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We study household mortgage choice in a model with three mortgage contracts that differ in their payment structures: fixed-rate fixed-payment, variable-rate variable-payment, and a hybrid variable-rate fixed-payment mortgage where interest rate changes affect principal repayment rather than payment size. We calibrate the model to match mortgage choice patterns in Canada, where all these options are offered with short terms. We demonstrate that restricting contract choice or mandating long terms, as in the U.S. system, can lead to substantial welfare losses by limiting risk management strategies and increasing mortgage pricing ex-ante.

We summarize the review and renewal process at four central banks (Reserve Bank of New Zealand, Bank of England, Sveriges Riksbank and the US Federal Reserve Bank) and compare them with the process at the Bank of Canada, which has been well-established since 2001.

When players repeatedly face an identical or similar game (e.g., coordination game, technology adoption game, or product choice game), they may learn through experience to perform better in the future. This learning behaviour has important economic implications.

We perform an analysis to determine how well the introduction of a countercyclical loanto- value (LTV) ratio can reduce household indebtedness and housing price fluctuations compared with a monetary policy rule augmented with house price inflation.

Business cycles are substantially correlated across countries. Yet most existing models are not able to generate substantial transmission through international trade. We show that the nature of such transmission depends fundamentally on the features determining the responsiveness of labor supply and labor demand to international relative prices.

With increasing levels of household debt in recent years, the number of households that may be vulnerable to a negative economic shock is rising as well. Decisions made by both the debtor and the creditor can contribute to insolvency. This article presents some stylized facts about insolvency in Canada’s household sector and analyzes the role of creditors in insolvencies. The average debt of an individual filing for bankruptcy is more than 1.5 times that of an average Canadian household; bankruptcy filers tend to be unemployed or in low-wage jobs, and are typically renters. The article reports that banks that approve more loans per branch, which is interpreted as less-intensive use of soft information (such as the loan officer’s assessment of the applicant’s character), experience more client bankruptcies. This finding has important policy implications, because financial institutions that do not use soft information risk further deterioration in their lending portfolios.

The Bank of Canada’s current suite of models faces challenges in addressing network effects that integrate household and firm-level heterogeneity and their behaviours. We develop CANVAS, a Canadian behavioural agent-based model to contribute to the Bank’s next-generation modelling effort. CANVAS improves forecasting performance and expands capacity for model-based scenario analysis.

We develop a model to analyze the link between financial leverage, worker pay structure and the risk of job termination. Contrary to the conventional view, we show that even in the absence of any agency problem among workers, variable pay can be optimal despite workers being risk averse and firms risk neutral.

We model how securities dealers respond to regulations on leverage, position and liquidity such as those imposed by the Basel III framework. We show that while asset prices exhibit greater price impact, bid-ask spreads do not change and trading volumes may even increase.

This paper analyzes cross-border cryptocurrency flows, focusing on Bitcoin and four major stablecoins. Using data for 162 countries, we identify the key determinants, including responses to weak economic conditions and demand for remittances. A COVID-19 case study supports these findings and emphasizes the role of cryptocurrencies in global finance.