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This article reviews recent work that uses principal-component analysis to extract information common to indicators from the Bank of Canada’s Business Outlook Survey (BOS). The authors use correlation analysis and an out-of-sample forecasting exercise to assess and compare the information content of the principal component with that of responses to key individual survey questions on growth in real gross domestic product and in real business investment. Results suggest that summarizing the common movements among BOS indicators may provide useful information for forecasting near-term growth in business investment. For growth in real gross domestic product, however, the survey’s balance of opinion on future sales growth appears to be more informative.

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.

This paper analyzes AI adoption among Canadian firms using December 2025 Business Leaders’ Pulse data. It finds that while personal use is widespread, operational adoption remains limited. Firms expect modest positive impacts on capital spending and small net negative effects on employment over the next three years.

Towards the end of the 1980s and into the early 1990s, the Canadian economy experienced a number of structural changes. These included free trade agreements (both the FTA and NAFTA), significant technological advances, deregulation in many sectors of the economy, the arrival of large, U.S.-based retailers, and the introduction of the GST.

Standard theories of price adjustment are based on the problem of a single-product firm, and therefore they may not be well suited to analyze price dynamics in the economy with multiproduct firms.

We report on the dynamics of Bitcoin awareness and ownership from 2016 to 2021, using the Bank of Canada's Bitcoin Omnibus Surveys (BTCOS). Our analysis also helps understand Bitcoin owners who adopted during the COVID-19 and how they differ from long-term owners. 

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.

Deputy Governor Lawrence Schembri discusses the historical evolution and future prospects for Canadian exports.

When countries are hit by supply shocks, central banks often face the dilemma of either looking through such shocks or reacting to them to ensure that inflation expectations remain anchored. In this paper, we propose a tractable framework to capture this dilemma and then explore optimal policy under a range of assumptions about how expectations are formed.