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Natural disasters can create important challenges for monetary policy in resource-rich small open economies. Using a DSGE model calibrated to Canada, we show that most disasters operate as adverse supply shocks, lowering output and raising inflation, thereby creating a trade-off for monetary policy.

This paper develops a stress-testing framework in which banks strategically adjust their balance sheets in response to regulatory constraints and market conditions. Applied to Canada’s largest banks, it quantifies the effects of macroprudential policies on lending and identifies systemic vulnerabilities through reverse stress testing.

In a dynamic model with limited commitment, aggregate payout-based compensation induces managers to raise outside equity yet invest too little today. Per-share compensation eliminates the dilution motive and restores efficient investment, but it does so through slower capital accumulation that better protects incumbent shareholder value.

This paper develops Monte Carlo likelihood-ratio tests for determining the number of regimes in Markov switching models. Unlike most existing procedures, which focus on testing one versus two regimes, the proposed methods allow testing an arbitrary number of regimes. They are valid in finite samples, robust to identification problems, and applicable to nonstationary, multivariate, and Markov switching GARCH models.

This policy note examines how a non-interest-bearing retail central bank digital currency (CBDC) could affect the financial stability of Canada’s systemically important banks during a severe recession. Stress test results show that the banks remain resilient, maintaining key regulatory ratios even under high CBDC demand.

Using simulations of the Bank of Canada’s projection model, we assess inflation risks from greater supply-shock volatility and show that monetary policy faces sharper trade-offs, as stabilizing inflation increasingly comes at the cost of weaker real activity.

We show that in a heterogeneous economy, optimal policy after cost-push shocks raises short-term rates to curb inflation while lowering long-term rates to support indebted households, speeding investment and output recovery while increasing consumption inequality.

Growth in potential output is expected to drop from 2.3% in 2025 to 1.2% in 2026 given slowing population growth, US tariffs and trade policy uncertainty. It is then estimated to pick up to an average of 1.5% over 2027–29 as strengthening business and government investment supports trend labour productivity (TLP). Gradual adoption of artificial intelligence is also expected to lift TLP growth over the projection horizon.

As the economy emerges from a crisis, macroeconomic policy confronts a dilemma: a protracted stimulus can foster a more inclusive labor market recovery, yet risks igniting inflation that ultimately undermines workers’ welfare through real income erosion. This tension amplifies in the presence of the ZLB and aggregate capacity constraints. We embed this insight into a quantitative model of the US economy.

Recessions feature elevated uncertainty. We develop a nonlinear imperfect-information New Keynesian model where procyclical information quality generates endogenous countercyclical uncertainty and precautionary saving. This demand channel can overturn the inflationary impact of negative supply shocks, making them deflationary, unless monetary policy stabilizes the output gap.