This paper aims at providing a primer on the use of big data in macroeconomic nowcasting and early estimation. We discuss: (i) a typology of big data characteristics relevant for macroeconomic nowcasting and early estimates, (ii) methods for features extraction from unstructured big data to...

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 assess to what extent indicators of financial conditions can be considered relevant determinants and predictors of macroeconomic aggregates. The main finding is that controlling for default risk and risk aversion measures improves the forecasts of output, employment and loans, but that this...

With reference to S&P 500 daily returns, we report evidence of an in-sample predictive accuracy breakdown for realized variance by GARCH models in correspondence to the March 2020 Covid-19 outbreak. However, a variety of macroeconomic risk, political and social media sentiment uncertainty...

The relationship between uncertainty and economic activity has attracted substantial interest in recent macroeconomics literature. Empirical work has mostly focused on short-run and medium-term effects of uncertainty shocks. However, there are a number of mechanisms that may cause a response of...