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How can Surveys of Professional Forecasters (SPF) be used to improve inflation forecasts? By using US historical quarterly data on SPF forecasts, we provide better understanding of how we can use forecast disagreement to improve our own forecasts.

This paper analyzes the implications of the global financial cycle for conventional and unconventional monetary policies and macroprudential policy in small, open economies such as Canada. The paper starts by summarizing recent work on financial cycles and their growing correlation across borders.

Although the number of job applications has risen, job-finding rates remain relatively unchanged while job-separation rates have significantly declined. Rather than raising the probability of finding a job, we find that a rise in applications raises the probability of finding a good match, as evidenced by the decline in separation rates.

We revisit an old question: how do financial constraints affect the transmission of monetary policy to the real economy? To answer this question, we propose a simple empirical strategy that combines firm-level employment and balance sheet data, identified monetary policy shocks and survey data on financing activities.

Our layered machine learning framework can enhance real-time transaction monitoring in high-value payment systems, which are a central piece of a country’s financial infrastructure. When tested on data from Canadian payment systems, it demonstrated potential for accurately identifying anomalous transactions. This framework could help improve cyber and operational resilience of payment systems.

This note summarizes the key findings from Bank of Canada staff analytical work examining the reasons for the recent weakness in Canadian non-energy exports. Canada steadily lost market share in US non-energy imports between 2002 and 2017, mostly reflecting continued and broad-based competitiveness losses.

This paper shows that regional disparities in house price growth are more pronounced during house price busts than during booms. To explain this observation we construct a two-region currency union model incorporating a housing sector and extrapolative belief updating regarding house prices. To solve the model, we propose a new method that efficiently handles extrapolative belief updating in a wide class of structural models.

We use graphic processing unit computing to compare Bayesian and sample theory semiparametric binary response models. Our findings show that optimal bandwidth does not outperform regular bandwidth in binary semiparametric models.