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The Bank of Canada considers a wide range of information and analysis before making a monetary policy decision and uses carefully articulated models to produce economic projections and to examine alternative scenarios. This article describes an ongoing research agenda at the Bank to develop models in which financial variables play an active role in the transmission of monetary policy actions to economic activity. Such models can help to analyze information from the financial side of the economy and to provide an overall view of the implications of financial developments for the current economic outlook. The authors also explain how this research can help address other issues relevant to the objectives of monetary policy, including how asset-price movements should be taken into account in the monetary policy framework.

Dion examines the evolution of Canadian productivity since the mid-1990s, using the United States as a benchmark. During this period, trend productivity growth in Canada remained modest, whereas the U.S. witnessed a strong resurgence. Among the factors identified as potential root causes of Canada's lower productivity performance are a lower investment in information and communications technology, reallocation and adjustment costs associated with large relative price movements, and a weak demand for innovation.

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.

I am honoured to address members of the Canadian Association for Business Economics. My remarks today will focus on critical issues that the Bank of Canada has studied over the past four years and how this research will inform our work as we move forward post crisis.

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.

Central banks face considerable uncertainty when conducting monetary policy. The COVID-19 pandemic brought this issue back to the forefront of policy discussions. We draw from academic literature to review key sources of uncertainty and how they affect the conduct of monetary policy.

This paper estimates a dynamic factor model (DFM) for nowcasting Canadian gross domestic product. The model is estimated with a mix of soft and hard indicators, and it features a high share of international data.

Allen and Engert report on recent research at the Bank of Canada on various aspects of efficiency in the Canadian banking industry. This research suggests that, overall, Canadian banks appear to be relatively efficient producers of financial services and they do not exercise monopoly or collusive-oligopoly power. The authors note the value of continuing to investigate opportunities to improve efficiency and competition in financial services in Canada.

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.