We develop a structural vector autoregressive framework that combines external instruments and heteroskedasticity for identification of monetary policy shocks. We show that exploiting both types of information sharpens structural inference, allows testing the relevance and exogeneity condition...

We study the dynamic impact of Covid-19, economic mobility, and containment policy shocks. We use Bayesian panel structural vector autoregressions with daily data for 44 countries, identified through sign and zero restrictions. Incidence and mobility shocks raise cases and deaths significantly...

We study the multifaceted effects and persistence of trade policy shocks on financial markets in a structural vector autoregression. The model is identified via event day heteroskedasticity. We find that restrictive US trade policy shocks affect US and international stock prices heterogeneously,...

We study the multifaceted effects of trade policy shocks on financial markets using a structural vector autoregression identified via event day heteroskedasticity. We find that restrictive US trade policy shocks affect US and international stock prices heterogeneously, but generally negatively....

We estimate the dynamic effects of government spending shocks, using time-varying volatility in US data modeled through a Markov switching process. We find that the average government spending multiplier is significantly and persistently above one, driven by a crowding-in of private consumption...

We develop a vector autoregressive framework for combining the information in an external instrument with the information in the second moments of the data to identify latent monetary shocks in the United States. We show that the framework improves the identification of the structural model and...

We construct a news-based viral disease index and study the dynamic impact of epidemics on the world economy, using structural vector autoregressions. Epidemic shocks have persistently negative effects, both directly and indirectly, on affected countries and on world output. The shocks lead to a...

We develop a vector autoregressive framework that combines an external instrument and heteroskedasticity for the identification of monetary policy shocks. We show that exploiting both types of information sharpens structural inference, allows testing both the relevance and exogeneity condition...

We study the state-dependent trading behavior of financial intermediaries in the oil futures market, using structural vector autoregressions with Markov switching in heteroskedasticity. We decompose changes in futures price volatility into changes in the slopes of traders' demand curves and in...