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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.

Project Samara was a real‑world experiment testing distributed ledger technology and wholesale central bank digital money for bond issuance and settlement in Canada. It demonstrated technical feasibility and potential efficiency and risk‑reduction benefits, while highlighting important trade‑offs related to complexity, governance, and regulatory alignment.

We explore how many electronic funds transfer (EFT) systems can viably coexist within a jurisdiction at efficient scale by estimating the cost curve of the average EFT. We estimate the marginal cost to be approximately $0.55 per transaction, and the fixed cost to be approximately $83 million per year.

Can artificial intelligence (AI) think and act like a cash manager? In this paper we explore how generative AI agents can help manage liquidity, prioritize payments and optimize efficiency in real-time gross settlement systems.

We study how participants in the Lynx payment system use the net send limit (NSL) tool to control their intraday payment outflow levels. Our results show that participants typically adopt a “set it and forget it” approach to scheduling NSLs and sometimes have distinct intraday NSL adjustment behaviours.

We study consumer cash inventory behavior by developing a dynamic model of forward-looking consumers and estimating structural parameters of the model using detailed consumer survey data. Consumers facing holding and withdrawal costs solve a discrete-time continuous-control dynamic programming problem to optimally use cash at the point of sale.

We outline possible system architectures for an online retail central bank digital currency (CBDC) and identify one well-suited for basic payments. We analyze OpenCBDC 2PC, a representative system, finding such designs to be feasible, although some areas require further investigation. Our framing highlights other promising architectures for a retail CBDC.

This paper analyzes the optimal quantity of central bank reserves in an economy where reserves and other financial assets provide liquidity benefits. Using a static model, I derive a constrained Friedman rule that characterizes the socially optimal level of reserves, demonstrating that this quantity is neither necessarily large nor small but depends on the marginal benefits of reserves relative to alternative safe assets.

Privacy-enhancing technologies (PETs) could offer solutions to safeguard end-user privacy and meet rigorous data protection standards for central bank digital currencies. We consider how PETs can transform privacy design in financial systems and the implications of their broader adoption.

We simulate introducing a central bank digital currency (CBDC) and consider consumer adoption, merchant acceptance and usage at the point of sale. Modest adoption frictions significantly inhibit CBDC market penetration along all three dimensions. Incumbent responses to restore pre-CBDC market shares are moderate to small and further reduce the impact of a CBDC.