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This report provides a detailed technical description of the updated MacroFinancial Risk Assessment Framework (MFRAF), which replaces the version described in Gauthier, Souissi and Liu (2014) as the Bank of Canada’s stress-testing model for banks with a focus on domestic systemically important banks (D-SIBs).

Annual research grants for a term of up to two years.

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.

I develop a population-based Markov chain Monte Carlo algorithm known as parallel tempering to estimate dynamic stochastic general equilibrium models. Parallel tempering approximates the posterior distribution of interest using a family of Markov chains with tempered posteriors.

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.

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 article summarizes the proceedings of an international research conference hosted by the Bank of Canada in November 2000. The conference marked the fiftieth anniversary of Canada's adoption of a flexible exchange rate, and its title recognizes the seminal contribution of Professor Milton Friedman's article "The Case for Flexible Exchange Rates." His keynote address to the conference is also summarized in the article. The conference papers re-examine many of the arguments raised by Friedman using recent developments in economic theory and econometric techniques. They investigate the experience of a wide range of industrialized and emerging-market economies. The main findings are that a strong case can be made for flexible exchange rates in economies that are large commodity exporters and that have credible low-inflation monetary policies and relatively well-developed financial systems.

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?

We propose an open-economy New Keynesian model with financial integration that allows financial intermediaries to hold foreign long-term bonds. We study the implications of financial integration on monetary policy transmission. Among various aspects of financial integration, the bond duration plays a major role. These results hold for conventional and unconventional monetary policies.