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作 者:钟山 林木材 洪智武 ZHONG Shan;LIN Mucai;HONG Zhiwu(Wang Yanan Institute for Studies in Economics,Xiamen University;School of Statistics,Huaqiao University;Business School,China University of Political Science and Law)
机构地区:[1]厦门大学王亚南经济研究院,福建厦门361005 [2]华侨大学统计学院,福建厦门361021 [3]中国政法大学商学院,北京102249
出 处:《金融研究》2023年第6期20-37,共18页Journal of Financial Research
基 金:国家自然科学基金青年项目(72103068,72203237)的资助。
摘 要:中国货币政策传导依赖金融市场的基准利率体系,探讨货币政策在不同利率间的传导,对于货币政策分析具有重要意义。本文在货币政策冲击传导分析中引入金融网络模型,为其提供了结构性分析视角。首先,本文将DY溢出网络的信息溢出作结构性分解,由此所构建的信息溢出网络可刻画货币政策冲击在不同利率间的传导。其次,本文在实证中构建了由银行间市场基准利率所组成的时变DY溢出网络,并探讨了货币政策冲击对该网络的影响。实证结果表明,1天质押式回购利率处于总信息溢出的核心位置,信息的净溢出由货币市场指向国债市场。货币政策冲击显著降低了1天质押式回购利率的信息净溢出,并且货币政策冲击的信息由国债市场向货币市场溢出。机制分析表明,国债收益率中的预期收益率提高了其对货币政策冲击信息的溢出能力。In August 2020, the People's Bank of China released a white paper entitled “Participating in International Benchmark Interest Rate Reform and Improving China's Benchmark Interest Rate System”. This highlights that China's money, bond, credit and derivatives markets have each developed their own benchmark interest rates with considerable credibility, authority and market recognition. Thus, monetary policy shocks in China are transmitted to the financial market through the benchmark interest rate system. Any comprehensive evaluation of China's monetary policy transmission therefore requires a structural perspective to assess the transmission of shocks between benchmark interest rates.In this study, we incorporate a network perspective into our macro-financial analysis by constructing a structural shock information spillover network. We conduct an empirical analysis of the impact of monetary policy shocks on the interbank benchmark interest rate network. The empirical results reveal the structural characteristics and mechanisms of monetary policy transmission. Our study makes three main contributions to the literature.In terms of our theoretical contribution, we analyze the formation mechanism of the information spillover network constructed by Diebold and Yilmaz(2012, 2014), hereinafter referred to as the DY spillover network. The information spillover between network nodes reflects two types of correlation: the synchronous correlation between nodes stemming from the effect of common shocks and the dynamic correlation between nodes caused by a “contagion effect”. The total information spillover can be attributed to different common shocks, which enables us to construct an information spillover network of structural shocks that have the same properties as common shocks. The transmission of monetary policy shocks between interest rates can be regarded as the spillover of monetary policy shock information between nodes.Empirically, we explore the impact of monetary policy shocks on the spillover of the interba
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