Search

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 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.

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.

Conventional models imply that central banks aiming to raise inflation should lower nominal rates and thus stimulate aggregate demand. However, several economists have recently challenged this conventional wisdom in favour of an alternative “neo-Fisherian’’ view under which higher nominal rates might in fact lead to higher 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.

We revisit an old question: how do financial constraints affect the transmission of monetary policy to the real economy? To answer this question, we propose a simple empirical strategy that combines firm-level employment and balance sheet data, identified monetary policy shocks and survey data on financing activities.

Markets for securitized assets were characterized by high liquidity prior to the recent financial crisis and by a sudden market dry-up at the onset of the crisis. A general equilibrium model with heterogeneous investment opportunities and information frictions predicts that, in boom periods or mild recessions, the degree of adverse selection in resale markets for securitized assets is limited because of the reputation-based guarantees by asset originators.

This paper explores the impact of extreme weather exposures on the financial outcomes of low-income households. Our findings highlight the heightened financial vulnerability of low-income households to environmental shocks and underscore the need for targeted policies.