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Spillover dynamics for systemic risk measurement using spatial financial time series models

机译:使用空间财务时间序列模型进行系统风险度量的溢出动态

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摘要

We extend the well-known static spatial Durbin model by introducing a time-varying spatial dependence parameter. The updating steps for this model are functions of past data and have information theoretic optimality properties. The static parameters are conveniently estimated by maximum likelihood. We establish the theoretical properties of the model and show that the maximum likelihood estimators of the static parameters are consistent and asymptotically normal. Using spatial weights based on cross-border lending data and European sovereign CDS spread data over the period 2009–2014, we find evidence of contagion in terms of high, time-varying spatial spillovers in the perceived credit riskiness of European sovereigns during the sovereign debt crisis. We find a particular downturn in spatial dependence in the second half of 2012 after the outright monetary transactions policy measures taken by the European Central Bank. Earlier non-standard monetary operations by the ECB did not induce such changes. The findings are robust to a wide range of alternative model specifications.
机译:通过引入时变空间相关性参数,我们扩展了著名的静态空间杜宾模型。该模型的更新步骤是过去数据的功能,并且具有信息理论上的最优性。方便地通过最大似然估计静态参数。我们建立了模型的理论性质,并表明静态参数的最大似然估计是一致且渐近正态的。使用基于跨境贷款数据和欧洲主权CDS分布数据(2009-2014年)的空间权重,我们发现了在主权债务期间欧洲主权国家感知到的信用风险的高时空空间溢出效应蔓延的证据危机。在欧洲中央银行采取了彻底的货币交易政策措施之后,我们发现2012年下半年空间依赖性出现了特别的下降。欧洲央行较早的非标准货币操作并未引起这种变化。这些发现对于各种替代模型规范都是可靠的。

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