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We develop a dynamic model to capture key features of decentralized finance lending. We identify a price-liquidity feedback: the market outcome in any given period depends on agents' expectations about lending activities in future periods, with higher future price expectations leading to more lending and higher prices in that period.

I develop a method for Bayesian estimation of globally solved, non-linear macroeconomic models. The method uses a mixture density network to approximate the initial state distribution. The mixture density network results in more reliable posterior inference compared with the case when the initial states are set to their steady-state values.

How do outcomes of monetary and fiscal stabilization policies at the zero lower bound change when decision makers have finite planning horizons in the economy? We explore the effects of limited foresight on policy tools and the interaction between monetary and fiscal policy.

We present a model in which banks and other financial intermediaries face both occasionally binding borrowing constraints and costs of equity issuance. Near the steady state, these intermediaries can raise equity finance at no cost through retained earnings.

While the Bank of Canada's inflation-control target is specified in terms of the rate of increase in the total consumer price index, the Bank uses a measure of trend or "core" inflation as a short-term guide for its monetary policy actions. When the inflation targets were renewed in May 2001, the Bank announced that it was adopting a new measure of core inflation. This measure excludes the eight most volatile components of the CPI and adjusts the remaining components for the effect of changes in indirect taxes. In this article, the author discusses the definition of the new measure of core inflation and describes some of its advantages relative to the previous measure. He notes that the new measure has a firmer statistical basis, has a better correspondence with economic theory, and does a better job of predicting future changes in overall inflation. While the new measure has these advantages, the Bank will continue to monitor a broad range of indicators when assessing the likely future path for inflation.

We identify and quantify fiscal news shocks, compiling events (2001–2023) that altered the expected path of U.S. defense expenditure. For each event, we estimate market-implied shifts in expected spending. A shift-share analysis yields a two-year, metropolitan statistical area–level GDP multiplier of approximately 1 for U.S. military build-ups.

I show how to combine large numbers of forecasts using several approaches within the framework of a Bayesian predictive synthesis. I find techniques that choose and combine a handful of forecasts, known as global-local shrinkage priors, perform best.

We explore the drivers of the surge in inflation in Canada during the COVID-19 pandemic. This work is part of a joint effort by 11 central banks using the model developed by Bernanke and Blanchard (2023) to identify similarities and differences across economies.

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.