Staff research

We study the competition between a welfare-maximizing public payment platform (e.g., CBDC or fast payment system) and a profit-maximizing private platform in a two-sided market, deriving optimal public pricing and showing how network effects, fragmentation, and policy mandates like zero fees or cost recovery shape welfare, usage, and fee incidence.

This note analyzes different economic models of a central bank digital currency (CBDC) ecosystem where the central bank chooses different levels of market involvement and usage of policy levers. The analysis suggests that there are trade-offs between the costs to the central bank and its ability to achieve policy goals like universal access.

A well-functioning monetary system is characterized by public and private forms of money that exchange at par as value flows freely between them. A relevant retail public money—whether in the form of cash, a central bank digital currency or both—is a necessary component of such a monetary system.

We review the nascent but fast-growing literature on central bank digital currencies (CBDCs), focusing on their potential impacts on private banks. We evaluate these impacts in three areas of traditional banking: payments, lending and liquidity and maturity transformation. We also take a broader look at CBDCs and highlight two promising directions for future research.

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.

We study the impact of the Bank of Canada’s choice of settlement mechanism in Lynx on participant behaviors, liquidity usage, payment delays and the overall operational efficiency of the new system.

We discuss the competition and innovation arguments for issuing a central bank digital currency (CBDC). A CBDC could be an effective competition policy tool for payments. A CBDC could also support the vibrancy of the digital economy. It could help solve market failures and foster competition and innovation in new digital payments markets.

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.

An anonymous token-based central bank digital currency (CBDC) would pose certain security risks to users. These risks arise from how balances are aggregated, from their transactional use and from the competition between suppliers of aggregation solutions.