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Because commodity prices help determine Canada’s terms of trade, employment, income and, ultimately, inflation, it is important to understand what causes them to fluctuate. Since the early 1900s, there have been four commodity price supercycles—which we define as extended periods of boom and bust that can take decades to complete. Now in its downswing phase, the current supercycle started after growth in China and other emerging-market economies in the mid-1990s resulted in an unexpected demand shock. The extent of this downswing depends on numerous factors that are presently uncertain.

We explain how housing supply elasticities for Canadian cities are estimated. The procedure we use exploits the systematic differences in various cities’ sensitivity to regional house-price cycles.

We measure how the change in the share of constrained households in Canada following the COVID-19 recession has impacted the effectiveness of monetary policy.

The Bank of Canada has a mandate to “promote the economic and financial welfare of Canada,” primarily through the conduct of monetary policy and promotion of a safe, sound and efficient financial system. Understanding the macroeconomic and financial system impacts of climate change and the transition to a low-carbon economy is therefore a priority for the Bank.

Unusually large revisions to CPI-common in recent months stem from increased common movements across consumer price index components amid broad inflationary pressures. With recent revisions, CPI-common is more closely aligned with the Bank of Canada’s other two preferred measures of core inflation. However, caution is necessary when interpreting real-time estimates of CPI-common in the current environment.

Using the quantum Monte Carlo algorithm, we study whether quantum computing can improve the run time of economic applications and challenges in doing so. We apply the algorithm to two models: a stress testing bank model and a DSGE model solved with deep learning. We also present innovations in the algorithm and benchmark it to classical Monte Carlo.

The formulation of monetary policy at the Bank of Canada relies on the analysis of a broad set of economic information. Greater availability of immediate and detailed information would improve real-time economic decision making. Technological advances have provided an opportunity to exploit “big data” - the vast amount of digital data from business transactions, social media and networked computers. Big data can be a complement to traditional information sources, offering fresh insight for the monitoring of economic activity and inflation.

Natural disasters can create important challenges for monetary policy in resource-rich small open economies. Using a DSGE model calibrated to Canada, we show that most disasters operate as adverse supply shocks, lowering output and raising inflation, thereby creating a trade-off for monetary policy.

Do bond risk premiums influence the effects of debt maturity operations? Using a model with realistic bond risk premiums, we show that maturity operations have sizable effects on expected inflation and output when the central bank passively responds to inflation and the fiscal authority weakly responds to the debt level.

In this paper, we extend the state-space methodology proposed by Blagrave et al. (2015) and decompose Canadian potential output into trend labour productivity and trend labour input. As in Blagrave et al. (2015), we include output growth and inflation expectations from consensus forecasts to help refine our estimates.