Center for Financial Studies (CFS)
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We studied information and interaction processes in six lending relationships between a universal bank and medium sized firms. The study is based on the credit files of the respective firms. If no problems occur in these lending relationships, bank monitoring is based mainly on cheap, retrospective and internal data. In case of distress, more expensive, prospective and external information is used. The level of monitoring and the willingness to renegotiate the lending relationship depends on what the lending officers can learn about the future prospects of the firm from the behaviour of the debtors. We identify both signalling and bonding activities. Such learning from past behaviour seems to allow monitoring at low cost, whereas the direct observation of the firm's investment outlook seems to be very costly. Also, too much knowledge about the firm's investments might leave the bank in a very strong bargaining position and distort investment incentives. Therefore, the traditional view of credit assessment as observation of the quality of a borrower's investment programme needs to be reconsidered.
Multiple lenders and corporate distress: evidence on debt restructuring : [Version Juni 2006]
(2006)
In the recent theoretical literature on lending risk, the coordination problem in multi-creditor relationships have been analyzed extensively. We address this topic empirically, relying on a unique panel data set that includes detailed credit-file information on distressed lending relationships in Germany. In particular, it includes information on creditor pools, a legal institution aiming at coordinating lender interests in borrower distress. We report three major findings. First, the existence of creditor pools increases the probability of workout success. Second, the results are consistent with coordination costs being positively related to pool size. Third, major determinants of pool formation are found to be the number of banks, the distribution of lending shares, and the severity of the distress shock.
We employ a representative sample of 80,972 Italian firms to forecast the drop in profits and the equity shortfall triggered by the COVID-19 lockdown. A 3-month lockdown generates an aggregate yearly drop in profits of about 10% of GDP, and 17% of sample firms, which employ 8.8% of the sample’s employees, become financially distressed. Distress is more frequent for small and medium-sized enterprises, for firms with high pre-COVID-19 leverage, and for firms belonging to the Manufacturing and Wholesale Trading sectors. Listed companies are less likely to enter distress, whereas the correlation between distress rates and family firm ownership is unclear.
(JEL G01, G32, G33)