Please wait a minute...
金融研究  2024, Vol. 525 Issue (3): 20-37    
  本期目录 | 过刊浏览 | 高级检索 |
非核心负债业务、流动性渠道和银行业系统性风险:理论模型与经验分析
方意, 和文佳, 王琦
中国人民大学国家发展与战略研究院,北京 100872;
北京工商大学经济学院,北京 100048;
中央财经大学金融学院,北京 100098
Non-core Liabilities, Liquidity Channels and Banks' Systemic Risks:Theoretical Models and Empirical Analysis
FANG Yi, HE Wenjia, WANG Qi
National School of Development and Strategy, Renmin University of China;
School of Economics, Beijing Technology and Business University;
School of Finance, Central University of Finance and Economics
下载:  PDF (556KB) 
输出:  BibTeX | EndNote (RIS)      
摘要 非核心负债的非稳定性特征,是诱发银行系统性风险的关键因素。非核心负债突然中断(负债流动性下降),将导致银行不得不折价卖出非流动性资产予以偿还(资产流动性下降),进而诱发资本金损失及系统性风险上升。本文从理论模型和经验分析两个角度,剖析中国商业银行非核心负债对系统性风险的影响程度及机制。研究结果表明:首先,银行以非核心负债融资来投资非流动性资产是一种高风险行为,银行持有非核心负债的数量越多,其面临的系统性风险水平也将越高。其次,就影响机制而言,银行非核心负债通过资产抛售的折价水平(资产流动性)和非预期负债被收回的比例(负债流动性)影响系统性风险。当银行资产流动性水平或负债流动性水平下降时,同样的非核心负债数量会带来更高的系统性风险水平,反之亦然。最后,规模越大的银行,非核心负债对其系统性风险的影响越大。
服务
把本文推荐给朋友
加入引用管理器
E-mail Alert
RSS
作者相关文章
方意
和文佳
王琦
关键词:  商业银行  非核心负债  系统性风险  流动性风险    
Summary:  The interbank businesses of commercial banks serve as a crucial mechanism for managing short-term liquidity, adjusting fund surpluses and shortages, and optimizing resource allocation. However, these operations also entail various risks such as regulatory arbitrage, maturity mismatch, funds idling, and shadow banking. In recent years, it is not uncommon for domestic and foreign financial institutions to almost cause systemic risks due to the rapid growth of interbank businesses. For instance, in March 2023, Silicon Valley Bank and Signature Bank in the United States experienced consecutive crises due to liquidity problems stemming from unstable funding sources. According to the historical data from China's banking industry, the scale of non-core liabilities of deposit-taking financial companies increased from 1.66 trillion yuan to 13.95 trillion yuan from 2007 to 2016, while their proportion doubled during this period. Although deleveraging policies have reduced the proportion of interbank liabilities since 2017, its absolute scale remains high. The potential risk associated with excessive reliance on interbank liabilities of banks should not be underestimated.Interbank liabilities are classified as non-core liabilities, which possess inherent instability that can easily trigger liquidity risks on both the asset and liability sides of banks and liquidity risk is a significant contributor to systemic risk. In November 2023, the “Measures for the Capital Management of Commercial Banks” issued by China's General Administration of Financial Supervision increased the risk measurement weight assigned to interbank business, highlighting regulatory authorities' ongoing focus on preventing systemic risks associated with non-core liabilities.Starting from the perspective of non-core liabilities of banks, this paper discusses the theoretical mechanism and empirical evidence regarding the impact of non-core liabilities on banks' systemic risks through liquidity channels and draws the following conclusions. Firstly, banks relying on non-core liabilities financing to invest in illiquid assets will bring systemic risks, with larger banks experiencing a greater impact of non-core liabilities on their systemic risks. This paper replaces core explanatory variables and explained variables, changes the estimation method, considers risk events during the sample period, expands the sample based on KNN machine learning and news text sentiment data, and addresses endogeneity problems using heteroscedasticity-based instruments, Bartik instrumental variables, and Heckman two-stage model. The fundamental conclusion that non-core liabilities increase banks' systemic risk remains valid. Secondly, bank asset liquidity and liability liquidity serve as important mechanisms through which non-core liabilities affect systemic risks. The liquidity of bank is reflected in the discount rate applied to illiquid assets sold in advance; higher discount rates indicate greater asset liquidity risk. Liability liquidity is reflected in the unextended ratio of non-core liabilities; higher ratios imply increased liability liquidity risk. When faced with high levels of liquidity risk there is an enhanced positive impact of non-core liabilities on systemic risk due to excessive holdings of such debt by banks which exposes them to potential delays or failure in rolling over these obligations timely. In such scenarios where liability liquidity risk increases significantly, banks need to divest more illiquid assets for repaying non-core liabilities that have not yet been extended yet. If there is also a rise in asset liquidity risk during this period, it results in heightened capital losses for banks, thereby amplifying overall levels of systemic risk.Based on the aforementioned research findings, this paper proposes that banks and regulatory authorities should actively monitor the scale and growth rate of non-core liabilities of banks and put forward stricter non-core liabilities management requirements for larger banks, so as to proactively prevent the risk accumulation resulting from the expansion of illiquid assets relying on non-core liabilities, thereby effectively averting systemic risks in the banking sector. In terms of bank liquidity risk management, counter-cyclical preventive policies should be adopted. When the scale of non-core liabilities expands excessively fast, restrictions can tighten the overall bank liquidity, limit the growth of non-core liabilities, and then reduce bank's risk accumulation. When the banking systemic risks increase, it is appropriate to relax bank liquidity in order to minimize the capital loss caused by the decline in liquidity and effectively alleviate the systemic risk.
Keywords:  Commercial Bank    Non-core Liabilities    Systemic Risk    Liquidity Risk
JEL分类号:  E58   G21   G28  
基金资助: * 本文感谢国家社会科学基金重大项目(23&ZD058)的资助。
通讯作者:  和文佳,经济学博士,讲师,北京工商大学经济学院,E-mail: hewenjia@btbu.edu.cn.   
作者简介:  方 意,经济学博士,教授,中国人民大学国家发展与战略研究院,E-mail: fangyi@ruc.edu.cn.
王 琦,博士研究生,中央财经大学金融学院,E-mail: changanwq@126.com.
引用本文:    
方意, 和文佳, 王琦. 非核心负债业务、流动性渠道和银行业系统性风险:理论模型与经验分析[J]. 金融研究, 2024, 525(3): 20-37.
FANG Yi, HE Wenjia, WANG Qi. Non-core Liabilities, Liquidity Channels and Banks' Systemic Risks:Theoretical Models and Empirical Analysis. Journal of Financial Research, 2024, 525(3): 20-37.
链接本文:  
http://www.jryj.org.cn/CN/  或          http://www.jryj.org.cn/CN/Y2024/V525/I3/20
[1]陈国进、蒋晓宇、刘彦臻和赵向琴,2021,《资产透明度、监管套利与银行系统性风险》,《金融研究》第3期,第18~37页。
[2]杜勇、孙帆和邓旭,2021,《共同机构所有权与企业盈余管理》,《中国工业经济》第6期,第155~173页。
[3]方意、荆中博、吴姬和李政,2020,《非核心负债、尾部依赖与中国银行业系统性风险》,《世界经济》第4期,第123~144页。
[4]方意,2021,《前瞻性与逆周期性的系统性风险指标构建》,《经济研究》第9期,第191~208页。
[5]葛新宇、庄嘉莉和刘岩,2021,《贸易政策不确定性如何影响商业银行风险——对企业经营渠道的检验》,《中国工业经济》第8期,第133~151页。
[6]江艇,2022,《因果推断经验研究中的中介效应和调节效应》,《中国工业经济》第5期,第120~140页。
[7]马勇和李振,2019,《资金流动性与银行风险承担——来自中国银行业的经验证据》,《财贸经济》第7期,第67~81页。
[8]李政、刘淇和梁琪,2019,《基于经济金融关联网络的中国系统性风险防范研究》,《统计研究》第2期,第23~37页。
[9]刘冲、曾琪和刘莉亚,2023,《金融强监管、存贷长期化与企业短债长用》,《经济研究》第10期,第75~92页。
[10]潘彬、王去非和易振华,2018,《同业业务、流动性波动与中央银行流动性管理》,《经济研究》第6期,第21~35页。
[11]钱崇秀、邓凤娟和许林,2020,《商业银行期限错配缺口与流动性调整策略选择》,《国际金融研究》第8期,第66~76页。
[12]童中文、解晓洋和邓熳利,2018,《中国银行业系统性风险的“社会性消化”机制研究》,《经济研究》第2期,第124~139页。
[13]吴德胜、曹渊、汤灿和郝希阳,2021,《分类管控下的债务风险与风险传染网络研究》,《管理世界》第4期,第35~54页。
[14]项后军和曾琪,2019,《期限错配、流动性创造与银行脆弱性》,《财贸经济》第8期,第50~66页。
[15]项后军和周雄,2022,《流动性囤积视角下的影子银行及其监管》,《经济研究》第3期,第100~117页。
[16]Acharya, V.V., V. Viral, L.H. Pedersen, T. Philippon and M. Richardson, 2017, “Measuring Systemic Risk”,Review of Financial Studies, Vol.30(1), pp.2~47.
[17]Adrian, T. and M.K. Brunnermeier, 2016, “CoVaR”, American Economic Review, Vol.106(7), pp.1705~1741.
[18]Boone, J., 2008, “A New Way to Measure Competition”, Economic Journal, Vol.118(531), pp. 1245~1261.
[19]Brownlees, C. and R. F. Engle, 2017, “SRISK: A Conditional Capital Shortfall Measure of Systemic Risk”, Review of Financial Studies, Vol.30(1),pp.48~79.
[20]Brunnermeier, M. K., M. Sockin and W. Xiong, 2020, “China's Model of Managing the Financial System”, NBER Working Paper,No.27171.
[21]de Haan, J., Y. Fang and Z. B. Jing, 2020, “Does the Risk on Banks' Balance Sheets Predict Banking Crises? New Evidence for Developing Countries”, International Review of Economics and Finance ,Vol.68, pp.254~268.
[22]Drehmann, M. and K. Nikolaou, 2013, “Funding Liquidity risk: Definition and Measurement”,Journal of Banking & Finance, Vol.37(7), pp. 2173~2182.
[23]Duarte F. and T. M. Eisenbach, 2021, “Fire-Sale Spillovers and Systemic Risk”, The Journal of Finance, Vol.76(3), pp.1251-1294.
[24]Eisenbach, T., T. Keister, J.J. Mcandrews and T. Yorulmazer, 2014, “Stability of Funding Models: An Analytical Farmwork.” FRBNY Economic Policy Review,Vol.2, pp.29~47.
[25]Goldsmith-Pinkham, P., I. Sorkin and H. Swift, 2020, “Bartik instruments: What, when. Why, and how”,American Economic Review, Vol.110 (8): pp.2586~2624.
[26]Greenwood, R., A. Landier and D. Thesmar, 2015,“Vulnerable Banks”, Journal of Financial Economics, Vol.115(3),pp.471~485.
[27]Hahm, J. H., H. S. Shin and K. Shin, 2013,“Noncore Bank Liabilities and Financial Vulnerability”, Journal of Money, Credit and Banking, Vol.45(1),pp.3~36.
[28]Mullainathan, S. and J. Spiess, 2017, “Machine Learning: an Applied Econometric Approach”, Journal of Economic Perspectives, Vol.31(2), pp.87~106.
[29]Shin, H.S. and K.Shin, 2011, “Procyclicality and Monetary Aggregate”, NBER Working Papers, No.16836.
[1] 赵家悦, 卢锐, 柳建华, Jerry Cao. 涨跌停制度变革、股票流动性与资本市场表现[J]. 金融研究, 2024, 525(3): 113-131.
[2] 范中杰, 何平, 刘泽豪. 风险传染、银行间市场骤冷及防范化解政策——基于金融网络模型视角[J]. 金融研究, 2024, 524(2): 38-56.
[3] 李天时, 祝继高. 地方银行业集中度对地方性商业银行贷款配置效率的影响研究[J]. 金融研究, 2023, 519(9): 76-93.
[4] 朱宁, 曾恒煜, 于之倩. 中国商业银行运营效率研究 ——基于多阶段合作型网络DEA的实证分析[J]. 金融研究, 2023, 518(8): 37-54.
[5] 郭杰, 饶含. 商业银行债券融资与货币政策传导[J]. 金融研究, 2023, 515(5): 38-57.
[6] 李志辉, 朱明皓, 李源, 李政. 我国金融机构的系统性风险溢出研究:测度、渠道与防范对策[J]. 金融研究, 2023, 514(4): 55-73.
[7] 杨子晖, 张平淼, 林师涵. 系统性风险与企业财务危机预警——基于前沿机器学习的新视角[J]. 金融研究, 2022, 506(8): 152-170.
[8] 张伟平, 曹廷求. 中国房地产企业间系统性风险溢出效应分析——基于尾部风险网络模型[J]. 金融研究, 2022, 505(7): 94-114.
[9] 张琳, 廉永辉, 方意. 政策连续性与商业银行系统性风险[J]. 金融研究, 2022, 503(5): 95-113.
[10] 王永钦, 段白鸽, 钱佳辉. 中国的“影子保险”:来自监管自然实验的证据[J]. 金融研究, 2022, 502(4): 18-38.
[11] 潘敏, 刘红艳, 程子帅. 极端气候对商业银行风险承担的影响——来自中国地方性商业银行的经验证据[J]. 金融研究, 2022, 508(10): 39-57.
[12] 赵静, 郭晔. 金融产品持股与银行系统性风险——兼论《商业银行股权管理暂行办法》的影响[J]. 金融研究, 2022, 499(1): 57-75.
[13] 徐国祥, 吴婷, 王莹. 基于共同冲击和异质风险叠加传导的风险传染研究——来自中国上市银行网络的传染模拟[J]. 金融研究, 2021, 490(4): 38-54.
[14] 陈国进, 蒋晓宇, 刘彦臻, 赵向琴. 资产透明度、监管套利与银行系统性风险[J]. 金融研究, 2021, 489(3): 18-37.
[15] 邓伟, 宋敏, 刘敏. 借贷便利创新工具有效影响了商业银行贷款利率吗?[J]. 金融研究, 2021, 497(11): 60-78.
No Suggested Reading articles found!
Viewed
Full text


Abstract

Cited

  Shared   
  Discussed   
版权所有 © 《金融研究》编辑部
本系统由北京玛格泰克科技发展有限公司设计开发 技术支持:support@magtech.com.cn
京ICP备11029882号-1