Structural vector-autoregressive models are potentially very useful tools for guiding both macro- and microeconomic policy. In this paper, we present a recently developed method for exploiting non-Gaussianity in the data for estimating such models, with the aim of capturing the causal structure...

This paper contributes to a fast-growing literature on the impact of COVID-19 on the business economy, by focusing on how a particular group of firms - High-Growth Enterprises (HGEs) have been affected by COVID-19 across several dimensions, such as investment expectations, investment priorities,...

This paper introduces a little known category of estimators - Linear Non-Gaussian vector autoregression models that are acyclic or cyclic - imported from the machine learning literature, to revisit a well-known debate. Does exporting increase firm productivity? Or is it only more productive...

We analyse how the COVID-19 crisis impacted firms' employment levels and digitalisation efforts differently depending on their pre-crisis productivity, digitalisation and growth performance. We match the EIB Investment Survey with firm-level financial statements from the ORBIS database for 27 EU...