The paper presents an alternative approach to measuring systemic illiquidity applicable to countries with frontier and emerging financial markets, where other existing methods are not applicable. We develop a novel Systemic Illiquidity Noise (SIN)-based measure, using the Nelson–Siegel–Svensson methodology in which we utilize the curve-fitting error as an indicator of financial system illiquidity. We empirically apply our method to a set of 10 divergent Central and Eastern Europe countries—Bulgaria, Croatia, Czechia, Estonia, Hungary, Latvia, Lithuania, Poland, Romania, and Slovakia—in the period of 2006–2020. The results show three periods of increased risk in the sample period: the global financial crisis, the European public debt crisis, and the COVID-19 pandemic. They also allow us to identify three divergent sets of countries with different systemic liquidity risk characteristics. The analysis also illustrates the impact of the introduction of the euro on systemic illiquidity risk. The proposed methodology may be of consequence for financial system regulators and macroprudential bodies: it allows for contemporaneous monitoring of discussed risk at a minimal cost using well-known models and easily accessible data.

中文翻译：

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基于系统性非流动性噪声的测量——前沿和新兴市场系统性流动性监测的解决方案

本文提出了一种衡量系统性流动性不足的替代方法，适用于具有前沿和新兴金融市场的国家，而其他现有方法不适用。我们使用 Nelson-Siegel-Svensson 方法开发了一种新的基于系统性非流动性噪声 (SIN) 的度量，其中我们利用曲线拟合误差作为金融系统非流动性的指标。在 2006 年至 2020 年期间，我们凭经验将我们的方法应用于一组 10 个不同的中欧和东欧国家——保加利亚、克罗地亚、捷克、爱沙尼亚、匈牙利、拉脱维亚、立陶宛、波兰、罗马尼亚和斯洛伐克。结果显示样本期间风险增加的三个时期：全球金融危机、欧洲公共债务危机和 COVID-19 大流行。它们还使我们能够识别具有不同系统性流动性风险特征的三组不同的国家。分析还说明了引入欧元对系统性非流动性风险的影响。所提议的方法可能对金融系统监管机构和宏观审慎机构具有重要意义：它允许使用众所周知的模型和易于访问的数据以最低成本同时监控所讨论的风险。