We present a new measure of producers’ aggregate importance in a production economy with input-output linkages. Unlike existing measures, which capture the impact of an isolated TFP shock to a sector on aggregate output, we quantify how a sector amplifies simultaneous shocks to all producers...

We show how random subspace methods can be adapted to estimating local projections with many controls. Random subspace methods have their roots in the machine learning literature and are implemented by averaging over regressions estimated over different combinations of subsets of these controls....

We analyze the distributional consequences of uncertainty shocks in the U.S. economy at a business cycle frequency. Our findings reveal that uncertainty shocks have heterogeneous effects across income and wealth distribution. While their impact on income inequality appears marginal when measured...

An updated version of our Markov-switching model of U.S. real GDP clearly suggests the COVID-19 recession was more U shaped than L shaped. As with linear time series models, it is important to account for extreme outliers during the pandemic, but a simple decay function for volatility from...

We study the effects of financial uncertainty on investment dynamics in the U.S. using a vector autoregression with drifting parameters and stochastic volatilities. We find time-varying negative effects of financial uncertainty shocks on investment. These effects have declined in the post-WWII...

This paper estimates the impact of uncertainty shocks in a disaggregate model featuring state-level unemployment and uncertainty, which is measured using Google search data. We show that the disaggregate model captures important spillover effects which a model using aggregate data would overlook...

This survey features three parts. The first one covers the recent literature on domestic (i.e., country-specific) uncertainty and offers ten main takeaways. The second part reviews contributions on the fast-growing strand of the literature focusing on the macroeconomic effects of uncertainty...

The early history of cycles research involved locating turning points in the data. Later, the development of methods such as spectral analysis led to a focus on oscillations. A distinction between cycles and oscillations is needed - both imply turning points, but turning points do not...

This paper presents evidence on the macroeconomic adjustment of a resource-rich country to a resource boom using the effects of Chinese industrialisation on Australia from 1988 to 2016. An SVAR model is specified, incorporating a proxy for Chinese resource demand and commodity prices to identify...

We analyze if the transmission of oil price shocks on the U.S. economy has changed with the shale oil boom. To do so, we put forward a framework that allows for spillovers between industries and learning by doing (LBD) over time. We identify these spillovers using a time-varying parameter...