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2126 Results

Non-Performing Loans, Fiscal Costs and Credit Expansion in China

Staff working paper 2018-53 Huixin Bi, Yongquan Cao, Wei Dong
This paper studies how the credit expansion policy pursued by the Chinese government in an effort to stimulate its economy in the post-crisis period affects bank–firm loan contracts and the macroeconomy. We build a structural model with financial frictions in which the optimal loan contract reflects the trade-off between leverage and the probability of default.

Machine learning for economics research: when, what and how

Staff analytical note 2023-16 Ajit Desai
This article reviews selected papers that use machine learning for economics research and policy analysis. Our review highlights when machine learning is used in economics, the commonly preferred models and how those models are used.

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.

On the Fragility of DeFi Lending

Staff working paper 2023-14 Jonathan Chiu, Emre Ozdenoren, Kathy Yuan, Shengxing Zhang
We develop a dynamic model to capture key features of decentralized finance lending. We identify a price-liquidity feedback: the market outcome in any given period depends on agents' expectations about lending activities in future periods, with higher future price expectations leading to more lending and higher prices in that period.

The Bank of Canada’s “Horse Race” of Alternative Monetary Policy Frameworks: Some Interim Results from Model Simulations

Staff discussion paper 2021-13 José Dorich, Rhys R. Mendes, Yang Zhang
Bank of Canada staff are running a “horse race” of alternative monetary policy frameworks in the lead-up to 2021 renewal of the Bank’s monetary policy framework. This paper summarizes some interim results of model simulations from their research.
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

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.

Canadians’ access to cash in 2023

Staff analytical note 2025-13 Heng Chen, Hongyu Xiao, Daneal O’Habib, Stephen Wild
This study updates our measure of Canadians' access to cash through automated banking machines and financial institution branches. We find that in 2023 overall access to cash remains stable, while rural Canadians continue having less access.
Content Type(s): Staff research, Staff analytical notes JEL Code(s): J, J1, J15, O, O1, R, R5, R51 Research Theme(s): Money and payments, Cash and bank notes
August 16, 2012

Bank of Canada Review - Summer 2012

This issue features three articles that present research and analysis by Bank of Canada staff. The first updates previous Bank estimates of measurement bias in the Canadian consumer price index; the second uses a new term-structure model to analyze the relationship between the short-term policy rate and long-term interest rates; and the third examines indicators of balance-sheet risks at financial institutions in Canada.

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.
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