In this contribution, we exploit machine learning techniques to predict the risk of failure of firms. Then, we propose an empirical definition of zombies as firms that persist in a status of high risk, beyond the highest decile, after which we observe that the chances to transit to lower risk...

In this contribution, we propose machine learning techniques to predict zombie firms . First, we derive risk of failure by training and testing our algorithm on disclosed financial information and non-random missing values by 304,906 firms active in Italy in the period 2008-2017. Then, we spot...

Using panel data on Italian students from 2013 to 2019, we compare the effect of a student’s class rank to the effect of class quality in primary school on subsequent academic outcomes. We propose a new strategy to identify the impact of rank while controlling for peer effects, by leveraging...