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We investigate the macroeconomic impacts of mothballed businesses—those that closed temporarily—on sectoral equilibrium prices after a negative demand shock. Our results suggest that pandemic fiscal support for temporary closures may have eased inflationary pressures.

We analyze monetary policy responses to AI in a two-sector New Keynesian model, distinguishing augmentation and automation. Both reduce labor demand, requiring accommodation that creates inflation trade-offs. Automation worsens them. Aggregate inflation depends on AI’s form and breadth, making policy stabilization more complex and aggregate data potentially misleading.

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.

Using highly disaggregated transaction-level trade data, we document the importance of new firm-level trade partner relationships and the addition of new products to existing relationships in driving aggregate trade flows.

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.

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.

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.

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 study whether the credit derivatives of firms reflect the risk from climate transition. We find that climate transition risk has asymmetric and significant economic impacts on the credit risk of more vulnerable firms, and negligible effects on other firms.