A dynamic network model of the unsecured interbank lending market

Blasques, Francisco; Bräuning, Falk; Lelyveld, Iman van

doi:10.1016/j.jedc.2018.03.015

Cited by 48 publications

(29 citation statements)

References 57 publications

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“…The presence of monitoring in networks has been identified by a number of empirical papers but they are mostly reduced form in nature and cannot quantify the magnitude of monitoring costs nor explain the emergence of the network structure, e.g., Cocco et al (2009), Furfine (2001), Affinito (2012), ?. Blasques et al (2018) simulate a dynamic model of the overnight interbank market for 50 banks and recover parameters by matching characteristics of the network between 50 large banks in the Netherlands. While they focus on banks meeting liquidity shocks in the overnight market, we estimate monitoring between a disjoint set of lenders and borrowers in meeting persistent funding needs, which is consistent with the full sample of interbank loans.…”

Section: Literature Reviewmentioning

confidence: 99%

Intermediation in the Interbank Lending Market

Craig

Ma²

2020

Working Paper (Federal Reserve Bank of Cleveland)

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This paper studies systemic risk in the interbank market. We first establish that in the German interbank lending market, a few large banks intermediate funding flows between many smaller periphery banks and that shocks to these intermediary banks in the financial crisis spill over to the activities of the periphery banks. We then develop a network model in which banks trade off the costs and benefits of link formation to explain these patterns. The model is structurally estimated using banks' preferences as revealed by the observed network structure in the precrisis period. It explains why the interbank intermediation arrangement arises, estimates the frictions underlying the arrangement, and quantifies how shocks are transmitted across the network. Model estimates based on precrisis data successfully predict changes in networklinks and in lending arising from the crisis in out-of-sample tests. Finally, we quantify the systemic risk of a single intermediary and the impact of ECB funding in reducing this risk through model counterfactuals.

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Section: Literature Reviewmentioning

confidence: 99%

Intermediation in the Interbank Lending Market

Craig

Ma²

2020

Working Paper (Federal Reserve Bank of Cleveland)

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“…4 The endogenous matching process, generates a counterparty selection bias, and can be seen as a specification error in the spirit of Heckman (1979). 5 We show that the role played by money market-specific unobservable factors (such as monitoring and searching costs, see Afonso and Lagos, 2015;Blasques et al, 2016) and the presence of the central bank as a lender of last resort lead to a non-standard estimation framework that departs from a classic dyadic econometric model (Cameron and Miller, 2014;Kenny et al, 2006). To solve this issue we apply a control function approach to account for the selection bias.…”

Section: Introductionmentioning

confidence: 91%

“…A large number of theories have been proposed to explain the features of bilateral trades in OTC markets (see Afonso and Lagos, 2015;Bech and Monnet, 2016;Blasques et al, 2016;Duffie et al, 2005, among the others), but the empirical literature still lacks in providing econometric models and evidences to better understand these pairwise outcomes. While there are empirical studies investigating interbank markets after the 2008 crisis (Afonso et al, 2011;Angelini et al, 2011), few evidences about the European sovereign crisis are available in the literature.…”

Section: Introductionmentioning

confidence: 99%

Pairwise Trading in the Money Market During the European Sovereign Debt Crisis

Rainone

2017

SSRN Journal

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This paper studies over-the-counter (OTC) trading in the unsecured interbank market for euro funds. The goal of our analysis is to identify the determinants of the probability of trading, the bilateral rate, and the quantity exchanged during the European sovereign debt crisis. We show how the specific features of this market bring to a non-standard estimation framework. We propose a dyadic econometric model with shadow rates to control for potentially endogenous matching with the counterparty, and construct a unique dataset containing banks' characteristics and bilateral trades to study trading patterns. The estimates provide mild evidence towards the existence of shadow rates. Active monitoring decreased market access to low equity and illiquid borrowers, while dispersion in rates and quantities was mainly driven by banks' nationality, especially at the peak of the crisis.

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“…Lux (2015) introduces a simple dynamic agent-based model that, starting from a heterogeneous bank size distribution and relying on a reinforcement learning algorithm based on trust, allows the system to naturally evolve toward a core-periphery structure where core banks assume the role of mediators between the liquidity needs of many smaller banks. Blasques et al (2018) propose a dynamic network model of interbank lending for the Dutch interbank market, pointing out that credit-risk uncertainty and peer monitoring are driving factors for the sparse core-periphery structure. e paper is structured as follows.…”

Section: Introductionmentioning

confidence: 99%

Re-Creating Banking Networks under Decreasing Fixed Costs

Maringer

Craig

Paterlini

2019

Working Paper (Federal Reserve Bank of Cleveland)

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Theory emphasizes the central role of the structure of networks in the behavior of financial systems and their response to policy. Real-world networks, however, are rarely directly observable: Banks' assets and liabilities are typically known, but not who is lending how much and to whom. We first show how to simulate realistic networks that are based on balance-sheet information by minimizing costs where there is a fixed cost to forming a link. Second, we also show how to do this for a model with fixed costs that are decreasing in the number of links. To approach the optimization problem, we develop a new algorithm based on the transportation planning literature. Computational experiments find that the resulting networks are not only consistent with the balance sheets, but also resemble real-world financial networks in their density (which is sparse but not minimally dense) and in their core-periphery and disassortative structure.

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A dynamic network model of the unsecured interbank lending market

Cited by 48 publications

References 57 publications

Intermediation in the Interbank Lending Market

Intermediation in the Interbank Lending Market

Pairwise Trading in the Money Market During the European Sovereign Debt Crisis

Re-Creating Banking Networks under Decreasing Fixed Costs

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