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Real growth in gross domestic product tends to be meaningfully higher when a large share of industries and demand components are growing—that is, when growth is broad across many fronts.

Models for macroeconomic forecasts do not usually take into account the risk of a crisis—that is, a sudden large decline in gross domestic product (GDP). However, policy-makers worry about such GDP tail risk because of its large social and economic costs.

This research develops a model in which the economy is directly influenced by how pessimistic or optimistic economic agents are about the future. The agents may hold different views and update them as new economic data become available.

I show that maturity considerations affect the optimal conduct of monetary and fiscal policy during a period of government debt reduction. I consider a New Keynesian model and study a dynamic game of monetary and fiscal policy authorities without commitment, characterizing the incentives that drive the choice of interest rate.

We study how input-output networks affect the speed of technology adoption. In particular, we model the decision to adopt the programming language Python 3 by software packages. Python 3 provides advanced features but is not backward compatible with Python 2, which implies it comes with adoption costs.

When players repeatedly face an identical or similar game (e.g., coordination game, technology adoption game, or product choice game), they may learn through experience to perform better in the future. This learning behaviour has important economic implications.

This paper studies the implications of model uncertainty for wealth distribution in a tractable general equilibrium model with a borrowing constraint and robustness à la Hansen and Sargent (2008). Households confront model uncertainty about the process driving the return of the risky asset, and they choose robust policies.

This paper looks at the implications for monetary policy of the widespread adoption of artificial intelligence and machine learning, which is sometimes called the “fourth industrial revolution.”

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.

I use a structural vector autoregression (SVAR) with sign restrictions to provide conditional evidence on the behavior of the US external finance premium (EFP). The results indicate that the excess bond premium, a proxy for the EFP, reacts countercyclically to supply and monetary policy shocks and procyclically to demand shocks.