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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.

This paper provides an overview of cryptoasset exchanges. We contrast their design with exchanges in traditional financial markets and discuss emerging regulatory trends and innovations aimed at solving the problems cryptoasset exchanges face.

We study the interaction between epidemics and economic decisions in a model that has silent transmission of the virus. We find that rational behaviour strongly diminishes the severity of the epidemic but worsens the economic recession. We also find that the detection and isolation of not only symptomatic individuals but also those who are infected and asymptomatic or mildly symptomatic can reduce the severity of the recession caused by the pandemic.

We compare the determinants of consumer inflation expectations in the US and Canada by analyzing two current surveys. We find that Canadian consumers rely more on professional forecasts and the history of actual inflation when forming their expectations, while US consumers rely more on their own lagged expectations.

Many explanations for the decline in real interest rates over the last 30 years point to the role that population aging or rising income inequality plays in increasing the long-run aggregate demand for assets. Notwithstanding the importance of such factors, the starting point of this paper is to show that the major change driving household asset demand over this period is instead an increased desire—for a given age and income level—to hold assets.

This article reviews selected papers that use machine learning for economics research and policy analysis. Our review highlights when machine learning is used in economics, the commonly preferred models and how those models are used.

We ask whether a weaker contribution of information and communication technologies (ICT) to productivity growth could account for the productivity slowdown observed in Canada since the early 2000s. To answer this question, we consider several methods capturing channels through which ICT could affect aggregate productivity growth.

Staff projections provided for the Bank of Canada's monetary policy decision process take into account the integration of Canada's very open economy within the global economy, as well as its close real and financial linkages with the United States. To provide inputs for this projection, the Bank has developed several models, including MUSE, NEUQ (the New European Quarterly Model), and BoC-GEM (Bank of Canada Global Economy Model), to analyze and forecast economic developments in the rest of the world. The authors focus on MUSE, the model currently used to describe interaction among the principal U.S. economic variables, including gross domestic product, inflation, interest rates, and the exchange rate. Brief descriptions are also provided of NEUQ and BoC-GEM.

This paper develops a model of firm heterogeneity, technological adoption, and urbanization. In the model, welfare is measured by household real income, and urbanization is measured by population density. I use the model to derive statistics that measure the effect of a new technology on productivity, welfare, and urbanization.