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Using the Bank of Canada's Currency Information Management Strategy, we analyze the network structure traced by a bank note’s travel in circulation and find that the denomination of the bank note is important in our potential understanding of the demand and use of cash.

The goods and services sectors have experienced considerably different dynamics over the past three decades. Our goal in this paper is to understand how such contrasting behaviors at the sectoral level affect the aggregate level of trend inflation dynamics.

Recent work at the Bank of Canada studied the impact of default in Canada’s large-value payments system, and concluded that participants could readily manage their potential losses (McVanel 2005). In an extension of that work, the authors use a much larger set of daily payments data – with three times as many observations – to […]

This paper continues the work started by Bolder and Stréliski (1999) and considers two alternative classes of models for extracting zero-coupon and forward rates from a set of observed Government of Canada bond and treasury-bill prices.

Multi-stage production is widely recognized as an important feature of the modern global economy. This feature has been incorporated into many state-of-the-art quantitative trade models, and has been shown to deliver significant additional gains from international trade.

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.

When lenders cannot directly identify behavioural and rational borrowers, they use type scoring to track the likelihood of a borrower’s type. This leads to the partial pooling of borrowers, which results in rational borrowers subsidizing borrowing costs for behavioural borrowers. This, in turn, reduces the effectiveness of regulatory policies that target mistakes by behavioural borrowers.

This article examines what market conditions lead to extreme losses in global financial systems. Using a reverse stress testing approach, it introduces two measures of systemic risk by starting from the tail losses and working backward to identify the events most closely associated with them.

In a simple two-sector New Keynesian model, sticky prices generate a counterfactual negative comovement between the output of durable and nondurable goods following a monetary policy shock. We show that heterogeneous factor markets allow any combination of strictly positive price stickiness to generate positive output comovement.

We introduce generalized autoregressive gamma (GARG) processes, a class of autoregressive and moving-average processes in which each conditional moment dynamic is driven by a different and identifiable moving average of the variable of interest. We show that using GARG processes reduces pricing errors by substantially more than using existing autoregressive gamma processes does.