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Financial sector bailouts, while potentially beneficial during a crisis, might lead to excessive risk taking if anticipated. Taking expectations and aggregate risk implications into account, we show that bailouts can be welfare improving, but only if capital adequacy constraints are sufficiently tight.

A model of over-the-counter markets is proposed. Some asset buyers are informed in that they can identify high quality assets. Heterogeneous sellers with private information choose what type of buyers they want to trade with.

Governor Tiff Macklem discusses the potential impact of a trade conflict with the United States. He also launches the review of the Bank’s monetary policy framework.

We investigate the unintended consequences of the Home Affordable Refinance Program (HARP). Originally designed to help borrowers refinance after the 2008–09 global financial crisis, HARP inadvertently strengthened the market power of incumbent lenders by creating a cost advantage for them. Despite a 2013 policy rectifying this cost advantage, we still find significant welfare losses for borrowers.

This paper shows point identification in first-price auction models with risk aversion and unobserved auction heterogeneity by exploiting multiple bids from each auction and variation in the number of bidders. The required exclusion restriction is shown to be consistent with a large class of entry models.

We explore the consumer value proposition of a hypothetical Digital Canadian Dollar, adoption considerations and the users who would benefit most from this potential new payment method. We employ a design-thinking consultation methodology, allowing participants to interact with research prototypes of increasing complexity to reveal user preferences, constraints and adoption influences.

We develop a model in which a financial intermediary’s investment in risky assets—risk taking—is excessive due to limited liability and deposit insurance and characterize the policy tools that implement efficient risk taking.

We present a novel database of real-time data and forecasts from the Bank of Canada’s staff economic projections. We then provide a forecast evaluation for GDP growth and CPI inflation since 1982: we compare the staff forecasts with those from commonly used time-series models estimated with real-time data and with forecasts from other professional forecasters and provide standard bias tests.

Modeling and estimating persistent discrete data can be challenging. In this paper, we use an autoregressive panel probit model where the autocorrelation in the discrete variable is driven by the autocorrelation in the latent variable. In such a non-linear model, the autocorrelation in an unobserved variable results in an intractable likelihood containing high-dimensional integrals.

This paper looks at the implications for monetary policy of the widespread adoption of artificial intelligence and machine learning, which is sometimes called the “fourth industrial revolution.”