Interbank Tiering and Money Center Banks

Abstract

Abstract:This paper provides evidence that interbank markets are tiered rather than flat, in the sense that most banks do not lend to each other directly but through money center banks acting as intermediaries. We capture the concept of tiering by developing a core-periphery model, and devise a procedure for fitting the model to real-world networks. Using Bundesbank data on bilateral interbank exposures among 1800 banks, we find strong evidence of tiering in the German banking system. Moreover, bankspecific features, such as balance sheet size, predict how banks position themselves in the interbank market. This link provides a promising avenue for understanding the formation of financial networks. Keywords:Interbank markets, intermediation, networks, tiering, core and periphery, market structureNon-technical summary This paper defines interbank tiering and provides a network characterization founded on intermediation. The interbank market is tiered when some banks intermediate between banks that do not extend credit among themselves. We capture this market structure by formulating a core-periphery model and devise a procedure for fitting the model to real-world networks. This can be thought of as running a regression, but instead of estimating a parameter that achieves the best linear fit, one determines the optimal set of core banks that achieves the best structural match between the observed network and a tiered structure of the same dimension. We show that our procedure delivers a core which is a strict subset of intermediaries, excluding those banks that play no essential role in holding together the interbank market. It also yields a measure of distance that aggregates the structural inconsistencies between the observed network and the nearest tiering model. We use this statistic to test formally whether the extent of tiering observed in the interbank market is significantly greater than what emerges in networks formed by random processes.Our empirical work relies on comprehensive Bundesbank statistics, which we use to construct the network of bilateral interbank positions between more than 2000 banks. While most banks simultaneously borrow and lend in the interbank market, we find that the core comprises only 2.7% of such intermediaries. Tiering thus delivers a strong refinement of the concept of intermediation. Throughout the available time span (1999Q1-2007Q4), the size and composition of the optimal core remain stable. This supports the view that we have identified a truly structural feature. Moreover, we show that the extent of tiering observed in the German interbank market cannot be replicated by standard random processes of network formation.The final part of the paper explores why the banking system organizes itself around a core of money center banks by testing whether balance sheet variables predict which kind of banks form the core. The probit regressions confirm that (only) large banks tend to belong to the core, even though economies of scale and scope play a limited role. Other bank-specific ...

Centrality-based Capital Allocations

“…As figures show, there are few very large total IB exposures, since the mean is between the 90 th and 95 th percentile, making the distribution highly skewed. Similar properties are observed for total assets, the total of large loans and Out Degrees, supporting the idea of a tiered system with few large banks that act as interbank broker-dealers connecting other financial institutions (see e.g., Craig and von Peter, 2014). 20…”

A Network View on Interbank Market Freezes

“…7 See, for example, Craig and von Peter (2014) for a study of the German interbank market. The notion of centrality in payment systems is more generally studied e.g.…”

The joint impact of bankruptcy costs, fire sales and cross-holdings on systemic risk in financial networks

“…In contrast to a deterministic approach, a probabilistic mechanism allows for an identification of the structure of a class of networks on the basis of appropriate statistical quantities. We choose two settings: Erdös-Rényi random networks (Erdös and Rényi (1959)), and a two-tiered (core-periphery) random graph model adapted to German interbank market data (extracted from Craig and von Peter (2014)). We also analyze an extension to multi-layer networks that capture heterogeneous business models.…”

“…Recent research on financial networks, however, suggests that core-periphery network models capture the structure of the interbank market (see, e.g., Craig and von Peter (2014) for the German interbank market, and van Lelyfeld and in't Veld (2014) for the Netherlands): Fig. 9 Level sets of the lowest capital adequacy ratio in the banking system C AR := min i∈N C AR i as a function of the buffer δ and the proportion ρ of the illiquid asset in an ENBF-model with α = 0.925, β = 0.9, and γ = 0.2.…”

“…As in the other case studies, we set n = 100, c = 0.15, and = 100. In addition, following Craig and von Peter (2014) who analyzed data from the German interbank market, we choose core-periphery parameters p CC =0.66, p C P =0.15, p PC =0.07, p P P =0.001, x CC =0.35,x C P =0.16,x PC =0.47,x P P =0.02.…”