financial markets and funds management, Market functioning, Market structure
Forecasting Recessions in Canada: An Autoregressive Probit Model Approach Staff working paper 2024-10 Antoine Poulin-Moore, Kerem Tuzcuoglu We forecast recessions in Canada using an autoregressive (AR) probit model. The results highlight the short-term predictive power of the US economic activity and suggest that financial indicators are reliable predictors of Canadian recessions. In addition, the suggested model meaningfully improves the ability to forecast Canadian recessions, relative to a variety of probit models proposed in the Canadian literature. Content Type(s): Staff research, Staff working papers JEL Code(s): C, C5, C51, C53, E, E3, E32 Research Theme(s): Models and tools, Econometric, statistical and computational methods, Monetary policy, Real economy and forecasting
The Evolution of Unobserved Skill Returns in the U.S.: A New Approach Using Panel Data Staff working paper 2017-61 Lance Lochner, Youngmin Park, Youngki Shin Economists disagree about the factors driving the substantial increase in residual wage inequality in the United States over the past few decades. To identify changes in the returns to unobserved skills, we make a novel assumption about the dynamics of skills (especially among older workers) rather than about the stability of skill distributions across cohorts, as is standard. Content Type(s): Staff research, Staff working papers JEL Code(s): C, C2, C23, J, J2, J24, J3, J31 Research Theme(s): Models and tools, Econometric, statistical and computational methods, Monetary policy, Real economy and forecasting, Structural challenges, Demographics and labour supply
What Can Stockouts Tell Us About Inflation? Evidence from Online Micro Data Staff working paper 2021-52 Alberto Cavallo, Oleksiy Kryvtsov Did supply disruptions and cost pressures play a role in rising inflation in 2020 during the COVID-19 pandemic? Using data collected from websites of large retailers in multiple sectors and countries, we show that shortages may indicate transitory inflationary pressures. Content Type(s): Staff research, Staff working papers JEL Code(s): D, D2, D22, E, E3, E31, E37 Research Theme(s): Monetary policy, Inflation dynamics and pressures, Real economy and forecasting
Classical Decomposition of Markowitz Portfolio Selection Staff working paper 2020-21 Christopher Demone, Olivia Di Matteo, Barbara Collignon In this study, we enhance Markowitz portfolio selection with graph theory for the analysis of two portfolios composed of either EU or US assets. Using a threshold-based decomposition of their respective covariance matrices, we perturb the level of risk in each portfolio and build the corresponding sets of graphs. Content Type(s): Staff research, Staff working papers JEL Code(s): C, C0, C02 Research Theme(s): Financial markets and funds management, Market functioning, Models and tools, Econometric, statistical and computational methods
Quantum Monte Carlo for Economics: Stress Testing and Macroeconomic Deep Learning Staff working paper 2022-29 Vladimir Skavysh, Sofia Priazhkina, Diego Guala, Thomas Bromley Using the quantum Monte Carlo algorithm, we study whether quantum computing can improve the run time of economic applications and challenges in doing so. We apply the algorithm to two models: a stress testing bank model and a DSGE model solved with deep learning. We also present innovations in the algorithm and benchmark it to classical Monte Carlo. Content Type(s): Staff research, Staff working papers JEL Code(s): C, C1, C15, C6, C61, C63, C68, C7, E, E1, E13, G, G1, G17, G2, G21 Research Theme(s): Financial system, Financial stability and systemic risk, Models and tools, Econometric, statistical and computational methods, Economic models