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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.

Indeed, the global financial crisis of the past two years has presented unique, stressful challenges that have forced us all to assess what has worked well and what needs to change. Today, I would like to review some of the critical thinking around these issues, primarily from the perspective of our work at the Bank of Canada.

We analyze the impact of interest rate policy on financial stability in an environment where banks can experience runs on their short-term liabilities, forcing them to sell assets at fire-sale prices.

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.

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.

We document an increase in deviations from short-term covered interest rate parity (CIP) in the first half of 2015. Since the Swiss National Bank’s (SNB) decision to abandon its minimum exchange rate policy, both the magnitude and volatility of deviations from CIP have increased across several currency pairs. The effect is particularly pronounced for pairs involving the Swiss franc.

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.

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.

This paper relaxes the Bayesian Nash equilibrium (BNE) assumption commonly imposed in empirical discrete choice games with incomplete information. Instead of assuming that players have unbiased/correct expectations, my model treats a player’s belief about the behavior of other players as an unrestricted unknown function. I study the joint identification of belief and payoff functions.

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.