We provide the first empirical evidence on how media-driven narratives influence cross-border institutional investment flows. Applying natural language processing techniques to one-and-a-half million newspaper articles, we document substantial cross-country variation in sentiment and risk...

Investors' behavior in U.S. Treasuries - the world's safe asset - affects monetary policy transmission mechanisms, fiscal policy space, loan pricing, and international vulnerabilities. Yet it is not well understood for a simple reason: researchers, not having a clear picture of the Treasury...

We characterize how risk evolves during a crisis. Using high-frequency data, we find that the first two principal components (PCs) of the covariance matrix of global asset returns experience large, sudden, and temporary spikes coinciding with well-known crises - Covid-19 pandemic, Global...

We introduce a novel empirical decomposition of equity price growth rates in terms of equity holdings, based on market-clearing conditions. Although our sample holdings cover only an average of 5% of market capitalization, our reconstructed equity holdings account for, on average, 89% of the...

This paper provides a comprehensive analysis of the forecastability of the real price of natural gas in the United States at the monthly frequency considering a universe of models that differ in their complexity and economic content. Our key finding is that considerable reductions in...

VARs are often estimated with Bayesian techniques to cope with model dimensionality. The posterior means define a class of shrinkage estimators, indexed by hyperparameters that determine the relative weight on maximum likelihood estimates and prior means. In a Bayesian setting, it is natural to...

In this paper we use the functional vector autoregression (VAR) framework of Chang, Chen, and Schorfheide (2024) to study the effects of monetary policy shocks (conventional and informational) on the cross-sectional distribution of U.S. earnings (from the Current Population Survey), consumption,...

The substantial fluctuations in oil prices in the wake of the COVID-19 pandemic and the Russian invasion of Ukraine have highlighted the importance of tail events in the global market for crude oil which call for careful risk assessment. In this paper we focus on forecasting tail risks in the...

Sparse models, though long preferred and pursued by social scientists, can be ineffective or unstable relative to large models, for example, in economic predictions (Giannone et al., 2021). To achieve sparsity for economic interpretation while exploiting big data for superior empirical...

We quantify the macroeconomic effects of the tariff measures announced (but not entirely implemented yet) on Liberation Day (April 2nd, 2025) through the lens of a New-Keynesian two-country model calibrated to the US and the rest of the world. We study both a unilateral 10pp tariff increase and...