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This paper argues that the introduction of the Banking Recovery and Resolution Directive (BRRD) improved market discipline in the European bank market for unsecured debt. The different impact of the BRRD on bank bonds provides a quasi-natural experiment that allows to study the effect of the BRRD within banks using a difference-in-difference approach. Identification is based on the fact that (otherwise identical) bonds of a given bank maturing before 2016 are explicitly protected from BRRD bail-in. The empirical results are consistent with the hypothesis that debt holders actively monitor banks and that the BRRD diminished bail-out expectations. Bank bonds subject to BRRD bail-in carry a 10 basis points bail-in premium in terms of the yield spread. While there is some evidence that the bail-in premium is more pronounced for non-GSIB banks and banks domiciled in peripheral European countries, weak capitalization is the main driver.
This paper provides an overview of how to use "big data" for economic research. We investigate the performance and ease of use of different Spark applications running on a distributed file system to enable the handling and analysis of data sets which were previously not usable due to their size. More specifically, we explain how to use Spark to (i) explore big data sets which exceed retail grade computers memory size and (ii) run typical econometric tasks including microeconometric, panel data and time series regression models which are prohibitively expensive to evaluate on stand-alone machines. By bridging the gap between the abstract concept of Spark and ready-to-use examples which can easily be altered to suite the researchers need, we provide economists and social scientists more generally with the theory and practice to handle the ever growing datasets available. The ease of reproducing the examples in this paper makes this guide a useful reference for researchers with a limited background in data handling and distributed computing.