Financial shocks generate a protracted and quantitatively important effect on real economic activity and financial markets only if the shocks are both negative and large. Otherwise, their role is quite modest. Financial shocks have become more important for economic fluctuations after the 2000...

Financial shocks represent a major driver of fluctuations in tail risk, defined as the 5th percentile of the forecast distributions of output and inflation. Since the variance and the asymmetry of the forecast distributions are largely driven by the left tail, financial shocks turn out to play a...

We use a dynamic factor model to provide a semi-structural representation for 101 quarterly US macroeconomic series. We find that (i) the US economy is well described by a number of structural shocks between two and five. Focusing on the four-shock specification, we identify, using sign...

We evaluate the role of financial conditions as predictors of macroeconomic risk first in the quantile regression framework of Adrian et al. (2019b), which allows for non-linearities, and then in a novel linear semi-structural model as proposed by Hasenzagl et al. (2018). We distinguish between...

Can discretionary increases in government spending stimulate the economy? We answer this question by taking into account both the information flow on fiscal measures and the role played by information frictions. Using a novel set of empirical proxies for fiscal news and agents’ misperceptions,...

We investigate the effects of fiscal policy communication on the propagation of government spending shocks. To this aim, we propose a new index measuring the coordination effects of policy communication on private agents' expectations. This index is based on the disagreement amongst US...

This Paper proposes a new forecasting method that exploits information from a large panel of time series. The method is based on the generalized dynamic factor model proposed in Forni, Hallin, Lippi, and Reichlin (2000), and takes advantage of the information on the dynamic covariance structure...

This paper shows how large-dimensional dynamic factor models are suitable for structural analysis. We establish sufficient conditions for identification of the structural shocks and the associated impulse response functions. In particular, we argue that, if the data follow an approximate factor...

In this paper, we investigate the presence of non-linearities in the transmission of geopolitical risk (GPR) shocks. Our methodology involves incorporating a non-linear function of the identified shock into a VARX model and examining its impulse response functions and historical decomposition....

When agents' information is imperfect and dispersed, existing measures of macroeconomic uncertainty based on the forecast error variance have two distinct drivers: the variance of the economic shock and the variance of the information dispersion. The former driver increases uncertainty and...