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Funding structures affected the amount of financial stress different countries and sectors experienced during the spread of COVID-19 in early 2020. Policy responses targeting specific vulnerabilities were more effective at mitigating this stress than those supporting banks or the economy more broadly.

We build a tractable New Keynesian model to study and compare four types of monetary and fiscal policy: policy rate adjustments, quantitative easing, lump-sum fiscal transfers and government spending. We find that tax-financed fiscal policy is more stimulative than debt-financed policy, and optimal policy coordination needs at least two of these four policy instruments.

Many explanations for the decline in real interest rates over the last 30 years point to the role that population aging or rising income inequality plays in increasing the long-run aggregate demand for assets. Notwithstanding the importance of such factors, the starting point of this paper is to show that the major change driving household asset demand over this period is instead an increased desire—for a given age and income level—to hold assets.

Does consumption smoothing fundamentally decrease during macroeconomic disasters? This paper uses a large historical dataset (1870–2016) for 16 industrial economies to show that during macroeconomic disasters (e.g., wars, pandemics, depressions) aggregate consumption and income are significantly less decoupled than during normal times.

This paper studies, theoretically and empirically, the unintended consequences of mandatory retention rules in securitization. It proposes a novel model showing that while retention strengthens monitoring, it may also encourage banks to shift risk.

This paper measures how both geographical and cultural proximity of bank branches affect household credit choice and pricing. For credit products that require high levels of ex-ante screening, we find that both proximities can complement each other in reducing the cost of providing soft information, thereby increasing credit access.

This paper proposes a unique approach to simulate intraday transactions in the Canadian retail payments batch system when such transactions are unobtainable. The simulation procedure has potential for helping with data-deficient problems where only high-level aggregate information is available.

We develop an algorithm and run it on a hybrid quantum annealing solver to find an ordering of payments that reduces the amount of system liquidity necessary without substantially increasing payment delays.

Hurricanes disrupt oil production in the Gulf of Mexico because producers shut in oil platforms to safeguard lives and prevent damage. We examine the effects of these temporary oil supply shocks on real economic activity in the United States.

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.