Using Dutch data we empirically investigate how financing and innovation vary across firm characteristics. We find that when firms face financial constraints, debt financing and innovation choices are not independent of firm characteristics, and R&D slows down. In the absence of financial...

This paper uses a nonlinear vector autoregression and a non-recursive identification strategy to show that an equal-sized uncertainty shock generates a larger contraction in real activity when growth is low (as in recessions) than when growth is high (as in expansions). An estimated New...

In this paper we extend the concept of serial correlation common features to panel data models. This analysis is motivated both by the need to develop a methodology to systematically stu dy and test for common structures and comovements in panel data with autocorrelation present and by an...

We employ real-time data available to the US monetary policy makers to estimate a Taylor rule augmented with a measure of financial uncertainty over the period 1969-2008. We find evidence in favor of a systematic response to financial uncertainty over and above that to expected inflation, output...

We estimate a nonlinear VAR model to study the real effects of monetary policy shocks in regimes characterized by high vs. low macroeconomic uncertainty. We find unexpected monetary policy moves to exert a substantially milder impact in presence of high uncertainty. We then exploit the set of...

We estimate a novel measure of global financial uncertainty (GFU) with a dynamic factor framework that jointly models global, regional, and country-specific factors. We quantify the impact of GFU shocks on global output with a VAR analysis that achieves set-identification via a combination of...