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We explore the idea that the financial sector can be a source of non-fundamental risk to the rest of the economy. We also consider whether policy can be used to reduce this risk—either by increasing the supply of publicly backed safe assets or by reducing the demand for safe assets.

We propose a model to understand low observed migration rates by considering the interaction between location and wealth decisions. We look at different policies and find that temporary moving vouchers only slightly increase welfare, while lower housing regulations can decrease the welfare gap by lowering house prices nationwide.

The use of bank notes in Canada for payments has declined consistently for some time, and similar trends are evident in other countries. This has led some observers to predict a cashless society in the future.

This paper examines the interaction between quantitative easing (QE) and the securities lending facility (SLF) using a detailed dataset on Riksbank QE purchases, Swedish DMO SLF transactions and OTC repo deals. A theoretical model further shows how excess demand for assets and search frictions shift the SLF from a backstop to a first-resort tool.

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.

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.

How does the supply of nominal government debt affect the macroeconomy? To answer this question, we propose a portfolio-balance model of the yield curve in which inflation is determined through an interest rate rule.

Firms that grow rapidly have the potential to usher in new innovations, products or processes (Kogan et al. 2017), become superstar firms (Haltiwanger et al. 2013) and impact the aggregate labour share (Autor et al. 2020; De Loecker et al. 2020). We explore the use of supervised machine learning techniques to identify a population of nascent high-growth firms using Canadian administrative firm-level data.

We consider structural vector autoregressions that are identified through stochastic volatility. Our analysis focuses on whether a particular structural shock can be identified through heteroskedasticity without imposing any sign or exclusion restrictions.

We show how participants in Canada’s new high-value payment system save liquidity by exploiting the new gridlock resolution arrangement. The findings have important implications for the design of these systems and shed light on financial institutions’ liquidity preference.