Banks' credit risk and its impact on banks' lending within a Banking Union

In this thesis we examine the determinants of banks’ risk-taking in the context of the Banking Union and subsequently the effect of banks’ risk on their role as lenders. To this purpose we utilize the quarterly supervisory bank level data, which are collected by the European Central Bank (ECB) starting from 2014 when the Single Supervisory Mechanism (SSM) was introduced in the European Union. According to theoretical work, centralised supranational supervision is expected to be "tougher" compared to the supervision exercised by the national supervisors, leading to lower risk-taking by banks that can have systemic impact. We investigate whether indeed the large banks which have come under the supervision of a supranational authority exhibit lower risk-taking compared to the banks which have remained under the supervision of national authorities. On the other hand, since large banks are more likely to receive implicit government guarantees when tail risk materialises, there is also the theoretical possibility that they are able to take on board more risk compared to non-systemically important banks (too-big-to-fail effect). We extend previous work examining the growth of non-performing loans (NPLs) from 2014 to 2019 that focused on the differences between the large and the small banks, in order to assess whether the centralisation or the size effect dominate. What was found is a negative relation between banks’ size and risk-taking behaviour, which could be attributed to the impact of the centralised supervision. From the results of these analysis we then examine, through dynamic panel data models, the importance of non-performing loans in determining the performance of banks’ primary role: lending. In the first chapter we describe more in details the theoretical work by E.Farhi and J.Tirole (2018) and the too-big-to-fail effect, as well as the possible impact of high non-performing loans ratio on banks’ lending. The second part of the chapter is instead an overview of the variables and their meaning and the data used in the model. This chapter is followed by a review of panel data and econometric models. The models and estimators explained will then be used in the analyses presented in chapter 3. A final section for conclusions and comments on the results will close the work. The analysis performed seems to confirm what found from M.Farne and A.Vouldis (2021) and hence to support the hypothesis by E.Farhi and J.Tirole (2018) as regards the effect of supranational supervision on banks’ risk. The second part of analysis highlights the non-performing loans ratio and the leverage as main drivers of the behaviour of banks’ lending.