Search

An essential element of the Bank of Canada's inflation-targeting framework is a floating exchange rate that is free to adjust in response to shocks that affect the Canadian and world economies. This floating rate plays an important role in the transmission mechanism for monetary policy. A practical question is how the Bank of Canada incorporates currency movements into the monetary policy decision-making process. Only after determining the cause and persistence of exchange rate change, and its likely net effect on aggregate demand, can the Bank decide on the appropriate policy response to keep inflation low, stable, and predictable. Ragan reviews the need to target inflation and the transmission mechanism for monetary policy, including the role of the exchange rate, before describing two types of exchange rate movements and their implications for monetary policy.

We study a novel policy tool—interest rate uncertainty—that can be used to discourage inefficient capital inflows and to adjust the composition of external account between shortterm securities and foreign direct investment (FDI).

Using data from the Bank Note Distribution System and consumer surveys, we find that bank notes in circulation remained high through 2021. Canadians continued to rely on electronic methods of payment, but a significant share also continued using cash for payments.

We study liquidity requirements in a framework with fire sales. The framework nests three common pricing mechanisms and produces the same observables. Absent risk-sharing considerations, the equilibrium is efficient with cash-in-the-market pricing; a liquidity requirement is optimal with second-best-use pricing; and a liquidity ceiling (i.e., a cap on liquid assets) is optimal with adverse selection.

We construct a macroeconomic estimate of total AI production in the United States, combining inference and R&D/training activities with quality adjustments to account for algorithmic progress. We then develop a nascent framework for "AI GDP" that tracks the AI economy as a coherent whole, complementing traditional national accounts.

This paper studies how financial shocks shape the distribution of output growth by introducing a quantile-augmented vector autoregression (QAVAR), which integrates quantile regressions into a structural VAR framework. The QAVAR preserves standard shock identification while delivering flexible, nonparametric forecasts of conditional moments and tail risk measures for gross domestic product.

This article examines the incentives for banks to hold various assets on their balance sheets for use as collateral when the opportunity cost of doing so can be high. Focusing on the five-year period (2002-07) that preceded the financial crisis, it examines the choices made by financial institutions among the assets that are pledged as collateral in Canada's Large Value Transfer System. This serves as a baseline for collateral-management practices during relatively normal times. The results of this study are important for policy-makers, especially the Bank of Canada, which is concerned both about the efficient functioning of fixed-income markets and about the credit risk it ultimately bears in insuring LVTS settlement. The results suggest that relative market liquidity and market-making capacity are important factors in the choice of securities pledged as collateral in the LVTS.

Many decentralized markets are able to attain a stable outcome despite the absence of a central authority (Roth and Vande Vate, 1990). A stable matching, however, need not be efficient if preferences are weak. This raises the question whether a decentralized market with weak preferences can attain Pareto efficiency in the absence of a central matchmaker.

There have been positive developments in the global financial system since the June Financial System Review, in part reflecting some encouraging signs about the global economy. At the same time, significant vulnerabilities remain. The Governing Council judges that the overall risk to the stability of Canada’s financial system has decreased from “high” to “elevated” over the past six months.

Do banks realize simultaneous trading losses because they invest in the same assets, or because different assets are subject to the same macro shocks? This paper decomposes the comovements of bank trading losses into two orthogonal channels: portfolio overlap and common shocks.