Staff working papers

Models with default options are hard to solve. We propose an extension of the endogenous grid method that solves default risk models more efficiently and accurately.

Many central banks are considering issuing a central bank digital currency (CBDC). This would introduce a new policy tool—interest on CBDC. We investigate how this new tool would interact with traditional monetary policy tools, such as the interest on central bank reserves.

We show that US banks price deposits almost uniformly across their branches and that this pricing practice is more important than increases in local market concentration in explaining the deposit rate dynamics following bank mergers.

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.

Digital currencies store balances in anonymous electronic addresses. This paper analyzes the trade-offs between the safety and convenience of aggregating balances in addresses, electronic wallets and banks.

How should policy be designed at high debt levels, when fiscal authorities have little room to adjust taxes? Assigning the monetary authority a role in achieving debt sustainability makes it less effective in stabilizing inflation and output.

We study how different monetary policies affect the yield curve and interact. Our study highlights the importance of the spillover structure across the yield curve for policy-making.

What are the main drivers behind the monetary policy reaction function of the People’s Bank of China?

We use retail payment data in conjunction with machine learning techniques to predict the effects of COVID-19 on the Canadian economy in near-real time. Our model yields a significant increase in macroeconomic prediction accuracy over a linear benchmark model.