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The U.S. recovery from the Great Recession has been slow relative to other postwar-era recoveries in the United States. Encouraged by loose lending standards in the pre-crisis period, U.S. households took on unsustainable amounts of debt, making them vulnerable to adverse shocks. Subsequently, a considerable drop in asset prices forced households to repair their balance sheets. While there has been progress in household deleveraging, the government sector now needs to delever, which will restrain growth over the next few years.

How should central banks design monetary policy in stable times and during recessions? We run a horse race between five monetary policy frameworks in an experimental laboratory to assess how well the different approaches can manage the public’s expectations and stabilize the economy.

Many explanations for the decline in real interest rates over the last 30 years point to the role that population aging or rising income inequality plays in increasing the long-run aggregate demand for assets. Notwithstanding the importance of such factors, the starting point of this paper is to show that the major change driving household asset demand over this period is instead an increased desire—for a given age and income level—to hold assets.

We ask whether a weaker contribution of information and communication technologies (ICT) to productivity growth could account for the productivity slowdown observed in Canada since the early 2000s. To answer this question, we consider several methods capturing channels through which ICT could affect aggregate productivity growth.

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.

Production efficiency and financial stability do not necessarily go hand in hand. With heterogeneity in banks’ abilities to screen borrowers, the market for loans becomes segmented and a self-competition mechanism arises. When heterogeneity increases, the intensive and extensive margins have opposite effects.

Unregulated capital flows are likely excessive during a stagflation episode, owing to a macroeconomic externality operating through the economy’s supply side. Inflows raise domestic wages and cause unwelcome upward pressure on firm costs, yet market forces likely generate such inflows. Optimal capital flow management instead requires net outflows.

Privacy is a key aspect of a potential central bank digital currency system. We outline different technical choices to enact various privacy models while complying with the appropriate regulations. We develop a framework to evaluate privacy models and list key risks and trade-offs in privacy design.

Solving macroeconomic models is difficult. One challenge is the occasionally binding constraint of the zero lower bound on nominal interest rates. This paper reviews various ways to solve models that include this feature.