C31 Cross-Sectional Models; Spatial Models; Treatment Effect Models; Quantile Regressions (Updated!)
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Causality is a widely-used concept in theoretical and empirical economics. The recent financial economics literature has used Granger causality to detect the presence of contemporaneous links between financial institutions and, in turn, to obtain a network structure. Subsequent studies combined the estimated networks with traditional pricing or risk measurement models to improve their fit to empirical data. In this paper, we provide two contributions: we show how to use a linear factor model as a device for estimating a combination of several networks that monitor the links across variables from different viewpoints; and we demonstrate that Granger causality should be combined with quantile-based causality when the focus is on risk propagation. The empirical evidence supports the latter claim.
The German financial market is often characterized as a bank-based system with strong bank-customer relationships. The corresponding notion of a housebank is closely related to the theoretical idea of relationship lending. It is the objective of this paper to provide a direct comparison between housebanks and "normal" banks as to their credit policy. Therefore, we analyze a new data set, representing a random sample of borrowers drawn from the credit portfolios of five leading German banks over a period of five years. We use credit-file data rather than industry survey data and, thus, focus the analysis on information that is directly related to actual credit decisions. In particular, we use bank-internal borrower rating data to evaluate borrower quality, and the bank's own assessment of its housebank status to control for information-intensive relationships.