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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.

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.

Examining the incentives for banks to hold various assets on their balance sheets for use as collateral when the opportunity cost of doing so can be high; an outline of the complexity inherent in any modern risk-management system and review of possible strategies to improve the performance of risk management; causes and consequences of the changing pace of labour reallocation in Canada; description of the structure and functioning of BoC-GEM— an adaptation of the Global Economy Model— with examples of its recent application.

Prices of commodities, including metals, energy and agricultural products, rose markedly over the 2009–2010 period. Some observers have attributed a significant part of this increase in commodity prices to the U.S. Federal Reserve’s large-scale asset purchase (LSAP) programs.

The household debt-to-disposable income ratio in Canada increased from 110 per cent in 1999 to 127 per cent in 2007. This increase has raised questions about the ability of households to service their increased debt if faced with a negative economic or socio-economic shock.

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.

Model risk is a constant danger for financial economists using interest-rate forecasts for the purposes of monetary policy analysis, portfolio allocations, or risk-management decisions. Use of multiple models does not necessarily solve the problem as it greatly increases the work required and still leaves the question "which model forecast should one use?"

The Federal Reserve’s quantitative easing (QE) program has been accompanied by a flow of funds into emerging-market economies (EMEs) in search of higher returns.

We construct a small-open-economy, New Keynesian dynamic stochastic general-equilibrium model with real-financial linkages to analyze the effects of financial shocks and macroprudential policies on the Canadian economy. Our model has four key features.