The Great Depression is infamous for banking panics, which were a symptomatic of a phenomenon that scholars have labeled a contagion of fear. Using geocoded, microdata on bank distress, we develop metrics that illuminate the incidence of these events and how banks that remained in operation...

We consolidate alternative ways for identifying stable and stressful scenarios in the S&P 500 market to construct contagion tests for recipient markets vulnerable to disturbances from this source market. The S&P 500 is decomposed into discrete conditions of: (1) Tranquil versus turbulent...

A new procedure to trace the sources of contagion in the oil-finance nexus is proposed. We do this by consolidating veteran rules derived from the empirical oil literature to filter oil supply, global demand, and oil demand shocks into discrete typical and extreme conditions. We show how these...

We investigate the relationship between oil prices and stock markets of selected oil importers and oil exporters at the time of the COVID-19 pandemic. We provide evidence in favour of energy contagion, in term of significantly higher correlations between oil and stock markets returns during...

This paper considers a first-order autoregressive panel data model with individual-specific effects and a heterogeneous autoregressive coefficient. It proposes estimators for the moments of the cross-sectional distribution of the autoregressive coefficients, with a focus on the first two...

This paper develops a machine-learning method that allows researchers to estimate heterogeneous treatment effects with panel data in a setting with many covariates. Our method, which we name the dynamic causal forest (DCF) method, extends the causal-forest method of Wager and Athey (2018) by...

We estimate a three-variate VAR using proxies of global financial uncertainty, the global financial cycle, and world industrial production to simulate the effects of the jump in financial uncertainty observed in correspondence of the Covid-19 outbreak. We predict the cumulative loss in world...

Oil market VAR models have become the standard tool for understanding the evolution of the real price of oil and its impact in the macro economy. As this literature has expanded at a rapid pace, it has become increasingly difficult for mainstream economists to understand the differences between...

This paper provides a detailed assessment of the real-time forecast accuracy of a wide range of vector autoregressive models (VAR) that allow for both structural change and indicators sampled at different frequencies. We extend the literature by evaluating a mixed-frequency time-varying...

We propose a novel identification strategy to measure monetary policy in a structural VAR. It is based exclusively on known past policy shocks, which are uncovered from high-frequency data, and does not rely on any theoretical a-priori restrictions. Our empirical analysis for the euro area...