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 ...
Standard-Nutzungsbedingungen:Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden.Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen.Sofern die Verfasser die Dokumente unter Open-Content-Lizenzen (insbesondere CC-Lizenzen) zur Verfügung gestellt haben sollten, gelten abweichend von diesen Nutzungsbedingungen die in der dort genannten Lizenz gewährten Nutzungsrechte. iii Terms of use: Documents in AbstractThe network pattern of financial linkages is important in many areas of banking and finance. Yet bilateral linkages are often unobserved, and maximum entropy serves as the leading method for estimating counterparty exposures. This paper proposes an efficient alternative that combines information-theoretic arguments with economic incentives to produce more realistic interbank networks that preserve important characteristics of the original interbank market. The method loads the most probable links with the largest exposures consistent with the total lending and borrowing of each bank, yielding networks with minimum density. When used in a stress-testing context, the minimumdensity solution overestimates contagion, whereas maximum entropy underestimates it. Using the two benchmarks side by side defines a useful range that bounds the cost of systemic stress present in the true interbank network when counterparty exposures are unknown. JEL classification: G21, L14, D85, C63 Bank classification: Econometric and statistical methods; Financial institutions; Financial stability RésuméLe réseau de liens financiers est important dans de nombreux segments des secteurs bancaire et financier. Pourtant, dans bien des cas, les liens bilatéraux ne sont pas observés et la méthode de l'entropie maximale est la plus couramment utilisée pour estimer les expositions au risque de contrepartie. Dans leur étude, les auteurs proposent une solution de rechange efficace qui combine des arguments relevant de la théorie de l'information et des arguments économiques pour créer des réseaux interbancaires hypothétiques plus réalistes qui préservent les principales caractéristiques du marché interbancaire original. La méthode consiste à tenir compte des liens les plus probables en fonction de la taille des expositions entre les banques, selon le total des prêts et des emprunts de chacune, afin de générer des réseaux ayant une densité minimale. Dans le contexte des tests de résistance, la méthode axée sur la densité minimale surestime la contagion, alors que celle de l'entropie maximale la sous-estime. En ayant recours aux deux modèles en parallèle, on peut ainsi définir une fourchette utile qui délimite le coût attribuable aux tensions systémiques présentes dans le réseau interbancaire réel lorsque les expositions au risque de contrepartie sont inconnues.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
customersupport@researchsolutions.com
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.