This paper studies the long term consequences on workers' labour earnings of the credit crunch induced by the 2007-2008 financial crisis. We study the evolution of both employment and wages in a large sample of Italian workers followed for nine years after the start of the crisis. We rely on a unique matched bank-employer-employee administrative dataset to construct a firm-specific shock to credit supply, which identifies firms that, because of the collapse of the interbank market during the financial crisis, were unexpectedly affected by credit restrictions. We find that workers who were employed before the crisis in firms more exposed to the credit crunch experience persistent and sizable earnings losses, mainly due to a permanent drop in days worked. These effects are heterogeneous across workers, with high-type workers being more affected in the long run. Moreover, firms operating in areas with favorable labor market conditions react to the credit shock by hoarding high-type workers and displacing low-type ones. Under unfavorable labor market conditions instead, firms select to displace also high-type (and therefore more expensive) workers, even though wages do react to the slack. All in all, our results document persistent effects on the earnings distribution.
We use cookies to provide you with an optimal website experience. This includes cookies that are necessary for the operation of the site as well as cookies that are only used for anonymous statistical purposes, for comfort settings or to display personalized content. You can decide for yourself which categories you want to allow. Please note that based on your settings, you may not be able to use all of the site's functions.
Cookie settings
These necessary cookies are required to activate the core functionality of the website. An opt-out from these technologies is not available.
In order to further improve our offer and our website, we collect anonymous data for statistics and analyses. With the help of these cookies we can, for example, determine the number of visitors and the effect of certain pages on our website and optimize our content.