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Our layered machine learning framework can enhance real-time transaction monitoring in high-value payment systems, which are a central piece of a country’s financial infrastructure. When tested on data from Canadian payment systems, it demonstrated potential for accurately identifying anomalous transactions. This framework could help improve cyber and operational resilience of payment systems.

Many emerging-market economies (EMEs) have significantly improved their macroeconomic fundamentals and undergone structural reforms since the Asian crisis. These developments have enhanced the composition of capital flows to EMEs through an improved debt structure, a larger share of capital flows as foreign direct investment, and greater access to international debt markets for corporations in EMEs. Structural changes in the global financial landscape have also increased capital flows, bringing economic and financial benefits to EMEs. During the recent financial crisis, however, the opening up of capital accounts and increased financial and trade linkages left many countries vulnerable to external disruptions. Countries with sound fundamentals have weathered the crisis relatively well. Policy-makers in EMEs need to implement policies that support capital flows and ensure that controls imposed to deal with detrimental outflows during periods of stress or rapid inflows are only temporary.

Hurricanes disrupt oil production in the Gulf of Mexico because producers shut in oil platforms to safeguard lives and prevent damage. We examine the effects of these temporary oil supply shocks on real economic activity in the United States.

Cash is the preferred method of payment for small value transactions generally less than $25. We provide insight to this finding with a new theoretical model that characterizes and compares consumers’ costs of paying with cash to paying with cards for each transaction.

I provide evidence that portfolio equity inflows can have expansionary effects on GDP and inflation if not offset by monetary policy. I use a shift-share instrument to estimate equity inflows based on plausibly exogenous timing of inflows into mutual funds with heterogeneous country portfolios.

Using turnover ratios, Anderson and Lavoie describe the recent evolution of liquidity in various secondary government bond markets, focusing specifically on the market for Government of Canada securities. They attribute much of the recent variation in liquidity to such cyclical factors as changes in the interest rate environment and investors' appetite for risk, as well as developments in equity markets in the late 1990s. They also examine longer-term structural and policy-related trends, including the rate of adoption of financial and technological innovations and the level of government borrowing and debt-management initiatives.

Central bankers argue that programmable digital currencies may compromise the uniformity of money. We develop a stylized model to examine this argument and the trade-offs involved in circulating programmable money.

This paper studies short-term forecasting of Canadian real GDP and its expenditure components using combinations of nowcasts from different models. Starting with a medium-sized data set, we use a suite of common nowcasting tools for quarterly real GDP and its expenditure components.

This article begins with a brief examination of the Canadian mortgage market, focusing on the market’s evolution following changes to the Bank Act in 1992, which allowed chartered banks to enter the trust business, and the subsequent entrance of virtual banks and mortgage brokers.

This paper develops a general equilibrium model to assess central bank digital currency (CBDC) design in a monetary system where traditional banks and “crypto banks” (i.e., banks that issue stablecoins) coexist. We compare tokenized and non-tokenized CBDC, showing that their desirability depends on the reliability of private money provision, the availability of collateral assets and the features of the crypto sector.