We Didn’t Start the Fire: Effects of a Natural Disaster on Consumers’ Financial Distress Staff working paper 2023-15 Anson T. Y. Ho, Kim Huynh, David T. Jacho-Chávez, Geneviève Vallée We use detailed consumer credit data to investigate the impact of the 2016 Fort McMurray wildfire, the costliest wildfire disaster in Canadian history, on consumers’ financial stress. We focus on the arrears of insured mortgages because of their important implications for financial institutions and insurers’ business risk and relevant management practices. Content Type(s): Staff research, Staff working papers JEL Code(s): C, C2, C21, D, D1, D12, G, G2, G21, Q, Q5, Q54 Research Theme(s): Financial system, Financial stability and systemic risk, Household and business credit, Structural challenges, Climate change
Housing and Tax-Deferred Retirement Accounts Staff working paper 2016-24 Anson T. Y. Ho, Jie Zhou Assets in tax-deferred retirement accounts (TDA) and housing are two major components of household portfolios. In this paper, we develop a life-cycle model to examine the interaction between households’ use of TDA and their housing decisions. Content Type(s): Staff research, Staff working papers JEL Code(s): C, C6, C61, D, D1, D14, D9, D91, E, E2, E21, H, H2, H24, R, R2, R21 Research Theme(s): Financial system, Household and business credit, Models and tools, Economic models, Monetary policy, Real economy and forecasting
How Do Agents Form Macroeconomic Expectations? Evidence from Inflation Uncertainty Staff working paper 2024-5 Tao Wang The uncertainty regarding inflation that is observed in density forecasts of households and professionals helps macroeconomists understand the formation mechanism of inflation expectations. Shocks to inflation take time to be perceived by all agents in the economy, and such rigidity is lower in a high-inflation environment. Content Type(s): Staff research, Staff working papers JEL Code(s): D, D8, D84, E, E3, E31, E7, E71 Research Theme(s): Models and tools, Economic models, Monetary policy, Inflation dynamics and pressures, Monetary policy framework and transmission
Non-competing Data Intermediaries Staff working paper 2020-28 Shota Ichihashi I study a model of competing data intermediaries (e.g., online platforms and data brokers) that collect personal data from consumers and sell it to downstream firms. Content Type(s): Staff research, Staff working papers JEL Code(s): D, D4, D42, D43, D8, D80, L, L1, L12 Research Theme(s): Financial markets and funds management, Market structure, Models and tools, Economic models, Money and payments, Digital assets and fintech
The Effect of Oil Price Shocks on Asset Markets: Evidence from Oil Inventory News Staff working paper 2020-8 Ron Alquist, Reinhard Ellwanger, Jianjian Jin We quantify the reaction of U.S. equity, bond futures, and exchange rate returns to oil price shocks driven by oil inventory news. Content Type(s): Staff research, Staff working papers JEL Code(s): D, D8, D83, E, E4, E44, G, G1, G14, G15, Q, Q4, Q41, Q43 Research Theme(s): Financial markets and funds management, International markets and currencies, Market functioning, Monetary policy, Inflation dynamics and pressures
The Rise of Non-Regulated Financial Intermediaries in the Housing Sector and its Macroeconomic Implications Staff working paper 2017-36 Hélène Desgagnés I examine the impact of non-regulated lenders in the mortgage market using a dynamic stochastic general equilibrium (DSGE) model. My model features two types of financial intermediaries that differ in three ways: (i) only regulated intermediaries face a capital requirement, (ii) non-regulated intermediaries finance themselves by selling securities and cannot accept deposits, and (iii) non-regulated intermediaries face a more elastic demand. Content Type(s): Staff research, Staff working papers JEL Code(s): E, E3, E32, E4, E44, E47, E6, E60, G, G2, G21, G23, G28 Research Theme(s): Financial system, Financial institutions and intermediation, Financial stability and systemic risk, Household and business credit, Models and tools, Economic models
December 8, 2006 Perspectives on Productivity and Potential Output Growth: A Summary of the Joint Banque de France/Bank of Canada Workshop, 24–25 April 2006 Bank of Canada Review - Winter 2006-2007 Gilbert Cette, Donald Coletti A nation's productivity is the prime determinant of its real incomes and standard of living, as well as being a major determinant of its potential output. In the short run, deviations of actual output from potential output are a useful indicator of inflationary pressures. This article is a short summary of the proceedings of the workshop, which focus on productivity and potential output growth among industrialized countries. The research is organized under three main themes: estimating potential growth; productivity and growth; and institutions, policies, and growth. Content Type(s): Publications, Bank of Canada Review articles
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
May 5, 2015 Liquid Markets for a Solid Economy Remarks Carolyn A. Wilkins Chambre de commerce du Montréal métropolitain Montréal, Quebec Senior Deputy Governor Wilkins discusses funding and market liquidity, and announces consultations on the Bank’s market operations and emergency lending frameworks. Content Type(s): Press, Speeches and appearances, Remarks
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