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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 examine how intermediary capitalization affects asset prices in a framework that allows for intermediary market power. We introduce a model in which capital-constrained intermediaries buy or trade an asset in an imperfectly competitive market, and we show that weaker capital constraints lead to both higher prices and intermediary markups.

I provide evidence that portfolio equity inflows can have expansionary effects on GDP and inflation if not offset by monetary policy. I use a shift-share instrument to estimate equity inflows based on plausibly exogenous timing of inflows into mutual funds with heterogeneous country portfolios.

This paper develops a general equilibrium model to assess central bank digital currency (CBDC) design in a monetary system where traditional banks and “crypto banks” (i.e., banks that issue stablecoins) coexist. We compare tokenized and non-tokenized CBDC, showing that their desirability depends on the reliability of private money provision, the availability of collateral assets and the features of the crypto sector.

Cover page

Chinese Coin Charms

The charms on the cover are part of the National Currency Collection of the Bank of Canada.

Photography by Gord Carter.

This paper theoretically and empirically examines the price impacts of liquidations in DeFi and how different liquidation mechanisms affect the price impacts.

This paper summarizes the literature on the performance of various extended monetary policy tools when conventional policy rates are constrained by the effective lower bound. We highlight issues that may arise when these tools are used by central banks of small open economies.

We perform an analysis to determine how well the introduction of a countercyclical loanto- value (LTV) ratio can reduce household indebtedness and housing price fluctuations compared with a monetary policy rule augmented with house price inflation.

Our layered machine learning framework can enhance real-time transaction monitoring in high-value payment systems, which are a central piece of a country’s financial infrastructure. When tested on data from Canadian payment systems, it demonstrated potential for accurately identifying anomalous transactions. This framework could help improve cyber and operational resilience of payment systems.

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.