This paper shows that newspaper articles contain timely economic signals that can materially improve nowcasts of real GDP growth for the euro area. Our text data is drawn from fifteen popular European newspapers, that collectively represent the four largest Euro area economies, and are machine...

Based on evidence gathered from a newly built large macroeconomic data set for the UK, labeled UK-MD and comparable to similar datasets for the US and Canada, it seems the most promising avenue for forecasting during the pandemic is to allow for general forms of nonlinearity by using machine...

This paper uses matched bank-firm-level data and the 2014 depreciation of the euro to show that exchange rate depreciations lead to increased bank loan supply of large banks with significant net foreign asset exposure. This increase in lending can be explained by a shift in credit towards both...

A large set of financial variables has only limited power to predict a latent factor common to the year-ahead forecast errors for real Gross Domestic Product (GDP) growth, the unemployment rate, and Consumer Price Index (CPI) inflation for three sets of professional forecasters: the Federal...

We propose a new framework for measuring uncertainty and its effects on the economy, based on a large VAR model with errors whose stochastic volatility is driven by two common unobservable factors, representing aggregate macroeconomic and financial uncertainty. The uncertainty measures can also...

We propose a new framework for measuring uncertainty and its effects on the economy, based on a large VAR model with errors whose stochastic volatility is driven by two common unobservable factors, representing aggregate macroeconomic and financial uncertainty. The uncertainty measures can also...

We propose a new empirical framework that jointly decomposes the conditional variance of economic time series into a common and a sector-specific uncertainty component. We apply our framework to a large dataset of disaggregated industrial production series for the US economy. Our results...

In the aftermath of the 2008 Global Financial Crisis (GFC), scholars and policymakers turned their attention to the role of uncertainty in amplifying the effects of economic or financial shocks on economic activity. A growing literature has focused on addressing this question. Most works find...

We propose a new empirical framework that jointly decomposes the conditional variance of economic time series into a common and a sector-specific uncertainty component. We apply our framework to a large dataset of disaggregated industrial production series for the US economy. Our results...

Using an asset pricing model of a multi-sector production economy with pandemic disasters, we explain the average stock price boom and significant cross-sectional variation of stock returns in the US and Japan during the COVID-19 pandemic recession. Two features of the pandemic, ambiguity and...