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Privacy is a key aspect of a potential central bank digital currency system. We outline different technical choices to enact various privacy models while complying with the appropriate regulations. We develop a framework to evaluate privacy models and list key risks and trade-offs in privacy design.

Recent years have seen renewed interest in the regulation of interbank markets. A review of the literature in this area identifies two gaps: first, the literature has tended to make ad hoc assumptions about the interbank contract space, which makes it difficult to generate convincing policy prescriptions; second, the literature has tended to focus on ex-post interventions that kick in only after an interbank disruption has come underway (e.g., open-market operations, lender-of-last-resort interventions, bail-outs), rather than ex-ante prudential policies.

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.

Production efficiency and financial stability do not necessarily go hand in hand. With heterogeneity in banks’ abilities to screen borrowers, the market for loans becomes segmented and a self-competition mechanism arises. When heterogeneity increases, the intensive and extensive margins have opposite effects.

The impact of COVID-19 on Canadian households’ debt and unplanned savings varies by household income. Low-income and high-income households accrued unplanned savings, while middle-income households tended to accumulate more debt.

Annual research grants and expense allowances for a term of up to five years.

How should central banks design monetary policy in stable times and during recessions? We run a horse race between five monetary policy frameworks in an experimental laboratory to assess how well the different approaches can manage the public’s expectations and stabilize the economy.

How do Canadians pay their bills? 2019 survey data collected from over 4,000 Canadian consumers show how people’s bill payment choices vary with consumer characteristics and types of bills. The data also reveal that many consumers feel limited in their choices, which suggests that preferences of billers might play an important role as well.

We demonstrate the usefulness of payment systems data and machine learning models for macroeconomic predictions and provide a set of econometric tools to overcome associated challenges.