A Dynamic Network Model of the Unsecured Interbank Lending Market

F. Blasques, Falk Bräuning, I. van Lelyveld
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引用次数: 86

Abstract

We introduce a structural dynamic network model of the formation of lending relationships in the unsecured interbank market. Banks are subject to random liquidity shocks and can form links with potential trading partners to bilaterally Nash bargain about loan conditions. To reduce credit risk uncertainty, banks can engage in costly peer monitoring of counterparties. We estimate the structural model parameters by indirect inference using network statistics of the Dutch interbank market from 2008 to 2011. The estimated model accurately explains the high sparsity and stability of the lending network. In particular, peer monitoring and credit risk uncertainty are key factors in the formation of stable interbank lending relationships that are associated with improved credit conditions. Moreover, the estimated degree distribution of the lending network is highly skewed with a few very interconnected core banks and many peripheral banks that trade mainly with core banks. Shocks to credit risk uncertainty can lead to extended periods of low market activity, amplified by a reduction in peer monitoring. Finally, our monetary policy analysis shows that a wider interest rate corridor leads to a more active market through a direct effect on the outside options and an indirect multiplier effect by increasing banks' monitoring and search efforts.
无担保银行间拆借市场的动态网络模型
我们引入了一个无担保银行间市场贷款关系形成的结构动态网络模型。银行受到随机流动性冲击的影响,可以与潜在的贸易伙伴建立联系,就贷款条件进行双边纳什讨价还价。为了减少信贷风险的不确定性,银行可以对交易对手进行成本高昂的同行监控。本文利用荷兰银行间市场2008 - 2011年的网络统计数据,通过间接推理估计了结构模型参数。估计模型准确地解释了借贷网络的高稀疏性和稳定性。特别是,同业监督和信贷风险的不确定性是形成稳定的银行间贷款关系的关键因素,这与信贷条件的改善有关。此外,贷款网络的估计程度分布高度倾斜,少数核心银行相互联系非常紧密,而许多外围银行主要与核心银行进行交易。对信贷风险不确定性的冲击可能导致市场活动长期低迷,而同行监督的减少则会加剧这种低迷。最后,我们的货币政策分析表明,更宽的利率走廊通过对外部选择的直接影响和通过增加银行的监测和搜索努力产生的间接乘数效应,导致市场更加活跃。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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