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Improving the conduct of monetary policy is unlikely to be the main motivation for central banks to issue a central bank digital currency (CBDC). While some argue that a CBDC could allow more complex transfer schemes or the ability to break below the zero lower bound, we find these benefits might be small or difficult to realize in practice.

One argument for central bank digital currencies (CBDCs) is that without them, private and foreign digital monies could displace domestic currencies, threatening the central bank’s monetary policy and lender of last resort capabilities. I revisit this monetary sovereignty rationale and offer a wider view—one that considers a broader set of currency functions and captures important cross-country variation.

When a bank holds a lot of safe assets, it is well situated to deal with funding stress. But when all banks hold a lot of safe assets, a pecuniary externality implies that their (wholesale) funding costs increase. This reduces banks’ ability to hold capital buffers and thus, paradoxically, increases the frequency of funding stress.

Central banks face considerable uncertainty when conducting monetary policy. The COVID-19 pandemic brought this issue back to the forefront of policy discussions. We draw from academic literature to review key sources of uncertainty and how they affect the conduct of monetary policy.

This article focuses on the role that loans backed by housing collateral play in amplifying housing booms and, more generally, procyclicality in the housing market. The author uses a model developed to include borrower and lender households, as well as a housing market, to examine the impact that altering the loan-to-value ratio (either permanently or countercyclically) might have on the volatility of house prices and mortgage debt.

In 2006, the Bank initiated a research program exploring two alternatives to the current inflation-targeting framework: (i) lowering the inflation target and (ii) shifting to a price-level target. This article discusses progress to date, places the Bank's findings in the context of a broader literature, and identifies avenues for future research.

We present a two-country model featuring risky lending and cross-border interbank market frictions.

This article focuses on a quantitative method to identify financial system vulnerabilities, specifically, an imbalance indicator model (IIM) and its application to Canada. An IIM identifies potential vulnerabilities in a financial system by comparing current economic and financial data with data from periods leading up to past episodes of financial stress. It complements other sources of information - including market intelligence and regular monitoring of the economy - that policy-makers use to assess vulnerabilities.

Latency delays—known as “speed bumps”—are an intentional slowing of order flow by exchanges. Supporters contend that delays protect market makers from high-frequency arbitrage, while opponents warn that delays promote “quote fading” by market makers. We construct a model of informed trading in a fragmented market, where one market operates a conventional order book and the other imposes a latency delay on market orders.

This paper estimates a dynamic factor model (DFM) for nowcasting Canadian gross domestic product. The model is estimated with a mix of soft and hard indicators, and it features a high share of international data.