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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.

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.

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Brass Cash Register, 1910

The register is part of the National Currency Collection, Bank of Canada.

Photographed by Gord Carter, Ottawa.

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.

Deputy Governor Timothy Lane discusses the benefits and challenges of international capital mobility.

I am honoured to address members of the Canadian Association for Business Economics. My remarks today will focus on critical issues that the Bank of Canada has studied over the past four years and how this research will inform our work as we move forward post crisis.

One of the most important factors that must be considered if countries are thinking about lowering the target level of inflation much below 2 per cent is the zero interest bound. Targeting inflation rates that are too low, the authors note, may restrict the ability of monetary policy to respond to economic shocks by limiting the amount by which interest rates can be eased.

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.

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.

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.