The outbreak of COVID-19 has significantly disrupted the economy. This paper attempts to quantify the macroeconomic impact of costly and deadly disasters in recent US history, and to translate these estimates into an analysis of the likely impact of COVID-19. A costly disaster series is...

Uncertainty about the future rises in recessions. But is uncertainty a source of business cycles or an endogenous response to them, and does the type of uncertainty matter? To address these questions, we propose a novel shock-restricted identification strategy. We find that sharply higher...

We integrate a high-frequency monetary event study into a mixed-frequency macro-finance model and structural estimation. The model and estimation allow for jumps at Fed announcements in investor beliefs, providing granular detail on why markets react to central bank communications. We find that...

This paper combines a data rich environment with a machine learning algorithm to provide new estimates of time-varying systematic expectational errors ("belief distortions") embedded in survey responses. We find that distortions are large on average even for professional forecasters, with all...

A single macroeconomic factor based on growth in the capital share of aggregate income exhibits significant explanatory power for expected returns across a range of equity characteristic portfolios and non-equity asset classes, with risk price estimates that are of the same sign and similar in...

We measure the nature and severity of a variety of belief distortions in market reactions to hundreds of economic news events using a new methodology that synthesizes estimation of a structural asset pricing model with algorithmic machine learning to quantify bias. We estimate that investors...

The outbreak of COVID-19 has significantly disrupted the economy. This paper attempts to quantify the macroeconomic impact of costly and deadly disasters in recent US history, and to translate these estimates into an analysis of the likely impact of COVID-19. A costly disaster series is...

It is well known that the covariance structure of the data alone is not enough to identify an SVAR, and the conventional approach is to impose restrictions on the parameters of the model based on a priori theoretical considerations. This paper suggests that much can be gained by requiring the...

Uncertainty about the future rises in recessions. But is uncertainty a source of business cycles or an endogenous response to them, and does the type of uncertainty matter? We propose a novel SVAR identification strategy to address these questions via inequality constraints on the structural...