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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.

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.

Real rigidities that limit the responsiveness of real marginal cost to output are a key ingredient of sticky price models necessary to account for the dynamics of output and inflation. We argue here, in the spirit of Bils and Kahn (2000), that the behavior of marginal cost over the cycle is directly related to that of inventories, data on which is readily available.

The research findings highlighted in this article suggest that firm-size differences play a significant role in explaining the productivity gap between Canada and the United States. The authors review factors that lead to a positive relationship between productivity and size and then look at Canadian evidence of this relationship at the firm level. They quantify the extent to which the change in Canadian productivity as well as the Canada-U.S. productivity differences can be accounted for by the change in the importance of large firms and identify several factors that play a role in determining average firm size and aggregate productivity.

Can artificial intelligence (AI) think and act like a cash manager? In this paper we explore how generative AI agents can help manage liquidity, prioritize payments and optimize efficiency in real-time gross settlement systems.

Latency delays—known as “speed bumps”—are an intentional slowing of order flow by exchanges. Supporters contend that delays protect market makers from high-frequency arbitrage, while opponents warn that delays promote “quote fading” by market makers. We construct a model of informed trading in a fragmented market, where one market operates a conventional order book and the other imposes a latency delay on market orders.

Recent research suggests that quantitative easing (QE) may affect a broad range of asset prices through a portfolio balance channel. Using novel security-level holding data of individual US mutual funds, we establish evidence that portfolio rebalancing occurred both within and across funds.

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.

This discussion paper represents the work of the inter-agency Canadian OTC Derivatives Working Group (OTCD WG), formed in December 2009, that is chaired by the Bank of Canada and composed of members from the Office of the Superintendent of Financial Institutions (OSFI), the federal Department of Finance, the Ontario Securities Commission, the Autorité des marchés financiers, the Alberta Securities Commission and the Bank of 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.