We expect potential output growth to be higher than in the October 2020 reassessment. By 2024, growth will be slightly above its average growth from 2010 to 2019. We assess that the Canadian nominal neutral rate continues to lie in the range of 1.75 to 2.75 percent.
We expect global potential output growth to rise to 3 percent by 2022. Relative to the last assessment in October 2020, potential output growth has been revised up across all the regions. The range of the US neutral rate remains unchanged relative to the autumn 2020 assessment.
Standard monetary models adopt an infinite horizon with discounting. Testing these models in the lab requires implementing this horizon within a limited time frame. We compare three approaches to such an implementation and discuss their relative advantages.
We investigate the economic forces behind the secular decline in bond yields. Before the anchoring of inflation in the mid-1990s, nominal shocks drove inflation, output and bond yields. Afterward, the impacts of nominal shocks were much less significant.
Using Bank Note Distribution System data on the demand for cash up to September 2020, we find that demand was strong. This is true even though cash use for payments declined early in the pandemic. When mobility restrictions and lockdown measures were eased, cash use for payments increased sharply but remained less popular than electronic methods of payment.
One year later, we review the events that took place in Canadian fixed-income markets at the beginning of the COVID-19 crisis and propose potential policy research questions for future work.
Although credit cards are more expensive for merchants to accept than cash or debit cards, merchants typically pass through their costs evenly to all customers. Along with consumer card rewards and banking fees, this creates cross-subsidies between payment methods. Because higher-income individuals tend to use credit cards more than those with lower incomes, our results indicate that these cross-subsidies might lead to regressive distributional effects.
We demonstrate the ability of reinforcement learning techniques to estimate the best-response functions of banks participating in high-value payments systems—a real-world strategic game of incomplete information.