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We analyze monetary policy responses to AI in a two-sector New Keynesian model, distinguishing augmentation and automation. Both reduce labor demand, requiring accommodation that creates inflation trade-offs. Automation worsens them. Aggregate inflation depends on AI’s form and breadth, making policy stabilization more complex and aggregate data potentially misleading.

Recent consumer and merchant surveys show a decrease in the use of cash at the point of sale. Increasingly, consumers and merchants have access to a growing array of payment innovations as substitutes for cash.

Can monetary policy influence the neutral real interest rate (r-star)? Using a new statistical model, we show that interest rate hikes tend to lower r-star and long-run growth, but that monetary policy explains only a small share of the long-run decline in r-star.

Using highly disaggregated transaction-level trade data, we document the importance of new firm-level trade partner relationships and the addition of new products to existing relationships in driving aggregate trade flows.

With increasing levels of household debt in recent years, the number of households that may be vulnerable to a negative economic shock is rising as well. Decisions made by both the debtor and the creditor can contribute to insolvency. This article presents some stylized facts about insolvency in Canada’s household sector and analyzes the role of creditors in insolvencies. The average debt of an individual filing for bankruptcy is more than 1.5 times that of an average Canadian household; bankruptcy filers tend to be unemployed or in low-wage jobs, and are typically renters. The article reports that banks that approve more loans per branch, which is interpreted as less-intensive use of soft information (such as the loan officer’s assessment of the applicant’s character), experience more client bankruptcies. This finding has important policy implications, because financial institutions that do not use soft information risk further deterioration in their lending portfolios.

Business cycles are substantially correlated across countries. Yet most existing models are not able to generate substantial transmission through international trade. We show that the nature of such transmission depends fundamentally on the features determining the responsiveness of labor supply and labor demand to international relative prices.

We perform an analysis to determine how well the introduction of a countercyclical loanto- value (LTV) ratio can reduce household indebtedness and housing price fluctuations compared with a monetary policy rule augmented with house price inflation.

This paper analyzes cross-border cryptocurrency flows, focusing on Bitcoin and four major stablecoins. Using data for 162 countries, we identify the key determinants, including responses to weak economic conditions and demand for remittances. A COVID-19 case study supports these findings and emphasizes the role of cryptocurrencies in global finance.

Across several dimensions of lender of last resort policy, I highlight broad changes that have occurred since the 2008–09 global financial crisis and discuss some of the key challenges, choices and considerations facing the designers of central bank liquidity tools today.

We study whether the credit derivatives of firms reflect the risk from climate transition. We find that climate transition risk has asymmetric and significant economic impacts on the credit risk of more vulnerable firms, and negligible effects on other firms.