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This paper studies short-term forecasting of Canadian real GDP and its expenditure components using combinations of nowcasts from different models. Starting with a medium-sized data set, we use a suite of common nowcasting tools for quarterly real GDP and its expenditure components.

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 show that a large share of low-frequency (quarterly) movements in Canadian government bond yields can be explained by macroeconomic news, even though high-frequency (daily) changes are driven by other shocks. Furthermore, we show that US macro news—not domestic news— explains most of the quarterly variation in Canadian bond yields.

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.

Hurricanes disrupt oil production in the Gulf of Mexico because producers shut in oil platforms to safeguard lives and prevent damage. We examine the effects of these temporary oil supply shocks on real economic activity in the United States.

Cash is the preferred method of payment for small value transactions generally less than $25. We provide insight to this finding with a new theoretical model that characterizes and compares consumers’ costs of paying with cash to paying with cards for each transaction.

Raising liquidity when funding is stressed creates pressure on the financial market. Liquidating large quantities of assets depresses their prices and may amplify funding shocks. How do banks weathering a funding crisis contribute to contagion risk?

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.

Central bankers argue that programmable digital currencies may compromise the uniformity of money. We develop a stylized model to examine this argument and the trade-offs involved in circulating programmable money.

The official consumer price index (CPI) inflation measure, based on a fixed basket set before the COVID 19 pandemic, may not fully reflect what consumers are currently experiencing. We partnered with Statistics Canada to construct a more representative index for the pandemic with weights based on real-time transaction and survey data.